Automatic Fire Detection in Video Sequences

Turgay Celik (Eastern Mediterranean University, Turkey)

In this paper, we propose a real-time fire-detector which combines foreground information with statistical color information to detect fires. The foreground information which is obtained using adaptive background information is verified by the statistical color information which is extracted using hand labeled fire pixels to determine whether the detected foreground object is a candidate for fire or not. The output of the both stages is analyzed in consecutive frames which is the verification process of fire that uses the fact that fire never stays stable in visual appearance. The frame processing rate of the detector is about 30 fps with image size of 176x144 which enables the proposed detector to be applied for real-time applications.

Adding geometrical terms to shadow detection process

László Havasi (Peter Pazmany Catholic University, Hungary)

The elimination of strong shadow in outdoor scenes contain-ing human activity is addressed in the paper. The main con-tribution of the introduced method is the integration of geo-metrical information into the shadow detection process. This novel approach takes into account the collinearity of shadow and light direction and completed with a simple colour based pre-filtering. The final classification step is carried out via a Bayesian iteration scheme which is general enough to handle further characteristics of the problem: weak shadow and reflection.

Human Model and Motion Based 3D Action Recognition in Multiple View Scenarios

Cristian Canton (Universitat Politecnica de Catalunya, Spain); Josep Casas (UPC - Technical University of Catalonia, Spain); Montse Pardas (Technical University of Catalonia, Spain)

This paper presents a novel view-independent approach to the recognition of human gestures of several people in low resolution sequences from multiple calibrated cameras. In contraposition with other multi-ocular gesture recognition systems based on generating a classification on a fusion of features coming from different views, our system performs a data fusion (3D representation of the scene) and then a feature extraction and classification. Motion descriptors introduced by Bobick et al. for 2D data are extended to 3D and a set of features based on 3D invariant statistical moments are computed. A simple ellipsoid body model is fit to incoming 3D data to capture in which body part the gesture occurs thus increasing the recognition ratio of the overall system and generating a more informative classification output. Finally, a Bayesian classifier is employed to perform recognition over a small set of actions. Results are provided showing the effectiveness of the proposed algorithm in a SmartRoom scenario.

Visual speech detection using mouth region intensities

Spyridon Siatras (Aristotle University of Thessaloniki, Greece); Nikos Nikolaidis (Aristotle University of Thessaloniki, Greece); Ioannis Pitas (ARISTOTLE UNIVERSITY OF THESSALONIKI, Greece)

In recent research efforts, the integration of visual cues into speech analysis systems has been proposed with favorable response. This paper introduces a novel approach for lip activity and visual speech detection. We argue that the large deviation and increased values of the number of pixels with low intensities that the mouth region of a speaking person demonstrates can be used as visual cues for detecting speech. We describe a statistical algorithm, based on detection theory, for the efficient characterization of speaking and silent intervals in video sequences. The proposed system has been tested into a number of video sequences with encouraging experimental results. Potential applications of the proposed system include speech intent detection, speaker determination and semantic video annotation.

Cooperative Background Modelling using Multiple Cameras Towards Human Detection in Smart-Rooms

Jose-Luis Landabaso (Technical University of Catalunya, Spain); Montse Pardas (Technical University of Catalonia, Spain)

Shape-from-Silhouette (SfS) is the common approach taken to reconstruct the Visual Hull which is later used in 3D-trackers and body fitting techniques. The Visual Hull is defined as the intersection of the visual cones formed by the back-projection of several 2D binary silhouettes into the 3D space. Silhouettes are usually extracted using a foreground classification process, which is performed independently in each camera view. In this paper we present a novel approach in which 2D-foreground classification is achieved in 3D accordance in a Bayesian framework. In our approach, instead of classifying images and reconstructing later, we simultaneously reconstruct and classify in the 3D space.

Active Video-Surveillance Based on Stereo and Infrared Imaging

Gabriele Pieri (CNR, Inst. of Information Science and Technologies, Italy); Ovidio Salvetti (ISTI-CNR, Italy)

Video-surveillance is a very actual and critical issue at the present time. Within this topic we address the problem of firstly identifying moving people in a scene through motion detection techniques, and subsequently categorising them in order to identify humans for tracking their movements. The use of stereo cameras, coupled with infrared vision, allows to apply this technique to images acquired through different and variable condition, and allows an a priori filtering based on the characteristics of such images to give evidence to objects emitting an higher radiance (i.e. higher temperature).

Contour Based Smoke Detection in Video Using Wavelets

Behcet Toreyin (Bilkent University, Turkey); Yigithan Dedeoglu (Bilkent University, Turkey); A. Enis Cetin (Bilkent University, Turkey)

This paper proposes a novel method to detect smoke in video. It is assumed the camera monitoring the scene is stationary. The smoke is semi-transparent at the early stages of a fire. Therefore edges present in image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. The background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Edges of the scene produce local extrema in the wavelet domain and a decrease in the energy content of these edges is an important indicator of smoke in the viewing range of the camera. Moreover, scene becomes grayish when there is smoke and this leads to a decrease in chrominance values of pixels. Periodic behavior in smoke boundaries is also analyzed using a Hidden Markov model (HMM) mimicking the temporal behavior of the smoke. In addition, boundary of smoke regions are represented in wavelet domain and high frequency nature of the boundaries of smoke regions is also used as a clue to model the smoke flicker.

Human Face Detection in Video Using Edge Projections

Mehmet Turkan (Bilkent University, Turkey); Ibrahim Onaran (Bilkent University, Turkey); Enis Çetin (Bilkent University, Turkey)

In this paper, a human face detection method in images and video is presented. After determining possible face candidate regions using color information, each region is filtered by a high-pass filter of a wavelet transform. In this way, edges of the region are highlighted, and a caricature-like representation of candidate regions is obtained. Horizontal, vertical and filter-like projections of the region are used as feature signals in dynamic programming (DP) and support vector machine (SVM) based classifiers. It turns out that SVM based classifier provides better detection rates compared to DP in our simulation studies.

Multimodal Fusion by Adaptive Compensation for Feature Uncertainty with Application to Audiovisual Speech Recognition

Athanassios Katsamanis (National Technical University of Athens, Greece); George Papandreou (National Technical University Athens, Greece); Vassilis Pitsikalis (National Technical University of Athens, Greece); Petros Maragos (National Technical University of Athens, Greece)

In pattern recognition one usually relies on measuring a set of informative features to perform tasks such as regression or classification. While the accuracy of feature measurements heavily depends on changing environmental conditions, studying the consequences of this fact has received relatively little attention to date. In this work we explicitly take into account uncertainty in feature measurements and we show in a rigorous probabilistic framework how the models used for classification should be adjusted to compensate for this effect. Our approach proves to be particularly fruitful in multimodal fusion scenarios, such as audio-visual speech recognition, where multiple streams of complementary features are integrated. For such applications, provided that an estimate of the measurement noise uncertainty for each feature stream is available, we show that the proposed framework leads to highly adaptive multimodal fusion rules which are widely applicable and easy to implement. We further show that previous multimodal fusion methods relying on stream weights fall under our scheme under certain assumptions; this provides novel insights into their applicability for various tasks and suggests new practical ways for estimating the stream weights adaptively. Preliminary experimental results in audio-visual speech recognition demonstrate the potential of our approach.

Opportunities and issues of Image Processing for Cultural Heritage Applications

Alessandro Piva (University of Florence, Italy); Vito Cappellini (University of Florence, Italy)

The application of image processing techniques for the analysis, the diagnostic and the restoration of artworks remains a very uncommon practise. Recently, however, there has been a greater interest on acquiring and processing image data of artworks: the efforts in this application field have been characterized by promising results, which proved the advantages that the use of digital image processing may have on several issues. In this paper the peculiarities and the state of the ar of this application field will be described.

Using Spanning Trees for Reduced Complexity Image Mosaicing

Nikos Nikolaidis (Aristotle University of Thessaloniki, Greece); Ioannis Pitas (ARISTOTLE UNIVERSITY OF THESSALONIKI, Greece)

Image mosaicing, i.e., reconstruction of an image from a set of overlapping sub-images, has numerous applications that include high resolution image acquisition of works of art. Unfortunately, optimal mosaicing has very large computational complexity that soon becomes prohibitive as the number of sub-images increases. In this paper, two methods which achieve significant computational savings by applying mosaicing in pairs of two sub-images at a time, without significant reconstruction losses, are proposed. Simulations are used to verify the computational efficiency and good performance in terms of matching error of the proposed techniques.

Automated Investigation of Archeological Vessels

Martin Kampel (Vienna University of Technology, Austria); Hubert Mara (Vienna University of Technology, Austria); Robert Sablatnig (Vienna University of Technology, Austria)

Motivated by the requirements of the present archaeology, we are developing an automated system for archaeological classification and reconstruction of ceramics. This paper shows a method to answer archaeological questions about the manufacturing process of ancient ceramics, which is important to determine the technological advancement of ancient culture. The method is based on the estimation of the pro- file lines of ceramic fragments, which can also be applied to complete vessels. With the enhancements shown in this paper, archaeologists get a tool to determine ancient manufacturing techniques.

Damages of Digitized Historical Images as Objects for Content Based Applications

Edoardo Ardizzone (Università degli Studi di Palermo, Italy); Haris Dindo (Università degli Studi di Palermo, Italy); Umberto Maniscalco (Istituto per le Applicazioni del Calcolo (I.A.C.) M. Picone - Italian National Research Council (C.N, Italy); Giuseppe Mazzola (Università degli Studi di Palermo, Italy)

This work presents the preliminary results achieved within a FIRB project aimed to develop innovative support tools for automatic or semi-automatic restoration of damaged digital images concerning archaeological and monumental inheritance of Mediterranean coast. In particular, this paper is focused on a methodology for describing image degradation and its meta-representation for content based storing and retrieval. Our innovative idea is to decompose and store in a conventional RDBMS the images content, considering the damages as objects of the images. Moreover, a set of descriptors(a subset of MPEG7 descriptors) is used for the damage meta representation aimed to content based application. Finally we developed a user-friendly database management tool for manipulating the contents of the database

The image processing system for art specimens: Nephele

Miroslav Benes (Institute of Information Theory and Automation, Czech Republic); Barbara Zitova (Institute of Information Theory and Automation, Czech Republic); Jan Flusser (Institute of Information Theory and Automation, Czech Republic); Janka Hradilova (Academic Laboratory of Materials Research of Paintings, Czech Republic); David Hradil (Academic Laboratory of Materials Research of Paintings, Czech Republic)

In our paper we introduce comprehensive solution for processing and archiving information about artwork specimens used in the course of art restoration - Nephele. The information processing based on image data is used in the procedure of identification of pigment and binder present in the artwork, which is very important issue for restorers. Proposed approach geometrically aligns images of microscopic cross-sections of artwork color layers - image registration method based on mutual information, and then creates preliminary color layer segmentation - modified k-means clustering. The archiving part of the Nephele enables creating database entries for painting materials research database, their storage, and creating text-based queries. In addition to these traditional database functions, advanced report retrieval is supported; based on the similarity of image data, comparing either the ultraviolet and visual spectra images (using co-occurence matrices and color similarity functions), or the energy dispersive X-ray images (using features computed from the wavelet decomposition of the data).

Multispectral UV Fluorescence Analysis of Painted Surfaces

Anna Pelagotti (INOA, Italy); Luca Pezzati (INOA, Italy); Alessandro Piva (University of Florence, Italy); Andrea Del Mastio (University of Florence - Media Integration and Communication Center, Italy)

A novel system has been developed to acquire digital multispectral ultraviolet (UV) induced visible fluorescence images of paintings. We present here the image processing needed to understand and further process the acquired multispectral UV fluorescence images.

Analysis of Multispectral Images of Paintings

Philippe Colantoni (Jean Monnet University, France); Ruven Pillay (C2RMF, France); Christian Lahanier (C2RMF, France); Denis Pitzalis (C2RMF, France)

One hundred paintings conserved in several museums have been scanned by the C2RMF using the multi-spectral CRISATEL camera. These high resolution images allow us to not only generate an accurate colour image under any chosen illuminant, but also allow us to reconstruct the reflectance spectra at each pixel. Such images can be used for a visual qualitative as well as measurement-based quantitative scientific analysis of the work of art. Several image processing tools have been developped to allow us to perform these analyses. The IIPImage system enables us to visualize high resolution multi-spectral 16 bit images, view image details in colour or for each spectral channel and to super-impose and compare different wavelengths. A complementary viewing system uses an innovative 3D graphics hardware-accelerated viewer to allow us to reconstruct the resulting colour dynamically while interactively changing the light spectrum. The system also allows us to perform segmentation, view the colour distribution for a particular colour-space and perform dynamic spectral reconstruction.

H.264 Coding Artifacts And Their Relation To Perceived Annoyance

Tobias Wolff (Darmstadt University of Technology, Germany); Hsin-Han Ho (University of California Santa Barbara, USA); John Foley (University of California Santa Barbara, USA); Sanjit K. Mitra (UCSB, USA)

In this study we investigate coding artifacts in H.264 baseline profile. A psychophysical experiment was conducted that collected data about the subjectively perceived annoyance of short video sequences as well as the perceived strength of three coding artifacts. The data provided by 52 subjects is analyzed with respect to bitrate and intra period of the encoded sequences. A new data analysis method is presented which is based on a granular data representation and enables the detection of multidimensional functional dependencies in data sets. This method is employed to establish a model for the perceived annoyance as a function of artifact strength.

Task impact on the visual attention in subjective image quality assessment

Alexandre Ninassi (University of Nantes, France); Olivier Le Meur (Thomson R&D, France); Patrick Le Callet (University of Nantes, France); Dominique Barba (Institut de Recherche en Communications et Cybernétique de Nantes, France); Arnaud Tirel (University of Nantes, France)

Visual attention is a main feature of the human visual system components. Knowing and using the mechanisms of the visual attention could help improving image quality assessment. But, which kind of saliency should be taken into account? A free-task visual selective attention or a quality oriented visual selective attention. We recorded and evaluated the discrepancy between these two types of visual attention. The results will be given to show the impact of the viewing task on visual strategy.

