In a communication system it results undoubtedly of great interest to compress the information generated by the data sources to its most elementary representation, so that the amount of power necessary for reliable communications can be reduced. It is often the case that the redundancy shown by a wide variety of information sources can be modelled by taking into account the probabilistic dependance among consecutive source symbols rather than the probabilistic distribution of a single symbol. These sources are commonly referred to as single or multiterminal sources "with memory" being the memory, in this latter case, the existing temporal correlation among the consecutive symbol vectors generated by the multiterminal source. It is well known that, when the source has memory, the average amount of information per source symbol is given by the entropy rate, which is lower than its entropy ...

Wyner-Ziv (WZ) video coding is a particular case of distributed video coding, a new video coding paradigm based on the Slepian-Wolf and Wyner-Ziv theorems which mainly exploit the source correlation at the decoder and not only at the encoder as in predictive video coding. Therefore, this new coding paradigm may provide a flexible allocation of complexity between the encoder and the decoder and in-built channel error robustness, interesting features for emerging applications such as low-power video surveillance and visual sensor networks among others. Although some progress has been made in the last eight years, the rate-distortion performance of WZ video coding is still far from the maximum performance attained with predictive video coding. The WZ video coding compression efficiency depends critically on the capability to model the correlation noise between the original information at the encoder and its estimation generated ...

Efficient decoding techniques for LDPC codes are in demand, since these codes are included in many standards nowadays. Although the theoretical performance of LDPC codes is impressive, their practical implementation leads to problems like numerical inaccuracy, limited memory resources, etc. We investigate methods that are suited to reduce the decoding complexity while still keeping the loss in performance small. We aim to reduce the complexity using three approaches: simplification of the component decoders, restricting the message passing algorithm to binary variables and combining the LDPC decoder with other receiver tasks like demapping or multi-user detection. For the simplification of the component decoders, we analyze the min-sum algorithm and derive a theoretical framework which is used to explain previous heuristic approaches to improve the performance of this algorithm. Using this framework, we are able to modify the algorithm in order to ...

This dissertation presents a general method and eight algebraic methods for constructing high performance and efficiently encodable non-binary quasi-cyclic LDPC codes based on arrays of special circulant permutation matrices. Two design techniques, array masking and array dispersion, for constructing both regular and irregular LDPC codes with desired specifications are also proposed. Codes constructed based on these methods perform very well over the AWGN channel and flat fading channels. With iterative decoding using a Fast Fourier Transform based sum-product algorithm, they achieve significantly large coding gains over Reed-Solomon codes of the same lengths and rates decoded with either algebraic hard-decision Berlekamp- Massey algorithm or algebraic soft-decision K¨otter-Vardy algorithm. Also presented is a class of asymptotically optimal LDPC codes for correcting bursts of erasures. Due to their quasi-cyclic structure, these non-binary LDPC codes can be encoded using simple shift-registers with linear complexity. ...

Distributed Video Coding (DVC) is a recently proposed paradigm in video communication, which fits well emerging applications such as wireless video surveillance, multimedia sensor networks, wireless PC cameras, and mobile cameras phones. These applications require a low complexity encoding, while possibly affording a high complexity decoding. DVC presents several advantages: First, the complexity can be distributed between the encoder and the decoder. Second, the DVC is robust to errors, since it uses a channel code. In DVC, a Side Information (SI) is estimated at the decoder, using the available decoded frames, and used for the decoding and reconstruction of other frames. In this