No-Reference perceptual quality assessment of colour image

Benjamin Bringier (SIC, Université de Poitiers, France); Noël RICHARD (Université de Poitiers, France); Chaker Larabi (SIC, Université de Poitiers, France); Christine Fernandez-Maloigne (SIC, Université de Poitriers, France)

Image quality assessment plays an important role in various image processing applications. In recent years, some objective image quality metrics correlated with perceived quality measurement have been developed. Two categories of metrics can be distinguished: with full-reference and noreference. Full-reference looks at decrease in image quality from some reference of ideal. No-reference approach attempts to model the judgment of image quality without the reference. Unfortunately, the universal image quality model is not on the horizon and empirical models establishes on psychophysical experimentation are generally used. In this paper, we present a new algorithm for quality assessment of colour reproduction based on human visual system modeling. A local contrast definition is used to assign quality scores. Finally, a good correlation is obtained between human evaluations and our method.

Estimation of accesible quality in noisy image compression

Nikolay Ponomarenko (National Aerospace University, Kharkov, Ukraine); Mikhail Zriakhov (National Aerospace University, Ukraine); Vladimir Lukin (National Aerospace University, Kharkov, Ukraine); Jaakko Astola (Tampere University of Technology, Finland); Karen Egiazarian (Tampere University of Technology, Finland)

A task of lossy compression of noisy images providing ac-cessible quality is considered. By accessible quality we mean minimal distortions of a compressed image with re-spect to the corresponding noise-free image that are ob-served for the case of optimal operation point (OOP). The ways of reaching OOP for noisy images are discussed. It is shown that this can be done in automatic mode with appro-priate accuracy. Investigations are performed for efficient DCT-based AGU coder for a set of test images. We also demonstrate that the proposed approach can be applied to automatic selection of compression ratio for lossy compres-sion of noise-free images.

No reference quality assessment of Internet multimedia services

Alessandro Neri (University of ROMA TRE, Italy); Marco Carli (University of Roma TRE, Italy); Marco Montenovo (HP C&I, Italy); Alessandro Perrot (HP C&I, Italy); Francesco Comi (University of Roma TRE, Italy)

In this paper an objective No Reference metric for assessing the quality degradations introduced by transmission over a heterogeneous IP network is presented. The proposed ap-proach is based on the analysis of the interframe correlation measured at the output of the rendering application. It does not require information about the kind of errors, delays and latencies that affected the link and countermeasures intro-duced by decoders in order to face the potential quality loss. Experimental results show the effectiveness of the proposed algorithm in approximating the assessments obtained with full reference metrics.

Intelligent Sharpness Enhancement for Video Post-Processing

Jorge Caviedes (Intel Corporation, USA)

Sharpness enhancement is one of the post-processing stages in the consumer electronics video chain that operates in an open-loop mode. Although adaptive behavior is possible, in general there is no feedback system aimed at maximizing perceived quality. In this paper we introduce a control system and metric for sharpness enhancement algorithms. We also discuss the options of implementing an internal or local control loop, i.e., to control the basic sharpness enhancement engine at the pixel or region level, and an external or global control loop for sharpness enhancement module.

4) Color Image Processing - 4 papers

Reduced-complexity Multiple Symbol Differential Detection for UWB Communications

Vincenzo Lottici (University of Pisa, Italy); Zhi Tian (Michigan Technological University, USA)

In ultra-wideband (UWB) communications, the typical signal propagation through dense multipath fading offers potentially very large multipath diversity, but at the same time complicates receiver design as far as channel estimation and multipath energy capture are concerned. To strike a desired balance, we propose a multi-symbol differential detection framework that bypasses training or costly channel estimation by the use of autocorrelation principle. Furthermore, resorting properly to the Viterbi algorithm enables to attain an efficient performance versus affordable complexity tradeoff solution. Simulation results demonstrate that the proposed detection scheme is remarkably robust with respect to the effects of both noise and multiple access interference.

UWB Receiver Design for low Resolution Quantization

Stefan Franz (University of Southern California, USA); Urbashi Mitra (University of Southern California, USA)

Digital implementation of ultra-wideband receivers requires analog-to-digital conversion (ADC) at an extremely high speed, thereby limiting the available bit resolution. Herein, a new family of receiver structures optimized and tailored to quantized observations is presented. The generalized-likelihood ratio test (GLRT) based on the quantized samples is derived and shown to provide performance improvements in comparison to the infinite resolution GLRT rule employed on the quantized received signal. Furthermore, simulation results reveal that four bits of resolution are sufficient to closely approach the performance of a full resolution receiver.

Narrowband Interference Suppression in Transmitted Reference UWB Receivers Using Sub-Band Notch Filters

Marco Pausini (Delft University of Technology, The Netherlands); Gerard Janssen (Delft University of Technology, The Netherlands)

The Transmitted-Reference (TR) signaling scheme in conjunction with the Auto-correlation Receivers (AcR) has gained popularity in the last few years as low-complexity system architecture for Ultra Wide Band (UWB) communications. Since the signal template is directly obtained from the received signal, not only the noise but also the interference caused by a narrowband (NB) system operating in the same bandwidth corrupt both the data and the reference pulses. In this paper we study the effects of a single-tone interferer on the performance of a TR systems, measured in terms of probability of error. We also propose a simple but effective way to counteract the NB interference, consisting of a bank of notch filters, suppressing the sub-band containing the NB signal.

Narrowband interference mitigation for a transmitted reference ultra-wideband receiver

Quang Hieu Dang (Delft University of Technology, The Netherlands); Alle Jan van der Veen (Delft University, The Netherlands)

Narrowband inteference (NBI) is of specific concern in transmitted reference ultrawide band (TR-UWB) communication systems. We consider NBI in high data rate applications where significant interframe interference is present due to a very short frame rate. Oversampling of the correlator output with respect to the frame rate is used to gather more information for the receiver. We formulate an approximate data model that includes the NBI terms, subsequently a receiver algorithm is derived.

Finger Selection for UWB Rake Receivers

Sinan Gezici (Princeton University, USA); Mung Chiang (Princeton University, USA); Hisashi Kobayashi (Princeton University, USA); H. Vincent Poor (Princeton University, USA)

The problem of choosing the multipath components to be employed at a selective Rake receiver, the finger selection problem, is considered for an impulse radio ultra-wideband system. First, the finger selection problem for MRC-Rake receivers is considered and the suboptimality of the conventional scheme is shown by formulating the optimal solution according to the SINR maximization criterion. Due to the complexity of the solution, a convex formulation is obtained by means of integer relaxation techniques. Then, the finger selection for MMSE-Rake receivers is studied and optimal and suboptimal schemes are presented. Finally, a genetic algorithm based solution is proposed for the finger selection problem, which works for various multipath combining schemes. Simulation studies are presented to compare the performance of different algorithms. Index Terms Ultra-wideband (UWB), impulse radio (IR), Rake receiver, convex optimization, integer programming, genetic algorithm (GA).

How to Efficiently Detect Different Data-Rate Communications in Multiuser Short-Range Impulse Radio UWB Systems

Simone Morosi (University of Firenze, Italy, Italy); Tiziano Bianchi (University of Florence, Italy)

Low and high data-rate applications can be foreseen for future ultra-wideband systems which are based on impulse radio and proper detection schemes have to be designed for the most general scenarios. In this paper an innovative frequency domain detection strategy is tested in two different indoor short-range communication scenarios where several mobile terminals transmit low or high data-rate flows to a base station. Both Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) criteria have been investigated and compared with the classical RAKE. The results show that the proposed approach is well suited for the considered scenarios.

Reduced Memory Modeling and Equalization of Second order FIR Volterra Channels in Non-coherent UWB Systems

Jac Romme (IMST, Germany); Klaus Witrisal (Graz University of Technology, Austria)

This paper investigates a combination of two approaches to obtain high-data-rate UWB communication over multipath radio channels, using low complexity, non-coherent receivers. The first approach targets to equalize the occurring \emph{non-linear} ISI using trellis-based equalization, while the second approach aims to reduce or even avoid ISI by dividing the spectral resources into (a few) sub-bands. Combination of both concepts allows for a complexity trade-off between equalizer and RF front-end. Firstly, a reduced-memory data model will be introduced for the non-linear sub-band channels, optimal in the sense of the MMSE criterion. This model is used to study the relationship between equalizer complexity and performance. The second part of the paper investigates the performance of the complete system, before and after forward error control. The system uses QPSK-TR signaling, but the key concepts are applicable to other non-coherent UWB systems as well.

Multi-Target Estimation of Heart and Respiration Rates Using Ultra Wideband Sensors

Natalia Rivera (Virginia Tech - Wake Forest University, USA)

Vital-signs monitoring devices continue to utilize invasive sensing methodologies, ranging from skin surface contact techniques such as the use of electrodes for measuring cardiac signals (ECG test), to more intrusive techniques such as the utilization of a facial mask for measuring gas exchange during respiration. In this paper, we present a wireless radar technique based on ultra-wideband (UWB) technology for non-invasive monitoring of heart and respiration rates. Our technique is based on the detection of chest-cavity motion through the measurement of UWB signal displacements due to this motion. We show that the technique provides accurate results even in the presence of multiple subjects. Specifically, we investigate the two techniques for estimating breathing and heart rates in the presence of multiple subjects: (1) the use of clustering algorithms to isolate the combined position and breathing/heart rate of multiple subjects and (2) the use of MUSIC to accurately estimate only the rates. Results are based on measurements from experiments with multiple subjects in a laboratory setting.

Analysis of Threshold-Based TOA Estimators in UWB Channels

Davide Dardari (University of Bologna, Italy); Chia-Chin Chong (NTT DoCoMo USA Labs, USA); Moe Win (Massachusetts Institute of Technology, USA)

In this paper we analyze and compare the performance of matched filter (MF) and energy detector (ED) time-of-arrival estimators based on thresholding in ultra-wide bandwidth (UWB) dense multipath channels. Closed-form expressions for the estimator bias and mean square error (MSE) are derived as a function of signal-to-noise ratio using a unified methodology. A comparison with results based on Monte Carlo simulation confirms the validity of our analytical approach. In addition, results based on experimental measurements in an indoor residential environment are presented as well. Our analysis enables us to determine the threshold value that minimizes the MSE, critical parameter for optimal estimator design. It is shown that the estimation accuracy mainly depends on large estimation errors due to peak ambiguities caused by multipath at the output of the MF or ED and on the fading statistics of the first path. The evaluation of the performance loss faced by ED estimators with respect to those based on MF is also carried out.

Blind CFO estimation for OFDM with constant modulus constellations: performance bounds and algorithms

Timo Roman (Helsinki University of Technology, Finland); Andreas Richter (Helsinki University of Technology, Finland); Visa Koivunen (Helsinki University of Technology, Finland)

In this paper, we derive the Cramer-Rao bound for blind carrier frequency offset (CFO) estimation in orthogonal frequency division multiplexing (OFDM) with constant modulus constellations. A blind maximum likelihood CFO estimator is also proposed. It achieves highly accurate frequency synchronization with a single OFDM block, regardless of multipath fading and without the need for null-subcarriers. The approach is thus very attractive for time and frequency selective channels where the CFO may be time varying. If additional information is available, such as a single pilot symbol, maximum likelihood estimates of channel parameters and transmitted data can be obtained as a byproduct. Finally, performance bounds are evaluated for several commonly encountered scenarios.

Time-Varying Communication Channels: Fundamentals, Recent Developments, and Open Problems

Gerald Matz (Vienna University of Technology, Austria); Franz Hlawatsch (Vienna University of Technology, Austria)

In many modern communication systems, the assumption of a locally time-invariant (block-fading) channel breaks down (e.g., due to growing user mobility, increasing data rates, and higher carrier frequencies). Fast time-varying channels feature significant Doppler spread (i.e., time selectivity) in addition to delay spread (frequency selectivity). In this tutorial paper, we review some basic characterizations and sparse representations (models) of time-varying channels. We then discuss several approaches recently proposed for the modeling, estimation, and equalization of time-varying channels, and we point out some related open problems and potential research directions.

Spatial Multiplexing with Linear Precoding in Time-Varying Channels with Limited Feedback

Geert Leus (Delft University of Technology, The Netherlands); Claude Simon (Delft University of Technology, The Netherlands); Nadia Khaled (Interuniversity Micro-Electronics Center (IMEC), Belgium)

Combining spatial multiplexing with linear unitary precoding allows for high data rates, but requires a feedback link from the receiver to the transmitter. We focus on quantizing and feeding back the precoder itself, since it outperforms quantized channel feedback. More specifically, we propose a modified precoder quantization approach that outperforms the conventional one. We investigate both the linear minimum mean square error (LMMSE) detector, which minimizes the mean square error (MSE) between the transmitted and estimated symbols, and the singular value decomposition (SVD) detector, which is a unitary detector that aims at diagonalizing the channel matrix. In this context, we illustrate that the LMMSE detector performs slightly better than the SVD detector. We also study precoder extrapolation, when the precoder is only fed back at a limited number of time instances, as well as a related detector extrapolation scheme for the LMMSE and SVD detector, when the channel is only known at some specific time instances. Simulation results illustrate the efficiency of the proposed extrapolation methods.

Banded Equalizers for MIMO-OFDM in fast Time-Varying Channels

Luca Rugini (University of Perugia, Italy); Paolo Banelli (University of Perugia, Italy)

We propose low-complexity equalizers for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems in frequency-selective time-varying channels, by extending the approach we formerly proposed for single-antenna OFDM systems. Specifically, by neglecting the intercarrier inter-ference (ICI) coming from faraway subcarriers, we design mini-mum mean-squared error (MMSE) block linear equalizers (BLE) and MMSE block decision-feedback equalizers (BDFE) that exploit a band LDL factorization algorithm. The complexity of the pro-posed banded equalizers is linear in the number of subcarriers, differently from conventional MMSE-BLE and MMSE-BDFE char-acterized by a cubic complexity. We also consider a receiver win-dow designed to minimize the power of the undesired ICI. Simula-tion results show that windowing is beneficial in taking under con-trol the complexity of the proposed equalizers with acceptable performance loss with respect to the conventional MMSE-BLE and MMSE-BDFE.

Estimation of Doubly-Selective Channels in Block Transmissions

Mounir Ghogho (University of Leeds, United Kingdom); Ananthram Swami (Army Research Lab., USA)

We propose to estimate time-varying frequency-selective channels using data-dependent superimposed training (DDST) and a basis expansion model (BEM). The proposed method is an extension of the DDST-based method recently proposed for time-invariant channels. The superimposed training consists of the sum of a known sequence and a data-dependent sequence, which is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. Symbol detection is performed using MMSE equalization.

Direct Equalization of Multiuser Doubly-Selective Channels Based on Superimposed Training

Shuangchi He (Auburn University, USA); Jitendra Tugnait (Auburn University, USA)

Design of doubly-selective linear equalizers for multiuser frequency-selective time-varying communications channels is considered using superimposed training and without first estimating the underlying channel response. Both the time-varying channel as well as the linear equalizers are assumed to be described by a complex exponential basis expansion model (CE-BEM). User-specific periodic (non-random) training sequences are arithmetically added (superimposed) to the respective information sequences at the transmitter before modulation and transmission. There is no loss in information rate. Knowledge of the superimposed training specific to the desired user and properties of the other training sequences are exploited to design the equalizers. An illustrative simulation example is presented.

Minimum-Energy Bandlimited Time-Variant Channel Prediction With Dynamic Subspace Selection

Thomas Zemen (ftw. Forschungszentrum Telekommunikation Wien, Austria); Christoph Mecklenbräuker (FTW, Austria); Bernard Fleury (Aalborg University, Denmark)

In current cellular communication systems the time-selective fading process is highly oversampled. We exploit this fact for time-variant flat-fading channel prediction by using dynamically selected predefined low dimensional subspaces spanned by discrete prolate spheroidal (DPS) sequences. The DPS sequences in each subspace exhibit a subspace-specific bandwidth matched to a certain Doppler frequency range. Additionally, DPS sequences are energy concentrated in a time interval matched to the channel observation interval. Both properties enable the application of DPS sequences for minimum-energy (ME) bandlimited prediction. The dimensions of the predefined subspaces are in the range from one to five for practical communication systems. The subspace used for ME bandlimited prediction is selected based on a probabilistic bound on the reconstruction error. In contrast, time-variant channel prediction based on non-orthogonal complex exponential basis functions needs Doppler frequency estimates for each propagation path which requires high computational complexity. We compare its performance (using perfectly known complex exponentials) with that of ME bandlimited prediction with dynamic subspace selection. In particular we analyze the mean square prediction error of the two schemes versus the number of discrete propagation paths.

Dependence Model and Network for Biomarker Identification and Cancer Classification

Peng Qiu (University of Maryland, College Park, USA); Z. Jane Wang (University of British Columbia, Canada); K.J. Ray Liu (Department of Electrical and Computer Engineering, University of Maryland, USA)

Of particular interest in this paper is to develop statistical and modeling approaches for protein biomarker discovery to provide new insights into the early detection and diagnosis of cancer, based on mass spectrometry (MS) data. In this paper, we propose to employ an ensemble dependence model (EDM)-based framework for cancer classification, protein dependence network reconstruction, and further for biomarker identification. The dependency revealed by the EDM reflects the functional relationships between MS peaks and thus provides some insights into the underlying cancer development mechanism. The EDM-based classification scheme is applied to real cancer MS datasets, and provides superior performance for cancer classification when compared with the popular Support Vector Machine algorithm. From the eigenvalue pattern of the dependence model, the dependence networks are constructed to identify cancer biomarkers. Furthermore, for the purpose of comparison, a classification-performance-based biomarker identification criterion is examined. The dependence-network-based biomarkers show much greater consistency in cross validation. Therefore, the proposed dependence-network-based scheme is promising for use as a cancer diagnostic classifier and predictor.

A Differential Biclustering Algorithm for Comparative Analysis of Gene Expression

Alain Tchagang (University of Minnesota, USA); Ahmed Tewfik (Prof. University of Minnesota, USA)

Convergences and divergences among related organisms (S.cerevisiae and C.albicans for example) or same organism (healthy and disease tissues for example) can often be traced to the differential expression of specific group of genes. Yet, algorithms to characterize such differences and similarities using gene expression data are not well developed. Given two related organisms A and B, we propose here a novel differential biclustering algorithm, that aims at finding convergent biclusters that is group of genes with similar functions that are conserved in A and B, and divergent biclusters that is group of genes with similar function in A (or B) but which play different role in B (or A). Uncovering such patterns can elucidate new insides about how related organisms have evolved or the role played by some group of genes during the development of some diseases. Our differential biclustering algorithm consists of two steps. The first step consists of using a parallel biclustering algorithm to uncover all qualified biclusters with coherent evolutions in each set of data. The second step consists of performing a differential analysis on the set of biclusters identified in step one, yielding a set of convergent biclusters and a set of divergent biclusters

Choosing the design parameters for protein lysate arrays

Andrea Hategan (Tampere University of Technology, Finland); Ioan Tabus (University of Tampere, Finland); Jaakko Astola (Tampere University of Technology, Finland)

Protein lysate array is a new technology for measuring the relative expressions of proteins, where the array image provides information about the concentrations (expressions) of a given protein for tens of patients or tissues. The array consists of replicated or serially diluted versions of the biological samples at several spots. When producing the lysate array the experimenter has to set several parameters, such as: the concentration of the sample solution to be printed at a certain spot, the concentration of the antibody solution, the number of dilutions, the number of replicates for each biological sample, and the dilution factor. Having the resulting image of intensities at all spots one can assume a nonlinear model and estimate the values of the relative protein expression levels for all biological samples. In this paper we study how the obtained model can be used to improve the design of the experiment, such that if a second lysate array will be produced, better design parameters will be selected. We propose a methodology for choosing the design parameters, and illustrate it with results for several lysate array data sets.

Spectral Analysis of DNA Sequences by Entropy Minimization

Lorenzo Galleani (Politecnico di Torino, Italy); Roberto Garello (Politecnico di Torino, Italy)

Spectral analysis can be applied to study base-base correlation in DNA sequences. A key role is played by the mapping between nucleotides and real/complex numbers. In this paper, we present a new approach where the mapping is not kept fixed: it is allowed to vary aiming to minimize the spectrum entropy, thus detecting the main hidden periodicities. The new technique is first introduced and discussed through a number of case studies, then extended to encompass time-frequency analysis.

A Sequential Monte Carlo Method for Motif Discovery

Kuo-Ching Liang (Columbia University, ? ); Xiaodong Wang (Columbia University, USA); Dimitris Anastassiou (Columbia University, USA)

We propose a sequential Monte Carlo (SMC)-based motif discovery algorithm that can efficiently detect motifs in datasets containing a large number of sequences. The statistical distribution of the motifs and the positions of the motifs within the sequences are estimated by the SMC algorithm. The proposed SMC motif discovery technique can locate motifs under a number of scenarios, including the single-block model, two-block model with unknown gap length, motifs of unknown lengths, motifs with unknown abundance, and sequences with multiple unique motifs. The accuracy of the SMC motif discovery algorithm is shown to be superior to that of the existing methods based on MCMC or EM algorithms. Furthermore, it is shown that the proposed method can be used to improve the results of existing motif discovery algorithms by using their results as the priors for the SMC algorithm.

Probabilistic Data Integration and Visualization for Understanding Transcriptional Regulation

Arvind Rao (University of Michigan, Ann Arbor, USA); Alfred Hero (University of Michigan, USA); David States (University of Michigan, Ann Arbor, USA); James Douglas Engel (University of Michigan, Ann Arbor, USA)

In this paper we propose a manifold embedding methodology to integrate heterogeneous sources of genomic data for the purpose of interpretation of transcriptional regulatory phenomena and subsequent visualization. Using the Gata3 gene as an example, we ask if it is possible to determine which genes (or their products) might be potentially involved in its tissue-specific regulation - based on evidence obtained from various available data sources. Our approach is based on co-embedding of genes onto a manifold wherein the proximity of neighbors is influenced by the probability of their interaction as reported from diverse data sources - i.e. the stronger the evidence for that gene-gene interaction, the closer they are.

Large-scale analysis of the human genome: from DNA sequence analysis to the modeling of replication in higher eukaryotes

Alain Arneodo (CNRS-Ecole Normale Suprieure de Lyon, France); Yves D'Aubenton-Carafa (CGM-CNRS, France); Benjamin Audit (ENS-Lyon, France); Edward Brodie of Brodie (ENS-Lyon, France); Samuel Nicolay (ENS-lyon, France); Philipppe St-Jean (ENS-Lyon, France); Claude Thermes (CGM-CNRS, France); Marie Touchon (CGM-CNRS, France); Cedric Vaillant (genopole, Evry, France)

We explore large-scale nucleotide compositional fluctuations along the human genome through the optics of the wavelet transform microscope. Analysis of the TA and GC skews reveals the existence of strand asymmetries associated to transcription and/or replication. The investigation of 14854 intron-containing genes shows that both skews display a characteristic step-like profile exhibiting sharp transitions between transcribed (finite bias) and non-transcribed (zero bias) regions. As we observe for 7 out of 9 origins of replication experimentally identified so far, the (AT+GC) skew exhibits rather sharp upward jumps, with a linear decreasing profile in between two successive jumps. We describe a multi-scale methodology that allows us to predict 1012 replication origins in the 22 human autosomal chromosomes. We present a model of replication with well-positioned replication origins and random termination sites that accounts for the observed characteristic serrated skew profiles. We emphasize these putative replication initiation zones as regions where the chromatin fiber is likely to be more open so that DNA be easily accessible. In the crowded environment of the cell nucleus, these intrinsic decondensed structural defects actually predisposes the fiber to spontaneously form rosette-like structures that provide an attractive description of genome organization into replication foci that are observed in interphase mammalian nuclei.

An Equivalent Markov Model for Gillespie's Stochastic Simulation Algorithm for biochemical systems

Ronit Bustin (Tel-Aviv University, Israel); Hagit Messer (Tel-Aviv University, Israel)

Mathematical/statistical modeling of biological systems is a desired goal for many years. It aims to be able to accurately predict the operation of such systems under various scenarios using computer simulations. In this paper we revisit Gillespie's Stochastic Simulation Algorithm for biochemical systems and we suggest an equivalent Markov Model for it. We show that under certain conditions it is a first order homogenous Markov process and we analyze these conditions. Our suggested model can be used to simulate the probability density function of a biochemical processes which, in turn, can be used for applying statistical signal processing and information theory tools on them.

Hypothesis Testing Over a Random Access Channel in Wireless Sensor Networks

Elvis Bottega (University of Padova, Italy); Petar Popovski (Aalborg University, Denmark); Michele Zorzi (Università degli Studi di Padova, Italy); Hiroyuki Yomo (CTIF, Aalborg University, Denmark); Ramjee Prasad (Aalborg University, Denmark)

In the design of the communication protocols for wireless sensor networks a specific requirement emerges from the fact that the data contained in an individual sensor is not important per se, but its significance is instantiated with respect to the contribution to the overall sensing task and the decision fusion. Therefore, the communication protocols should be application-aware and operate by reckoning the utility of the carried data. In this paper we consider the problem of hypothesis testing at the fusion center (sink) when all the sensors communicate with the sink via a random access channel. Each sensor contains a binary information 0 (event occurred) or 1 (event did not occur). In a traditional protocol design, an existing random--access protocol is used by which the sink collects the data from all sensors and subsequently makes the decision through majority voting over the received data. In this paper, we propose approaches for joint design of the communication and the decision fusion for the application of hypothesis testing. The fusion center terminates the data gathering through the random access channel as soon as it can make sufficiently reliable decision based on the data received so far. We describe two instances of the protocols, where the total number of sensors $N$ is known and not known, respectively. Our results show that the proposed approaches provide optimized performance in terms of time, energy and reliability.

Reducing Power Consumption in a Sensor Network by Information Feedback

Mikalai Kisialiou (University of Minnesota, USA); Zhi-Quan Luo (University of Minnesota, USA)

We study the role of information feedback for the problem of distributed signal tracking/estimation using a sensor network with a fusion center. Assuming that the fusion center has sufficient energy to reliably feed back its intermediate estimates, we show that the sensors can substantially reduce their power consumption by using the feedback information in a manner similar to the stochastic approximation scheme of Robbins-Monro. For the problem of tracking an autoregressive source or estimating an unknown parameter, we quantify the total achievable power saving (as compared to the distributed schemes with no feedback), and provide numerical simulations to confirm the theoretical analysis.

Clustering in Distributed Estimation with Dependent Observations

Sung-Hyun Son (Princeton University, USA); Sanjeev Kulkarni (Princeton University, USA); Stuart Schwartz (Princeton University, USA)

A wireless sensor network with dependent observations is considered to study the effects of clustering on the parameter estimation problem. The set of sensors is partitioned in such a way that the intracluster sensor observations are spatially correlated while the intercluster sensor observations are independent. The size of the cluster allows flexibility in selecting the magnitude of spatial correlation which ranges from one sensor per cluster, (i.e., independent observations), to all sensors in one cluster, (i.e. dependent observations). From an energy point of view, sending all the local data to the fusion center is the most costly, but leads to optimum performance results since all the dependencies are taken into account. From an estimation accuracy point of view, sending only parameter estimates and associated quality measures is the least accurate, but is the most parsimonious in terms of communication costs. Hence, this tradeoff between the cluster size and the estimation accuracy is explored. Various topologies and communication protocols are studied where both communication costs and estimation accuracy are optimized.

Analysis versus Synthesis in Signal Priors

Ron Rubinstein (Technion, Israel Institute of Technology, Israel); Michael Elad (Technion, Israel); Peyman Milanfar (University of California, Santa Cruz, Canada)

The concept of prior probability for signals plays a key role in the successful solution of many inverse problems. Much of the literature on this topic can be divided between analysis-based and synthesis-based priors. Analysis-based priors assign probability to a signal through various forward measurements of it, while synthesis-based priors seek a reconstruction of the signal as a combination of atom signals. In this paper we describe these two prior classes, focusing on the distinction between them. We show that although when reducing to the complete and under-complete formulations the two become equivalent, in their more interesting over-complete formulation the two types depart. Focusing on the L1 denoising case, we present several ways of comparing the two types of priors, establishing the existence of an unbridgeable gap between them.

Adaptive Bayesian/Total-Variation Image Deconvolution: A Majorization-Minimization Approach

José Bioucas-Dias (Instituto Superior Técnico, Portugal); Mario Figueiredo (Instituto Superior Técnico, Portugal); João Oliveira (Instituto Superior Técnico, Portugal)

This paper proposes a new algorithm for total variation (TV) image deconvolution under the assumptions of linear observations and additive white Gaussian noise. By adopting a Bayesian point of view, the regularization parameter, modeled with a Jeffreys' prior, is integrated out. Thus, the resulting crietrion adapts itself to the data and the critical issue of selecting the regularization parameter is sidestepped. To implement the resulting criterion, we propose a {\em majorization-minimization} approach, which consists in replacing a difficult optimization problem with a sequence of simpler ones. The computational complexity of the proposed algorithm is O(N) for finite support convolutional kernels. The results are competitive with recent state-of-the-art methods.

Hirarchical Markovian Models for 3D Computed Tomography in Non Destructive Testing Applications

Ali Mohammad-Djafari (Centre national de la recherche scientifique (CNRS), France); Lionel Robillard (EDF, France)

Computed Tomography (CT) has become an usual technic in Non Destructive Testing (NDT) applications, in particular in detection and characterization of defaults in metalic objects. One of the characteristics of such applications is that, in general the number and angles of of projections are very limited, but at the other hand, we know a priori the number of the kind of materials we can found, mainly metal and air or metal, air and a composite material. In this work, we first propose a particular hierarchical Markov-Potts a priori model which takes into account for the specificty of the NDT CT. Then, we give details of a Bayesian estimation computation based on MCMC and EM technics. Finally, we show the performances of the proposed 3D CT reconstruction method with a very limited number and angles of projections with very low signal to noise ratio simulating a real application of NDT in power plants industry.

Hierarchical Bayesian Super Resolution Reconstruction of Multispectral Images

Rafael Molina (Universidad de Granada, Spain); MIguel Vega (University of Granada, Spain); Javier Mateos (University of Granada, Spain); Aggelos K. Katsaggelos (Northwestern University, USA)

In this paper we present a super resolution Bayesian methodology for pansharpening of multispectral images which: a) incorporates prior knowledge on the expected characteristics of the multispectral images, b) uses the sensor characteristics to model the observation process of both panchromatic and multispectral images, c) includes information on the unknown parameters in the model, and d) allows for the estimation of both the parameters and the high resolution multispectral image. Using real data, the pansharpened multispectral images are compared with the images obtained by other parsharpening methods and their quality assessed both qualitatively and quantitatively.

Variational Bayesian Blind Image Deconvolution Based on a Sparse Kernel Model for the Point Spread Function

Dimitris Tzikas (University of Ioannina, Greece); Aristidis Likas (University of Ioannina, Greece); Nikolaos Galatsanos (University of Ioannina, Greece)

In this paper we propose a variational Bayesian algorithm for the blind image deconvolution problem. The unknown point spread function (PSF) is modeled as a sparse linear combination of kernel basis functions. This model offers an effective mechanism to estimate for the first time both the support and the shape of the PSF. Numerical experiments demonstrate the effectiveness of the proposed methodology.

Adaptive regularization of noisy linear inverse problems

Lars Kai Hansen (Technical University of Denmark, Denmark); Kristoffer Madsen (Tecnical University of Denmark, Denmark); Tue Lehn-Schioler (Technical University of Denmark, Denmark)

In the Bayesian modeling framework there is a close relation between regularization and the prior distribution over parameters. For prior distributions in the exponential family, we show that the optimal hyperparameter, i.e., the optimal strength of regularization, satisfies a simple relation: The expectation of the regularization function, takes the same value in the posterior and prior distribution. We present three examples: Two simulations and application in fMRI neuroimaging.

A Perceptual Bayesian Estimation Framework and its Application to Image Denoising

Javier Portilla (Universidad de Granada, Spain)

We present a generic Bayesian framework for signal estimation that incorporates into the cost function a perceptual metric. We apply this framework to image denoising, considering additive noise of known density. Under certain assumptions on the way local differences in visual responses add up into a global perceptual distance, we obtain analytical solutions that exhibit interesting theoretical properties. We demonstrate through simulations, using an {\em infomax} non-linear perceptual mapping of the input and a local Gaussian model, that in the absence of a prior the new solutions provide a significant improvement on the visual quality of the estimation. Furthermore, they also improve in Mean Square Error terms w.r.t. their non-perceptual counterparts.

 

Sub-carrier SNR Estimation at the Transmitter for Reduced Feedback OFDMA

Patrick Svedman (Royal Institute of Technology, Sweden); David Hammarwall (Royal Institute of Technology, Sweden); Bjorn Ottersten (Royal Institute of Technology, Sweden)

In multiuser OFDMA FDD systems with resource allocation based on the instantaneous channel quality of the users, the feedback overhead can be very large. In this paper, a method to significantly reduce this feedback is proposed. The idea is to let the users feed back the channel quality (the SNR in this paper) of only a sub-set of their strongest sub-carriers. The SNRs on the other sub-carriers are instead estimated from the fed back values. We derive the MMSE estimator of the SNR of a sub-carrier, which uses two fed back SNRs as input. As a comparison, we also study the performance of the LMMSE estimator as well as spline interpolation. Numerical results show that the LMMSE estimator tends to underestimate the SNR compared to the other two estimators, whereas the interpolation tends to overestimate the SNR. System simulations including adaptive modulation and packet losses indicate that the MMSE estimator is the best choice in practice.

Distributed Algorithms for Maximum Throughput in Wireless Networks

Yufang Xi (Yale University, USA); Edmund Yeh (Yale University, USA)

The Maximum Differential Backlog (MDB) control policy of Tassiulas and Ephremides has been shown to adaptively maximize the stable throughput of multi-hop wireless networks with random traffic arrivals and queueing. The practical implementation of the MDB policy in wireless networks with mutually interfering links, however, requires the development of distributed optimization algorithms. Within the context of CDMA-based multi-hop wireless networks, we develop a set of node-based scaled gradient projection power control algorithms which solves the MDB optimization problem in a distributed manner using low communication overhead. As these algorithms require time to converge to a neighborhood of the optimum, the implementation of the MDB policy must be done with delayed queue state information. For this, we show that the MDB policy with delayed queue state information remains throughput optimal.

Autonomous QoS Control for Wireless Mesh and Ad-hoc Networks - the Generalized Lagrangean Approach

Marcin Wiczanowski (Technical University of Berlin, Germany); Slawomir Stanczak (Fraunhofer German-Sino Lab for Mobile Comm., Germany); Holger Boche (Fraunhofer Institute for Telecommunications HHI, Germany)

We consider the combined problem of performance optimization and interference control in wireless mesh and ad-hoc networks. Relying on the specific construction of the generalized Lagrangean function we propose a simple primal-dual unconstrained iteration providing convergence to a (local) optimum under arbitrary performance objectives. We present a decentralized implementation of such routine in linear networks.

A framework for resource allocation in OFDM broadcast systems

Gerhard Wunder (Heinrich-Hertz-Institut, Germany); Thomas Michel (German-Sino Mobile Communications Institute (MCI), Germany); Chan Zhou (Mobile Communication Lab for Mobile Communications MCI, HHI, Germany)

In this paper we consider resource allocation for OFDM broadcast channels (BC) where we introduce several scheduling policies in an ideal information-theoretic context and analyze their performance in terms of throughput, stability and delay dependent on system parameters such as user numbers and channel parameters. We provide algorithms to solve the stated scheduling problems where we use Langrangian and duality theory. These solutions can be used as a general benchmark for specific approaches and they also provide some intuition for good suboptimal solutions. Additionally, all these strategies are compared to a practical setup tested in a complete simulation chain (physical and medium access layer) according to the 3GPP HSDPA specification.

On the interplay between scheduling, user distribution, CSI, and performance measures in cellular downlink

Eduard Jorswieck (Royal Institute of Technology (KTH), Sweden); Mats Bengtsson (Royal Institute of Technology, Sweden); Bjorn Ottersten (Royal Institute of Technology, Sweden)

The cross-layer design of future communication systems jointly optimizes multiple network layers with the goal of boosting the system wide performance. This trend brings together the physical and the medium access layers. For the joint optimization of these two lowest layers, it is necessary to understand and relate their terms and concepts. In this paper, we study the interplay between four terms, namely channel state information from link-level, scheduling and user distribution from system level, and different performance measures from both levels. The envisaged scenario is the cellular downlink transmission. The average sum rate describes the long-term performance from a system perspective. The optimal scheduling policy as well as the impact of the user distribution can be clearly characterized as a function of the channel state information (CSI). In contrast, the short-term system performance which is described by the outage sum rate, shows a varying behavior in terms of the optimal scheduling policy and as a function of the user distribution. The analysis is performed by employing Majorization theory for comparing different user distributions. Three different CSI scenarios, namely the uninformed base, the perfectly informed base, and the base with covariance knowledge are studied. Finally, the extension to two less well known performance measures, the maximum throughput and the delay-limited sum rate is addressed.

Cross-layer Solutions to Performance Problems in VoIP over WLANs

Federico Maguolo (University of Padova, Italy); Francesco De Pellegrini (Universita` di Padova, Italy); Andrea Zanella (University of Padova, Italy); Michele Zorzi (University of Padova, Italy)

The design of WLANs was meant to extend Ethernet LANs in the most transparent way, but no particular mechanism was deployed in order to support real-time applications natively. At present VoIP calls are becoming customary, and IEEE802.11 WLANs must face the provision of guaranteed quality of service. In practice, QoS should be provided somehow a posteriori on top of the existing standard. In this paper, we address some concerns on the efficiency of WLANs for VoIP provision already remarked in literature and analyze possible solutions to increase the voice capacity of DCF IEEE802.11 WLANs. We consider two candidate solutions, the VA [1] and the M-M [2] cross-layer schemes. The efficiency of such mechanisms is evaluated in order to assess the performance gain compared to existing solutions. We provide extensive simulation results, proving that the advantage is signifcant, while requiring minor changes compared to the current IEEE802.11 standard.

Coordination and resilience in wireless adhoc and sensor networks

Leandros Tassiulas (University of Thessaly, Greece)

A review of radio channel sounding techniques

David Laurenson (The University of Edinburgh, United Kingdom); Peter Grant (Edinburgh School of Engineering and Electronics, United Kingdom)

This short paper will introduce the key approaches that have been adopted for channel sounding and describe systems that have been reported to date for measuring indoor and outdoor radio channels in the 1-5 GHz range of operating frequencies.

Performance Verification of MIMO Concepts using Multi-Dimensional Channel Sounding

Christian Schneider (Technische Universität Ilmenau, Germany); Uwe Trautwein (TeWiSoft, Germany); Reiner Thomae (University of Ilmenau, Germany); Walter Wirnitzer (MEDAV GmbH, Germany)

The advances in multi-dimensional channel-sounding techniques make it possible to evaluate performances of radio multiple access and signal processing schemes under realistic propagation conditions. This paper focuses on the methodology how recorded impulse response data gathered through multidimensional channel sounding field measurements can be used to evaluate link- and system-level performances of the multiple-input multiple-output (MIMO) radio access schemes. The method relies on offline simulations. It can be classified in between the performance evaluation using some predefined channel models and the evaluation in field experiments using a set of prototype hardware. New aspects for the simulation setup are discussed, which are frequently ignored when using simpler model-based evaluations. Example simulations are provided for an iterative ("turbo") MIMO equalizer concept. The dependency of the achievable bit error rate performance on the spatial-temporal propagation characteristics and on the variation in some system design parameters is shown. Although in many of the considered constellations turbo MIMO equalization appears feasible in real field scenarios, there exist cases with poor performance as well, indicating that in practical applications link adaptation of the transmitter and receiver processing to the environment is necessary.

Characterization of MIMO Channels for Handheld Devices in Personal Area Networks at 5 GHz

Johan Karedal (Lund Univ., Sweden); Anders Johansson (Lund University, Sweden); Fredrik Tufvesson (Lund University, Sweden); Andreas Molisch (Mitsubishi Electric Research Laboratory, USA)

In this paper we analyze the properties of MIMO channels for personal area networks (PANs). Such channels differ from propagation channels in wide-area networks due to several reasons: (i) the environments in which the systems operate are different, (ii) the mobility models and ranges are different, (iii) the influence from human presence in the environment is different. In this paper, we present results from a measurement campaign for PAN channels between two handheld devices. The measurements are conducted over distances of 1-10 m using two handheld four-element antenna devices. For each distance, a number of channel realizations are obtained by moving the devices over a small area, and by rotating the persons holding the devices. We find that the correlation between the antenna elements is low. The small-scale statistics of the amplitude are well described by the Rayleigh distribution in many cases, but the effects of shadowing by the body of the operator can lead to different statistics.

A Simple Approach to MIMO Channel Modelling

Rafal Zubala (Warsaw University of Technology, Poland); Hubert Kokoszkiewicz (Warsaw University of Technology, Poland); Martijn Kuipers (IT / IST-TUL, Portugal); Luis Correia (IST - Tech. Univ. Lisbon, Portugal)

A semi-statistical MIMO radio channel model is described, adequate for analysing multi-user environments, by simulating the channels between different users at the radio propagation level. The model is capable of simulating MIMO links between users, by allowing multiple antennas at mobile terminals and/or base stations. Results are shown for the influence of antenna spacing on MIMO capacity gain. For pico- and micro-cells, an increase in the number of antennas has a larger impact on capacity gain compared to macro-cells. Using the Geometrically Based Single Bounce Channel Model for micro-cell scenarios, a 20% variation in performance is obtained, depending on the orientation of antennas of both transmitter and receiver. For the macro-cell, a similar variation is seen, but only for the orientation of base station antennas.

Enhanced Tracking of Radio Propagation Path Parameters Using State-Space Modeling

Jussi Salmi (Helsinki University of Technology, Finland); Andreas Richter (Helsinki University of Technology, Finland); Visa Koivunen (Helsinki University of Technology, Finland)

Future wireless communication systems will exploit the rich spatial and temporal diversity of the radio propagation environment. This requires new complex channel models, which need to be verified by real-world channel sounding measurements. In this context the reliable estimation and tracking of the model parameters from measurement data is of particular interest. In this paper, we build a state-space model, and track the propagation parameters with the Extended Kalman Filter in order to capture the dynamics of the channel parameters in time. We then extend the model by considering first order derivatives of the geometrical parameters, which enhances the tracking performance due to improved prediction and robustness against shadowing and fading. The model also includes the effect of distributed diffuse scattering in radio channels. The issue of varying state variable dimension, i.e., the number of propagation paths to track, is also addressed. The performance of the proposed algorithms is demonstrated using both simulated and measured data.

Modelling and Manipulation of Polarimetric Antenna Beam Patterns via Spherical Harmonics

Giovanni Del Galdo (Ilmenau University of Technology, Germany); Jörg Lotze (Ilmenau University of Technology, Germany); Markus Landmann (Ilmenau University of Technology, Germany); Martin Haardt (Ilmenau University of Technology, Germany)

Measured antenna responses, namely their beam patterns with respect to the vertical and horizontal polarizations, play a major role in realistic wireless channel modeling as well as in parameter estimation techniques. The representations commonly used suffer from drawbacks introduced by the spherical coordinate system which is affected by two knots at the poles. In general, all methods which describe the beam pattern with a matrix fail in correctly reproducing its inherent spherical symmetry. In this contribution we propose the use of the Spherical Fourier Transformation (SFT) which allows the description of the beam pattern via spherical harmonics. This mathematical tool, well known in other fields of science, is rather new to wireless communications. The main applications of the SFT include the efficient description of a beam pattern, noise filtering, the precise interpolation in the spherical Fourier domain, and the possibility to obtain an equivalent description of the beam pattern for an arbitrary coordinate system. The latter allows us to improve an existing 2-D FFT based technique: the Effective Aperture Distribution Function (EADF).

Distributed UWB MIMO Sounding for Evaluation of Cooperative Localization Principles in Sensor Networks

Rudolf Zetik (Technical University Ilmenau, Germany); Jürgen Sachs (TU Ilmenau, Germany); Reiner Thomä (TU-Illmenau, Germany)

We describe architecture, design, and a novel application of a real-time MIMO UWB channel sounder. The sounder is applied for evaluating of localization principles in distrib-uted sensor networks that are based on UWB radio technol-ogy. We assume an application scenario without any sup-porting infrastructure as it may occur in emergency situa-tions such as fire disasters, earthquakes or terror attacks. At first we discuss the deployment scenario and signal process-ing principles applied for cooperative sensor node localiza-tion and imaging of the propagation environment. Then, we describe the architecture of the UWB MIMO channel sounder. Finally, a measurement example is demonstrated

System-level performance evaluation of MMSE MIMO turbo equalization techniques using measurement data

Mariella Särestöniemi (University of Oulu, Finland); Tadashi Matsumoto (CWC - Oulu, Finland); Christian Schneider (Technische Universität Ilmenau, Germany); Reiner Thomä (TU-Illmenau, Germany)

In this paper, system-level performance of MMSE turbo MIMO equalization techniques is evaluated in realistic scenarios. Soft cancellation and minimum mean squared error filtering (SC/MMSE) turbo equalization and its complexity reduced version, turbo equalized diversity, is considered. Furthermore, another version of equalized diversity, turbo equalized diversity with common SC/MMSE, which exploits the transmit diversity and coding gain through the cross-wise iterations over the decoding branches, is evaluated. The multi-dimensional channel sounding measurement data used for the simulations consists of snapshots measured in different channel conditions in terms of spatial and temporal properties. The system-level assessment is in terms of outage probabilities of the performance figures such as bit and frame error rates obtained by evaluating their cumulative probability densities using the field measurement data. It is found that the receivers considered in this paper can all provide reasonable system-level performance. However, turbo equalized diversity receiver is slightly more sensitive to the channel conditions than the original SC/MMSE equalizer. It is also found that the performance gain obtained from the cross-wise iteration over the decoding branches in the turbo equalized diversity with common SC/MMSE technique is significant.

Widely Linear MMSE Transceiver for Real-Valued Sequences over MIMO Channel

Davide Mattera (Università degli Studi di Napoli Federico II, Italy); Luigi Paura (Università di Napoli Federico II, Italy); Fabio Sterle (University of Naples Federico II, Italy)

Joint design of the precoder and the decoder (say, transceiver) for multiple-input/multiple-output (MIMO) channels is considered and, in particular, the already existing procedure for the design of the linear transceiver according to the minimum-mean-square-error (MMSE) criterion is extended to the more general case where the transceiver resorts to widely linear (WL) processing rather than linear one. WL filters linearly and independently process both the real and the imaginary parts of the input signals, and they are usually employed in order to trade-off a limited increase in the computational complexity with performance gains when the input signals are circularly variant. For this reason, we propose to resort to WL processing in the synthesis of the MIMO transceiver when real-valued data streams have to be transmitted. The performance analysis shows significant performance advantages of the proposed WL-MMSE MIMO transceiver with respect to the linear one.

Linear receiver interfaces for multiuser MIMO communications

Alessandro Nordio (Politecnico di Torino, Italy); Giorgio Taricco (Politecnico di Torino, Italy)

We consider the uplink of a DS-CDMA wireless communication system with multiple users equipped with several transmit antennas. We assume that a multiple-antenna subsystem is added to an existing multiuser detector and we compare the performance of this receiver and that of an optimum receiver accounting for both spatial and multiple-access interference simultaneously. In the former case we say that the receiver is separate whereas in the latter we say that the receiver is joint. Several classes of separate and joint linear receivers are considered and their performance is evaluated asymptotically and by simulation.

Multiuser detection using random-set theory

Ezio Biglieri (Universitat Pompeu Fabra, Barcelona, Spain); Marco Lops (University of Cassino, Italy)

In mobile multiple-access communications, not only the location of active users, but also their number varies with time. In typical analyses, multiuser detection theory is developed under the assumption that the number of active users is constant and known at the receiver, and coincides with the maximum number of users entitled to access the system. This assumption is often overly pessimistic, since many users might be inactive at any given time, and detection under the assumption of a number of users larger than the real one may impair performance. This paper undertakes a different, more general approach to the problem of identifying active users and estimating their parameters and data in a dynamic environment where users are continuously entering and leaving the system. Using a mathematical tool known as Random Set Theory, we derive Bayesian-filter equations which describe the evolution with time of the a posteriori probability density of the unknown user parameters, and use this density to derive optimum detectors.

Subcarrier Allocation in a Multiuser MIMO Channel Using Linear Programming

Ari Hottinen (Nokia Research Center, Finland); Tiina Heikkinen (MTT Economic Research, Finland)

In this paper, we apply specialized linear programming algorithms in assigning users to orthogonal frequency channels or subcarriers in a channel-aware MIMO-OFDMA system. Efficient optimization techniques enable total utility (e.g. downlink capacity) maximization in polynomial time in the presence of strict fairness constraints.

Efficient Vector Perturbation in Multi-Antenna Multi-User Systems Based on Approximate Integer Relations

Dominik Seethaler (Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology, Austria); Gerald Matz (Vienna University of Technology, Austria)

Approximate vector perturbation techniques assisted by LLL lattice reduction (LR) can exploit all the diversity that is available in multi-user multi-antenna broadcast systems. However, the required computational complexity of LLL-LR can be quite large. In this paper, we propose a much simpler and much more efficient LR algorithm than LLL. This LR technique is based on Brun's algorithm for finding approximate integer relations (IRs). The link between LR and IRs is established by considering poorly conditioned channels with a single small singular value. Simulation results show that our scheme can achieve large (but bot full) diversity at a fraction of the complexity required for LLL-assisted vector perturbation.

Iterative Transceiver Optimization for Linear Multiuser MIMO Channels with MMSE Requirements

Martin Schubert (Fraunhofer German-Sino Lab for Mobile Communications MCI, Germany); Shuying Shi (Fraunhofer German-Sino Lab for Mobile Communications MCI, Germany); Holger Boche (Fraunhofer Institute for Telecommunications HHI, Germany)

We address the problem of jointly optimizing linear transmit and receive filters for a multi-user MIMO system, under the assumption that all users have individual Minimum- Mean-Square-Error (MMSE) requirements. Each user can perform spatial multiplexing with several data streams (layers). All users and layers are coupled by interference, so the choice of filters is intricately interwoven with the power allocation strategy. Design goal is power minimization under MMSE constraints. This results in non-convex problem formulations, for which we propose computationally-efficient iterative algorithms. The iteration consists of alternating optimization of powers, transmit filters and receive filters. We prove that the total required power obtained by the algorithm is monotonically decreasing and converges to a limit.

Transmit Correlation-Aided Opportunistic Beamforming and Scheduling

Marios Kountouris (France Telecom R&D, France); David Gesbert (Eurecom Institute, France); Lars Pittman (Norwegian Univ. of Science & Technology, Norway)

The problem of joint opportunistic scheduling and beamforming for multiuser systems exploiting partial channel state information at the transmitter (CSIT) is addressed here. We show that useful information relevant to the scheduler lies untapped in the long-term statistical information of users' channels, which is easily acquired either by uplink/downlink reciprocity of the second-order statistics or via very low rate feedback. We show how statistical channel knowledge can be efficiently combined with instantaneous-but-partial CSIT to derive a channel estimate for the downlink of multiuser correlated MIMO systems. This estimate can in turn be exploited for user selection as well as for the design of the multiuser beamforming matrix. Performance evaluation shows the capacity gain of this type of approach over conventional opportunistic schemes in various settings.

A reduced complexity MIMO Broadcast scheme: a way between opportunistic and dirty paper implementation

Nizar Zorba (Telecommunications Technological Center of Catalonia (CTTC), Spain); Ana I. Perez-Neira (Universitat Politecnica de Catalunya, Spain); Miguel Angel Lagunas (Telecommunications Technological Center of Catalonia, Spain)

Departing from the opportunistic schemes in Multiuser Broadcast MIMO schedulers, practical transmission techniques to get closer to the channel capacity are proposed for the outdoor urban scenario. By considering the Spatial Power Density function of the arriving signal, the paper develops different setups based on the quantity of available Channel State Information at the transmitter side (CSIT). In a first approach, Signal to Noise Interference Ratio (SNIR) feedback scenario is considered, but to further decrease the gap between the channel capacity and the proposed scheme, the paper suggests that only the selected users are asked to provide their full CSIT to the transmitter side. The goal is to always keep a small load on the feedback link while at the same time providing almost all of the benefits of full CSIT scenarios. The proposed schemes are compared via simulations with other possible transmission strategies in terms of system sum rate.

Transmit and Receive Antenna Subset Selection for MIMO SC-FDE in Frequency Selective Channels

Andreas Wilzeck (University Duisburg-Essen, Germany); Patrick Pan (University Duisburg-Essen, Germany); Thomas Kaiser (University of Duisburg-Essen, Germany)

Antenna (subset) selection is a feasible scheme to reduce the hardware complexity of Multiple-Input Multiple-Output (MIMO) systems. Studies of antenna selection schemes are typically based on channel capacity optimizations employing frequency flat channel models, which are inconsistent with MIMO systems employing spatial-multiplexing. Such systems aim to offer a high data-rate transmission, so that the channel is of frequency selective nature. In this contribution we study antenna subset selection at transmitter- and receiver-side for theMIMO Single Carrier (SC) scheme with Frequency Domain Equalization (FDE) in frequency selective channels. As alternative selection metric the signal quality of the MIMO equalizer output is used.

Non-Linear Precoding for MIMO Multi-User Downlink Transmissions with different QoS requirements

Luca Sanguinetti (University of Pisa, Italy); Michele Morelli (University of Pisa, Italy)

An efficient non-linear pre-filtering technique based on Tomlinson-Harashima pre-coding (THP) has recently been proposed by Liu and Krzymien for multiple antenna multiuser systems. The algorithm is based on the Zero-Forcing (ZF) criterion and assumes a number of transmit antennas equals to the number of active users. In contrast to other methods, it ensures a fair treatment of the active users providing them the same signal-to-noise ratio. In multimedia applications, however, several types of information with different quality-of-service (QoS) must be supported. Motivated by the above problem, in the present work we design a ZF THP-based pre-filtering algorithm for multiple antenna multi-user networks in which the base station allocates the transmit power according to the QoS requirement of each active user. In doing so, we consider a system in which the number of active users may be less than the number of transmit antennas. As we will see, in such a case there exists an infinite number of solutions satisfying the ZF criterion. We address the problem of finding the best using as optimality criterion the maximization of the signal-to-noise ratios at all mobile terminals.

Levenberg-Marquardt Computation of the Block Factor Model for Blind Multi-user Access in Wireless Communications

Dimitri Nion (ETIS, UMR 8051 (CNRS, ENSEA, UCP), France); Lieven de LATHAUWER de LATHAUWER (E.E. Dept. (ESAT) - SCD-SISTA, Belgium)

In this paper, we present a technique for the blind separation of DS-CDMA signals received on an antenna array, for a multi-path propagation scenario with Inter-Symbol-Interference. Our method relies on a new third-order tensor decomposition, which is a generalization of the parallel factor model. We start with the observation that the temporal, spatial and spectral diversities give a third-order tensor structure to the received data. This tensor is then decomposed in a sum of contributions, where each contribution fully characterizes one user. We also present an algorithm of the Levenberg-Marquardt type for the calculation of this decomposition. This method is faster than the alternating least squares algorithm previously used.

A Selective Beamforming Strategy for Multi-User MIMO Communications

Mirette Sadek (University of California, Los Angeles, USA); Alireza Tarighat (University of California. Los Angeles (UCLA), USA); Ali Sayed (University of California, Los Angeles, USA)

The paper develops a dynamic antenna scheduling strategy for downlink MIMO communications, where the transmitted signal for each user is beamformed towards a selected subset of receive antennas at this user. It is shown in this paper both analytically and through simulations that increasing the number of antennas at one user degrades the SINR performance of other users in the network. This fact is then exploited to improve the systems performance in terms of target SINR outage probability for each user. Using the SINR outage criterion, allows us to lower the number of targeted antennas at a particular user if the user is already meeting its target SINR. By doing so, other users in the network originally below their target SINR can achieve their target SINR as well. In other words, the antenna scheduling schemes aims at maximizing the number of users meeting their target SINR values by dynamically changing the active antenna sub-sets for every user.

Linear Detectors for multi-user MIMO systems with correlated spatial diversity

Laura Cottatellucci (ftw.-Forschungszentrum Telekommunikation Wien, Austria); Ralf Mueller (Norwegian University of Science and Technology, Norway); Merouane Debbah (Institut Eurecom, France)

A multiuser CDMA systems with both the transmitting and the receiving sites equipped with multiple antenna elements is considered. The multiuser MIMO channel is correlated at the transmitting and the receiving sites. Multistage detectors achieving near-linear MMSE performance with a complexity order per bit linear in the number of users are proposed. The large system performance is analyzed in a general framework including any multiuser detector that admits a multistage representation. The performance of this large class of detectors is independent of the channel correlation at the transmitter. It depends on the direction of the channel gain vector of the user of interest if the channel gains are correlated.

Design of robust linear dispersion codes based on imperfect CSI for ML receivers

Svante Bergman (KTH, Sweden); Bjorn Ottersten (Royal Institute of Technology, Sweden)

This paper concern the design of codes for multi-input multi-output communication systems. The transmission scheme utilize imperfect channel state information (CSI) in the design, assuming maximum-likelihood detection is employed at the receiver. It is argued that channel diagonalizing codes are not robust to imperfections in the CSI. A robust non-diagonalizing code with good minimum distance separation between received codewords is proposed. The code is very suitable for systems with high data rates due to its low design complexity. Numerical results show that the proposed code outperforms a state of the art diagonalizing precoder.

MIMO-ISI Channel equalization -- Which Prize We Have to Pay for Causality

Holger Boche (Heinrich-Hertz-Institut für Nachrichtentechnik Berlin GmbH, Germany); Volker Pohl (Technical University Berlin, Germany)

In the investigation of equalizers and precoders for multiple-input multiple-output systems with intersymbol interference, completely new phenomena appear if the causality of theses filters is required. Both, the noise enhancement and the robustness of the equalizing filter are important criteria which influence the performance of the filter. It is shown that under the causality constrain, the optimal filters with respect to both criteria does not coincide such that a certain trade-off between both performance measures has to be found. For precoders, the effective receive power reduction is the most important performance criteria. It is shown that the robustness of the inverses and the effective receive power decreases exponential with the number of transmit and receive antennas of the MIMO system.

Switching effects of a virtual rotating MIMO antenna

Robert Bains (Norwegian Univ. of Science and Technology, Norway); Ralf Mueller (Norwegian University of Science and Technology, Norway)

In a previous paper a concept of compact MIMO-receiver was proposed consisting of a single active receiver antenna and multiple parasitic elements placed on a circle around the antenna. The advantage of this MIMO-receiver is that the parasitic elements can be placed much closer to the active receiver antenna than half the carrier wavelength. The results in the previous paper was mainly based on the concept of a continuously rotating antenna, and didn't go into the details of the effects created when the antenna rotates 360 degrees with discrete steps. In another paper by the same authors the effects of a discrete rotation were studied based on theoretical grounds. This paper will study the effect of the discrete rotation and the switching effects based on electromagnetic simulations.

Multi-user Topologies in Multi-Antenna Wireless Networks

Christian Peel (Brigham Young University, USA); Lee Swindlehurst (Brigham Young University, USA); Wolfgang Utschick (Munich University of Technology, Germany)

Recent results on the throughput achievable with wireless networks have not fully considered multiple antennas and multi-user links. We introduce these topics by deriving the transport capacity of a multiple-access channel with CSI available only at the receiver. We also give the transport capacity of the multiple-access and broadcast channels with full CSI. We use these topologies at the physical layer of an ad-hoc network to obtain achievable distance-weighted rate regions for a multi-antenna wireless network. These regions are obtained by maximizing the distance-weighted rate over all combinations of uplink and downlink topologies, respectively. A Nash-equilibrium-seeking algorithm is used to optimize the transmit covariance matrices for the centralized topology search. Distributed algorithms for topology creation are also presented which utilize only local channel state information and compared with multi-user versions of slotted ALOHA. Numerical examples show the benefit of uplink topologies over point-to-point and downlink topologies, especially at high transmit power, high numbers of antennas, and a large number of nodes.

Randomized distributed Multi-antenna Systems in Multi-path channels

Anna Scaglione (Cornell University, USA); Birsen Sirkeci (Cornell University, USA); Stefan Geirhofer (Cornell University, USA); Lang Tong (Cornell University, USA)

A great deal of research on MIMO systems is now trying to focus on distributed designs to bring the advantages of co-located antenna systems to nodes with a single RF front end, by leveraging on the other nodes resources. Yet, most schemes that are considered assume that the nodes encode their signals in a fashion that requires at least the knowledge of the number of nodes involved and in many cases the specific encoding rule to use. Hence, while the hardware resources are distributed, the protocols that are proposed are not. Recently we have proposed schemes that are totally decentralized and using random matrix theory we have studied the diversity attainable through these schemes in flat fading channels. The goal of this paper is to show that our general randomized designs are suitable to work in frequency selective channels and can easily be adapted to block space-time precoding schemes that are known to harvest diversity not only from the multiple antennas but also from the multi-path.

An Efficient Feedback Scheme with Adaptive Bit Allocation for Dispersive MISO Systems

Leonid Krasny (Ericsson Inc., USA); Dennis Hui (Ericsson Inc., USA)

In this paper, we focus on a cellular system with M transmit antennas at the base station (BTS) and one receive antenna at the mobile (i.e. an M-input/single-output (MISO) channel), where the BTS commands each mobile to transmit its channel state information back to the BTS. Our main result is a specific feedback scheme with adaptive bit allocation, where a binary tree-structured vector quantizer is used to separately quantize different channel taps at different level of quantization. We show that proposed feedback scheme allows to exploit the different statistics of the channel taps and results in a performance very close (within 1dB) to the performance that can be obtained with perfect channel knowledge at the BTS.

Generalized Receiver-Enhanced Cooperative Spatial Multiplexing

Hilde Skjevling (University of Oslo, Norway); David Gesbert (Eurecom Institute, France); Are Hjørungnes (Unversity of Oslo, Norway)

This paper explores the idea of cooperative spatial multiplexing for use in MIMO multi-cell networks. We imagine applying this cooperation for several multiple antenna access-points to jointly transmit streams towards multiple user terminals, with arbitrary number of base station and user terminal antennas. We make the setting more realistic by introducing a constraint on the {\em hybrid channel state information} (HCSI), assuming that each transmitter has full CSI for its own channel, but only {\em statistical} information about other transmitters' channels. Each cooperating transmitter then makes guesses about the behaviour of the other transmitters, using the available statistical CSI. We show two of several possible transmission strategies under this setting, and include simple optimization at the receiver to improve performance. Comparisons are made with fully cooperative (full CSI) and non-cooperative schemes. Simulation results show a substantial cooperation gain despite the lack of instantaneous information.

Robust transmitter design in MISO multiuser broadcast systems

Ami Wiesel (Technion-Israel Institute of Technology, Israel)

We consider the problem of transmitter design in multiuser broadcast systems under channel uncertainty. In particular, we are interested in broadcast systems in which the transmitter has multiple antennas, and each user has a single receive antenna. We assume that there are strict quality of service constraints on the data rates of each of the users and try to minimize the average transmitted power while maintaining these rates. This problem was recently solved assuming perfect channel knowledge at the transmitter, but is still an open question when only partial channel state information (CSI) is available.

On MIMO Transmission Techniques for Multiuser Communications

Wolfgang Utschick (Munich University of Technology, Germany)

A communication scenario with multiple cooperating transmitters, which can perform a joint pre-processing of the signals to be transmitted, and multiple decentralized receivers, which can only process the received signals inde-pendently, is referred to as (MIMO) Broadcast Channel. We consider receivers with a vector receive signal, e.g., from multiple antenna elements. The Broadcast Channel scenario occurs in wireline as well as in wireless communi-cations (communication from access point to multiple mobile terminals), which is considered here. In this work we will critically review different optimality criteria and algorithms for the design of MIMO transmission techniques under the view of the amount of required channel state information (CSI), computational complexity and performan-ce quality.

System Level Design Considerations for HSUPA User Equipment

Moritz Harteneck (Aeroflex Inc, United Kingdom)

Within Release 6 of the 3GPP standards, one of the most important features is High Speed Uplink Packet Access (HSUPA) or enhanced DCH (E-DCH), which is the uplink counterpart for High Speed Downlink Packet Access (HSDPA). Most notable improvements, when compared to the R99 specification, are the achievable peak data rate of 5.76 Mbps, reduced latency due to a shortened transmission time interval and increased uplink cell throughput. This has been achieved by the use of multi-code transmission on the uplink, together with an improved forward error correction scheme including the use of hybrid automatic repeat request operating between the UE and the nodeB and a tighter (nodeB based) control of the uplink resources. In this paper, system level design considerations are de-rived which point out the design problems one faces when designing a HSUPA compliant UE. First, the HSUPA system is explained, then the receiver is analysed in more detail and finally, considerations for the RF transmitter block are shown.

IEEE 802.11n MIMO-Prototyping with Dirty RF Using the Hardware-in-the-Loop Approach

Matthias Stege (Signalion GmbH, Germany); Tim Hentschel (Signalion GmbH, Germany); Michael Löhning (Signalion GmbH, Germany); Gerhard Fettweis (Technische Universitaet Dresden, Germany); Marcus Windisch (Technische Universität Dresden, Germany)

Modern wireless systems employ highly integrated hardware. Especially for the processing at radio frequencies this high integration causes many undesired effects of signal distortion and degradation that must be simulated comprehensively before finalizing the system design. However, often the model accuracy is not sufficient to obtain sound results of the simulations; and in the case of sufficiently accurate models the simulation times get immense. A way out is to use real radio frequency hardware and digital physical layer simulations together in a hardware-in-the-loop system. Short simulation times and real-world radio characteristics are the unbeatable advantage of the hardware-in-the-loop approach.

Real-Time Implementation of a Sphere Decoder-Based MIMO Wireless System

Mikel Mendicute (University of Mondragon, Spain); Luis Barbero (University of Edinburgh, United Kingdom); Gorka Landaburu (University of Mondragon, Spain); John. S Thompson (University of Edinburgh, United Kingdom); Jon Altuna (University of Mondragon, Spain); Vicente Atxa (University of Mondragon, Spain)

This contribution analyzes the integration of the sphere decoder (SD) in a complete field-programmable gate array (FPGA)-based real-time multiple input-multiple output (MIMO) platform. The algorithm achieves the performance of the maximum likelihood detector (MLD) with reduced complexity. However, its non-deterministic complexity, depending on the noise level and the channel conditions, hinders its integration process. This paper evaluates the performance and limitations of the SD in a real-time environment where signal impairments, such as symbol timing, imperfect channel estimation or quantization effects are considered.

Real-Time Experiments on Channel Adaptive Transmission in the Multi-User Up-link at very high Data Rates using MIMO-OFDM

Thomas Haustein (Heinrich Hertz Institut Berlin, Germany); Andreas Forck (HHI, Germany); Holger Gäbler (FhG-HHI, Germany); Volker Jungnickel (Fraunhofer Institut für Nachrichtentechnik (Heinrich-Hertz-Institut) Berlin, Germany); Stefan Schiffermueller (FhG-HHI, Germany)

In this paper we focus on channel adaptive transmission in the multi-user OFDM uplink where the base station uses multiple antennas. The additional degree of freedom in space requires extra signal processing effort which becomes challenging especially for a high data rate implementation in real-time. Our MIMO-OFDM experimental system which is capable to transmit data rates beyond 1~Gbit/s, was enhanced by adaptive resource allocation, where the modulation on each antenna and each sub-carrier was controlled by a narrow-band feed-back channel. We present experimental results for the total rate achieved at the base station and the individual rates per user terminal in line-of-sight and non-line-of-sight scenarios. We compare the rates expected from theory on the measured indoor channels with rates achieved in the experiments.

An 8x8 RLS based MIMO detection ASIC for broadband MIMO-OFDM wireless transmissions

Jingming Wang (Marvell Semiconductor, USA); Babak Daneshrad (University of California, Los Angeles, USA)

This paper presents the architecture and VLSI implementation of a highly flexible MIMO detection engine which supports a wide array of configurations ranging from 1x1 to 8x8 square, as well as all possible non-symmetric MIMO configurations. The chip is specifically designed to work with an underlying OFDM modulation scheme, and can cover the range of 64 to 1024 subchannels. The chip implements an RLS based MIMO solution which provides a good balance between hardware complexity and overall system performance. To further reduce the complexity, frequency domain linear interpolation is also used. The actual implementation is based upon the highly scalable inverse QR decomposition based systolic array architecture. A single systolic array is time-multiplexed for all OFDM subchannels. This naturally overcomes the pipelining difficulty in traditional single channel systolic arrays without doubling the array size. In conjunction with the array design, a unique input tagging scheme is incorporated to allow dynamic reconfiguration of the ASIC on a per packet basis, and also to reduce power consumption when only a sub-array is needed for the operation. The final implementation of the MIMO detection engine supports up to an 8x8 configuration in 12.5 MHz of bandwidth. A 4x4 or any smaller array can also be supported at up to 25 MHz of bandwidth. The chip was fabricated using a 3.3V/1.8V 0.18um CMOS technology. The resulting core layout measures 29.2mm^2 and clocks at a maximum clock frequency of 58MHz. The power consumption of the chip in a 2x2-25 MHz configuration is 360 mW, whereas the 12.5 MHz 8x8 mode consumes 830mW.

Design of WARP: A Wireless Open-Access Research Platform

Patrick Murphy (Rice University, USA); Ashutosh Sabharwal (Rice University, USA); Behnaam Aazhang (Rice University, USA)

This paper presents the design of WARP, a custom platform for research in advanced wireless algorithms and applications. The platform consists of both custom hardware and FPGA implementations of key communications blocks. The hardware consists of FPGA-based processing boards coupled to wideband radios and other I/O interfaces; the algorithm implementations already include a flexible OFDM physical layer. Both the hardware design and algorithm implementations will be freely available to academic researchers to enable the development of a widely disseminated, highly capable platform for wireless research.

High-throughput multi-rate LDPC decoder based on architecture-oriented parity check matrices

Predrag Radosavljevic (Rice University, USA); Alexandre de Baynast (Rice University, USA); Marjan Karkooti (Rice University, USA); Joseph Cavallaro (Rice University, USA)

High throughput pipelined LDPC decoder that supports multiple code rates and codeword sizes is proposed. In order to increase memory throughput, irregular block structured parity-check matrices are designed with the constraint of equally distributed odd and even nonzero block-columns in each horizontal layer for pre-determined set of code rates. Designed decoder achieves data throughput of approximately 1 Gb/s without sacrificing error-correcting performance of capacity-approaching irregular block codes. The prototype architecture is implemented on FPGA.

Fast Prototyping of Digital Signal Processing Systems by Means of a Mopdel-based Codesign Environment

Leonardo Reyneri (Politecnico di Torino, Italy); Fabio Ancona (Sundance Italia s.r.l., Italy)

This paper presents a novel tool, based on Simulink, for model-based high-level HW/SW codesign of high-performance digital signal processing systems. The tool has been tailored to support HW/SW configurable platforms, in particular those from Sundance Microprocessor Technology

MIMO Signal Processing on a reconfigurable architecture

Klaus Hueske (University of Dortmund, Germany); Juergen Goetze (University of Dortmund, Germany)

In this paper the implementation of multiple-input multiple-output (MIMO) signal processing on a reconfigurable hardware architecture is discussed. The implementation of MIMO systems is usually determined by the parameters of the application at hand, e.g. the number of input signals, number of output signals, number of users or word length. Furthermore, there is also a flexibility in terms of the algorithms, which are used for computing the required task. We will present the implementation of the linearly constrained MVDR beamformer on a reconfigurable hardware architecture. A virtual parallel implementation of the used algorithms is mapped to a reconfigurable hardware architecture, where the used processor elements can execute different modes (configuration modes). We will discuss the configuration in terms of change of parameters and change of algorithm, respectively. Furthermore, bit true simulations of the BER for different configurations are presented for various word lengths. Finally, the trade-off between performance and reconfiguration effort is discussed.

VLSI Implementation of Pipelined Sphere Decoding with Early Termination

Andreas Burg (ETHZ, Switzerland); Markus Wenk (IIS/ETH-Zurich, Switzerland); Wolfgang Fichtner (ETHZ, Switzerland)

The sphere decoding algorithm allows to implement MIMO detection with maximum likelihood error rate performance while complexity is far below an exhaustive search. This paper addresses two important problems associated with the practical implementation of sphere decoding: the mitigation of the bit error rate performance loss when the runtime of the decoder is constrained and the introduction of pipelining into the recursive depth-first sphere decoding algorithm. The result of this work is a sphere decoder implementation for a 4x4 system with 16-QAM modulation in a 0.13 um technology that achieves a guaranteed minimum throughput of 761 Mbps.

Controlling particle filter regularization for GPS/INS hybridization

Audrey Giremus (university of Toulouse, France); Jean-Yves TOURNERET (IRIT/ENSEEIHT/TéSA, France)

Coupling GPS with Inertial Navigation Systems (INS) is an interesting way of improving navigation performance in terms of accuracy and continuity of service. This coupling is generally performed by using GPS pseudorange measurements to estimate INS estimation errors and sensor biases. Particle filtering techniques are good candidates to solve the corresponding estimation problem due to the nonlinear measurement equation. However, classical particle filter algorithms tends to degenerate for this application because of the small state noise. Regularized particle filters allow to overcome this limitation at the expense of noisy state estimates. A recent regularized particle filter was proposed to control the regularization process by a Metropolis-Hasting step. The method was shown to increase particle filter robustness while decreasing the variance of the estimates. This paper goes further by introducing an appropriate criterion which measures the degeneracy of the particle cloud. This criterion is used to control the regularization which is not applied systematically reducing the algorithm computational cost. The main idea of the proposed strategy is to monitor on line the mean jumps of the predicted measurement likelihood by means of a CUSUM algorithm. Simulation results are proposed to validate the relevance of the criterion and the performance of the overall algorithm.

Efficient Variable Rate Particle Filters For Tracking Manoeuvring Targets Using An MRF-based Motion Model

William Ng (University of Cambridge, United Kingdom); Sze Kim Pang (University of Cambridge, United Kingdom); Jack Li (University of Cambridge, United Kingdom); Simon GODSILL (University of Cambridge, United Kingdom)

In this paper we describe an efficient real-time tracking algorithm for multiple manoeuvring targets using particle filters. We combine independent partition filters with a Markov Random Field motion model to enable efficient and accurate tracking for interacting targets. A Poisson model is also used to model both targets and clutter measurements, avoiding the data association difficulties associated with traditional tracking approaches. Moreover, we present a variable rate dynamical model in which the states change at different and unknown rates compared with the observation process, thereby being able to model parsimoniously the manoeuvring behaviour of an object even though only a single dynamical model is employed. Computer simulations demonstrate the potential of the proposed method for tracking multiple highly manoeuvrable targets in a hostile environment with high clutter density and low detection probability.

A Particle Filter for Beacon-Free Node Location and Target Tracking in Sensor Networks

Joaquín Míguez (Universidad Carlos III de Madrid, Spain); Antonio Artés-Rodríguez (Universidad Carlos III de Madrid, Spain)

We address the problem of tracking a maneuvering target that moves along a region monitored by a sensor network, whose nodes, including both the sensors and the data fusion center (DFC), are located at unknown positions. Therefore, the node locations and the target track must be estimated jointly without the aid of beacons. We assume that, when the network is started, each sensor is able to detect the presence of other nodes within its range and transmit the resulting binary data to the DFC. After this startup phase, the sensor nodes just measure some physical magnitude related to the target position and/or velocity and transmit it to the DFC. At the DFC, a particle filtering (PF) algorithm is used to integrate all the collected data and produce on-line estimates of both the (static) sensor locations and the (dynamic) target trajectory. The validity of the method is illustrated by computer simulations of a network of power-aware sensors.

Tracking a Large Number of Targets in Clutter with Particle Filter

Darko Musicki (University of Melbourne, Australia); Mark Morelande (University of Melbourne, Australia)

Multitarget tracking in clutter has two levels of complexity. One is caused by the exponential increase of number of measurement histories in time, and the other is caused by complexity in allocating measurements to tracks in each scan, which is also exponential in the number of tracks and the number of measurements involved. Linear Multitarget tracking is a Bayesian method for multi target tracking which dispenses with measurement to track allocation completely. This results in complexity which is linear in the number of tracks and the number of measurements. This method is seamlessly integrated with a number of filters which use the target existence paradigm. In this paper the Linear Multitarget methodology is integrated with a particle filter implementation of IPDA and applied to a situation where a large number of targets with crossing trajectories exist in significant clutter. A simulation study shows the effectiveness of this approach, concentrating on the false track discrimination and track retention capabilities of this filter.

On Low-Power Analog Implementation of Particle Filters for Target Tracking

Rajbabu Velmurugan (Georgia Tech, USA); Shyam Subramanian (Georgia Tech, USA); Volkan Cevher (University of Maryland, USA); David Abramson (Monash University, Australia); Kofi Odame (Georgia Tech, USA); Jordan Gray (Georgia Tech, USA); Haw-Jing Lo (Georgia Tech, USA); James McClellan (Georgia Tech, USA); David Anderson (Georgia Tech, USA)

We propose a low-power, analog and mixed-mode, implementation of particle filters. Low-power analog implementation of nonlinear functions such as exponential and arctangent functions is done using multiple-input translinear element (MITE) networks. These nonlinear functions are used to calculate the probability densities in the particle filter. A bearings-only tracking problem is simulated to present the proposed low-power implementation of the particle filter algorithm.

A Joint Radar-Acoustic Particle Filter Tracker with Acoustic Propagation

Volkan Cevher (University of Maryland, USA); Milind Borkar (Georgia Institute of Technology, USA); James McClellan (Georgia Institute of Technology, USA)

In this paper, a novel particle filter tracker is presented for target tracking using collocated radar and acoustic sensors. Real-time tracking of the target's position and velocity in Cartesian coordinates is performed using batches of range and direction-of-arrival estimates. For robustness, the filter aligns the radar and acoustic data streams to account for acoustic propagation delays. The filter proposal function uses a Gaussian approximation to the full tracking posterior for improved efficiency. To incorporate the aligned acoustic data into the tracker, a two-stage weighting strategy is proposed. Computer simulations are provided to demonstrate the effectiveness of the algorithm.

Advances in Cost-Reference Particle Filtering

Monica Bugallo (Stony Brook University, USA); Petar Djuric (State University of New York at Stony Brook, USA)

Recently, we have proposed a particle filtering-type methodology, which we refer to as cost-reference particle filtering (CRPF). Its main feature is that it is not based on any particular probabilistic assumptions regarding the studied dynamic model. The concepts of particles and particle streams, however, are the same in CRPF as in standard particle filtering (SPF), but the probability masses of the particles are replaced with user defined costs. In this paper we propose some modifications of the original CRPF methodology. The changes allow for development of simpler algorithms, which may also be less computationally intensive and possibly more robust. We investigate several variants of CRPF and compare them with SPF. The advantages and disadvantages of the considered algorithms are illustrated and discussed through computer simulations of tracking of multiple targets which move along a two-dimensional space.

A slope-based technique for motion estimation and optimum time selection for ISAR imaging of ship targets

Debora Pastina (University of Rome "La Sapienza", Italy); Chiara Spina (Selex Airborne and Sensor Systems - Galileo Avionica Spa, Italy); Angelo Aprile (Selex Airborne and Sensor Systems - Galileo Avionica Spa, Italy)

The focus of this paper is on optimum time selection and angular motion estimation for ship ISAR imaging. The aim is to select proper imaging intervals and to estimate ship angular motion in order to obtain high quality top-view or side-view ship images suitable for processing by classifica-tion/identification procedures. To this purpose a slope-based ISAR algorithm is proposed, able to estimate the time instants better suited for top or side-view image formation and the rotation motion vertical/horizontal components for image scaling. The performance of the proposed ISAR tech-nique is investigated against simulated data under different ship model, ship motion, acquisition geometry and back-ground conditions. Results obtained by applying the pro-posed technique to live ISAR data proves the effectiveness of the proposed approach.

Radar Imaging via Adaptive MIMO Techniques

Luzhou Xu (University of Florida, USA); Jian Li (University of Florida, USA); Petre Stoica (Uppsala University, Sweden)

We investigate several adaptive techniques for a multiple-input multiple-output (MIMO) radar system. By transmitting independent waveforms via different antennas, the echoes due to targets at different locations are linearly independent of each other, which allows the direct application of many adaptive techniques. We discuss several adaptive radar imaging algorithms, which can provide excellent estimation accuracy of both target locations and target amplitudes, and high robustness to the array calibration errors. To reject the false peaks due to the strong jammers, we also propose a generalized likelihood ratio test (GLRT). As shown by the numerical examples, the number of targets can be estimated accurately by using GLRT, and an accurate description of the target scenario can be obtained by combining the adaptive radar imaging algorithms and the GLRT technique.

Optimised Image Autofocusing for Polarimetric ISAR

Marco Martorella (University of Pisa, Italy)

The use of full polarisation enables multi-channel SAR processing for enhancing both imaging and classification capabilities. In the field of Inverse Synthetic Aperture Radar (ISAR) very little has been investigated, especially from the point of view of multi-channel ISAR image formation. In this paper, the authors want to define an optimised image auto-focusing technique that exploits full polarisation informa-tion. Theory and simulation results will be provided in the paper.

S-Method in radar imaging

Ljubisa STANKOVIC (University of Montenegro, Serbia and Montenegro); Thayananthan Thayaparan (Radar Applications and Space Technology, Defence Research and Development Canada, Ottawa, Canada, Canada); Milos Dakovic (University of Montenegro, Serbia and Montenegro); Vesna Popovic (University of Montenegro, Serbia and Montenegro)

Commonly used technique for the SAR and ISAR signal analysis is a two-dimensional Fourier transform. Moving targets in SAR or maneuvering targets in ISAR case, induce Doppler-shift and Doppler spread in the returned signal, producing blurred or smeared images. Standard techniques for the solution of these problems are motion compensation and time-frequency analysis based techniques. Both of them are computationally intensive. Here, we will present a numerically simple S-method based approach that belongs to the time-frequency techniques. Beside the basic S-method here we will present the signal adaptive form and two-dimensional form of this method. They improve readability of the radar images what will be demonstrated on the simulated SAR and ISAR setups.

AD-based Detector for Denoising in ISAR Imaging

Omar Yeste (Universidad Politécnica de Madrid, Spain); Jesús Grajal (Universidad Politécnica de Madrid, Spain)

We have investigated two different strategies to improve the quality of ISAR images corrupted by Gaussian noise. The images are generated using a Time Frequency technique known as Atomic Decomposition (AD). The first strategy is a classical denoising technique based on an AD detector developed for signal detection in noise. The second technique separates the atoms extracted through AD by their parameters in two classes: atoms coming from noise and atoms coming from signal components. Compared to the first one, the second technique requires a greater knowledge about the signal components.

A Novel Focusing Technique for ISAR in case of Uniform Rotation Rate

José María Muñoz-Ferreras (Universidad Politécnica de Madrid, Spain); Félix Pérez-Martínez (Universidad Politécnica de Madrid, Spain)

A method for the correction of Migration Through Resolution Cells (MTRC) in ISAR (Inverse Synthetic Aperture Radar) is addressed here. The new technique needs neither to know the target motion parameters, to estimate them nor to use optimization to maximize (minimize) an image focusing indicator. It assumes that the target rotation rate is uniform and the direction of the effective rotation vector does not change during the Coherent Processing Interval (CPI). The algorithm corrects the MTRC in two phases: Slant Range Rotation Compensation (SRRC) and Cross Range Rotation Compensation (CRRC), where CRRC is based on an extension of the Phase Difference method (PD). The effectiveness of the proposed technique is verified with simulated (MIG-25 aircraft) and real (sailboat) radar data and compared with the standard Range-Doppler Algorithm (RDA).

Signal Processing for Target Motion Estimation and Image Formation in Radar Imaging of Moving Targets

Trygve Sparr (FFI, Norway)

Radar imaging of moving targets is often called ISAR (Inverse Synthetic Aperture Radar.) Imaging of moving targets generally consists of two separate tasks: Estimation and correction of target motion, and the explicit image formation. Both tasks must be implemented with great care, as it is the coherent processing of the received radar signal phase that makes imaging possible. Of the two tasks, the motion compensation is often most difficult, as many radar targets move in a complicated and fairly unpredictable manner. When the motion is complicated, the imaging step can be a challenge as well. The reason is that the target 3D-structure begins to matter, and projection plane effects may cause blurred images for even well designed ISAR processors.

Sparse sources are separated sources

Scott Rickard (University College Dublin, Ireland)

Sparse respresentations are being used to solve problems previously thought insolvable. For example, we can separate more sources than sensors using an appropriate transformation of the mixtures into a domain where the sources are sparse. But what do we mean by sparse? What attributes should a sparse measure have? And how can we use this sparsity to separate sources? We investigate these questions and, as a result, conclude that sparse sources are separated sources, as long as you use the correct measure.

Towards Underdetermined Source Reconstruction from a Clasp-and-Play Binaural Live Recording

Pau Bofill (Universitat Politecnica de Catalunya, Spain)

The goal of our current research is to be able to separate a few audio sources from the signals of two microphones, using a separate recording of each player clasping their hands. The separation is performed in the frequency domain, where speech and music signals are mostly sparse. The clasping is used to estimate each transfer function, and the sources are reconstructed using Second Order Cone Programming (SOCP). Our experiments show moderatly good results for synthetic mixtures (11.5dB average SNR) and poor results for the real case (2.2dB). This paper points out some of the issues that make this task a difficult one, and shows some experimental analysis of why this is so.

Bayesian blind separation of audio mixtures with structured priors

Cédric Févotte (University of Cambridge, United Kingdom)

In this paper we describe a Bayesian approach for separation of linear instantaneous mixtures of audio sources. Our method exploits the sparsity of the source expansion coefficients on a time-frequency basis, chosen here to be a MDCT. Conditionally upon an indicator variable which is 0 or 1, one source coefficient is either set to zero or given a Student t prior. Structured priors can be considered for the indicator variables, such as horizontal structures in the time-frequency plane, in order to model temporal persistency. A Gibbs sampler (a standard Markov chain Monte Carlo technique) is used to sample from the posterior distribution of the indicator variables, the source coefficients (corresponding to nonzero indicator variables), the hyperparameters of the Student t priors, the mixing matrix and the variance of the noise. We give results for separation of a musical stereo mixture of 3 sources.

Normalized Observation Vector Clustering Approach for Sparse Source Separation

Shoko Araki (NTT communication Science Laboratories, Japan); Hiroshi Sawada (NTT communication Science Laboratories, Japan); Ryo Mukai (NTT communication Science Laboratories, Japan); Shoji Makino (NTT Communication Science Laboratories, Japan)

This paper presents a new method for the blind separation of sparse sources whose number N can exceed the number of sensors M. Recently, sparseness based blind separation has been actively studied. However, most methods utilize a linear sensor array (or only two sensors), and therefore have certain limitations; e.g., they cannot be applied to symmetrically positioned sources. To allow the use of more than two sensors that can be arranged in a non-linear/non-uniform way, we propose a new method that includes the normalization and clustering of the observation vectors. We report promising results for the speech separation of 3-dimensionally distributed five sources with non-linear/non-uniform sensor arrangements of four sensors in a room (RT_{60}= 120 ms).

Current and future trends in embedded VLIW microprocessors applied to multimedia and signal processing

Giuseppe Desoli (STMicroelectronics, Switzerland); Thierry Strudel (STMicroelectronics, France); Jean-Philippe Cousin (STMicroelectronics, France); Kaushik Saha (STMicroelectronics, India, India)

Although Very Long Instruction Word (VLIW) processors mix of performance, power consumption, flexibility and cost is a very good match for embedded systems in general and multimedia streaming ones in particular; they might be adversely exposed to increasing memory latencies, code size bloat and to some extent performance scalability with increasing issue width. This paper presents two extensions for such VLIW micros that have a large potential impact when applied to the highly competitive market of multimedia con-sumer applications and more recently streaming: Symmetric Multi Processor (SMP) cache coherency and multithreading; we present a quick summary of those developments carried out by STMicroelec-tronics within the framework of the ST200 family of embedded mi-croprocessor and preliminary results obtained from their use in selected video and audio applications

Hardware co-processor for real-time and high quality H.264/AVC video coding

Maurizio Martina (Politecnico di Torino, Italy); Guido Masera (Politecnico di Torino, Italy); Luca Fanucci (University of Pisa, Italy); Sergio Saponara (University of Pisa, Italy)

Real-Time and High-Quality video coding is gaining a wide interest in the research community, mainly for entertainment and leisure applications. Furthemore H.264/AVC, the most recent standard for high performance video coding, can be successfully exploited in such a critical scenario. The need for high-quality imposes to sustain up to tens of Mbits/s. To that purpose in this paper optimized architectures for H.264/AVC most critical tasks, Motion Estimation (ME) and Context Aware Binary Arithmetic Coding (CABAC) are pro-posed. Post synthesis results on a 0.18 µm standard cells technology show that the proposed architectures can actu-ally process in real time 720x480 video sequences at 30 Hz and grant more than 20Mbits/s in the simplest configuration. Keywords: Video coding, H.264/AVC, Hardware architec-tures, motion estimation, entropy coder

Performance Optimization for Multimedia Transmission in Wireless Home Networks

Diego Melpignano (STMicroelectronics, Italy); Gabriella Convertino (STMicroelectronics, Italy); Andrea Vitali (STM, Italy); Juan Carlos De Martin (Politecnico di Torino, Italy); Paolo Bucciol (Politecnico di Torino, Italy); Antonio Servetti (Dipartimento di Automatica ed Informatica - Politecnico di Torino, Italy)

This paper describes a network adaptive real-time demonstrator for converged applications (audio, video, voice, and data) on an IEEE802.11g Wireless Home Network. Video transmission qual-ity is optimised by dynamically adapting the source video bit-rate to a real-time estimate of the available bandwidth on the wireless network and by introducing data redundancy to recover packet losses (Forward Error Correction). Video adaptation is done by DCT-domain video transcoding algorithms performed in real-time on a digital signal processor. Voice over Internet Protocol (VoIP) services are offered manag-ing the coexistence of 802.11g terminals and Bluetooth headsets. Audio time-scale modification and adaptive playout algorithms enable robust and high quality interactive voice communications minimizing the effect of packet losses and jitter typical of wireless scenarios. All devices can share and remotely control content via Universal Plug and Play (UPnP).

Design of Application Specific Instruction-set Processor for Image and Video Filtering

Sergio Saponara (University of Pisa, Italy); Luca Fanucci (University of Pisa, Italy); Stefano Marsi (University of Trieste, Italy); Giovanni Ramponi (University of Trieste, Italy); Martin Witte (University of Aachen, Germany); David Kammler (University of Aachen, Germany)

Two architectures for cost-effective and real-time implementation of non-linear image and video filters are presented in the paper. The first architecture is a traditional VHDL-based ASIC (Application Specific Integrated Circuit) design while the second one is an ADL (Architecture Description Language) based ASIP (Application Specific Instruction Set Processor). A system to improve the visual quality of images, based on Retinex-like algorithm, is referred as case study. First, starting from a high-level functional description the design space is explored to achieve a linearized structural C model of the algorithm with finite arithmetic precision. For the algorithm design space exploration visual and complexity criteria are adopted while a statistical analysis of typical input images drives the algorithm optimization process. The algorithm is implemented both as ASIC and ASIP solution in order to explore the trade-off between the flexibility of a software solution and the power and complexity optimization of a dedicated hardware design. The aim is to achieve the desired algorithmic functionality and timing specification at reasonable complexity and power costs. Taking advantage of the processor programmability, the flexibility of the system is increased, involving e.g. dynamic parameter adjustment and color treatment. Gate level implementation results in a 0.18µm standard-cell CMOS technology are presented for both the ASIC and ASIP approach

An H.264-Based Video Encoding Scheme for 3D TV

Mahsa T. Pourazad (University of British Columbia, Canada); Panos Nasiopoulos (University of British Columbia, Canada); Rabab Ward (University of British Columbia, Canada)

This paper presents an H.264-based scheme for compress-ing 3D content captured by 3D depth range cameras. Exist-ing MPEG-2 based schemes take advantage of the correla-tion between the 2D video sequence and its corresponding depth map sequence, and use the 2D motion vectors (MV) for the depth video sequence as well. This improves the speed of encoding the depth map sequence, but it results in an increase in the bitrate or a drop in the quality of the re-constructed 3D video. This is found to be due to the MVs of the 2D video sequence not being the best choice for encod-ing some parts of the depth map sequence containing sharp edges or corresponding to distant objects. To solve this problem, we propose an H.264-based method which re-estimates the MVs and re-selects the appropriate modes for these regions. Experimental results show that the proposed method enhances the quality of the encoded depth map se-quence by an average of 1.77 dB. Finding the MVs of the sharp edge-included regions of the depth map sequence amounts to 30.64% of the computational effort needed to calculate MVs for the whole depth map sequence.

Code-aided Frequency Ambiguity Resolution and Channel Estimation for MIMO OFDM systems

Frederik Simoens (Ghent University, Belgium); Marc Moeneclaey (Ghent University, Belgium)

This contribution deals with channel estimation and frequency ambiguity resolution in a MIMO OFDM context. Existing blind frequency-recovery algorithms for OFDM are able to provide a reliable estimate of the frequency offset up to an integer multiple of the subcarrier spacing. To resolve the remaining ambiguity, one can employ either pilot symbols or the unknown coded data symbols. Clearly, the latter method results in a higher bandwidth efficiency. Similar considerations hold for the estimation of a frequency-selective MIMO channel. In this contribution, we propose a code-aided technique to jointly estimate the channel and resolve the frequency ambiguity. The estimator is based on the expectation-maximization (EM) algorithm and exploits information from the unknown coded data symbols and only a small number of pilot symbols. A significant performance gain is observed compared to existing, solely pilot-based estimation techniques.

New Results in Iterative Frequency-Domain Decision-Feedback Equalization

Frédérique Sainte-Agathe (Supélec, Thales Communication, France); Hikmet Sari (Ecole Supérieure d'Electricité (SUPELEC), France)

Single-carrier transmission with frequency-domain equalization (SCT/FDE) is today recognized as an attractive alternative to orthogonal frequency-division multiplexing (OFDM) for wireless applications with large channel dispersions. In this paper, we investigate iterative frequency-domain decision- feedback equalization (FD/DFE), which significantly improves performance compared to minimum mean-square error (MMSE) and zero-forcing (ZF) linear equalizers. We introduce a new FD/DFE and compare it to previously proposed equalizers.

Network Planning for Multi-radio Cognitive Wireless Networks

Xiaodong Wang (Columbia University, USA)

We propose a general network planning framework for multi-radio multi-channel cognitive wireless networks. Under this framework, data routing, resource allocation, and scheduling are jointly designed to maximize a network utility function. We treat such a cross-layer design problem with fixed radio distributions across the nodes and formulate it as a large-scale convex optimization problem. A primal-dual method together with the column-generation technique is proposed to efficiently solve this problem. Simulation studies are carried out to assess the performance of the proposed cross-layer network planning framework. It is seen that the proposed approach can significantly enhance the overall network performance.

Space-Time Block Coding for Noncoherently Detected CPFSK

Fabrizio Pancaldi (University of Modena - Dept. of Information Eng., Italy); Giorgio M. Vitetta (University of Modena and Reggio Emilia, Italy)

In this paper the problem of unitary rate space-time block coding for multiple-input multiple-output communication systems employing continuous phase frequency shift keying is investigated. First, the problem of optimal codeword by codeword noncoherent detection is analysed; then, design criteria for optimal space-time clock codes are proposed and some novel coding schemes are devised. Simulation results evidence that the proposed schemes can efficiently exploit spatial diversity and that their use can entail a limited energy loss with respect to other solutions available in the technical literature for coherent systems, with the substantial advantage, however, of a simple detection algorithm.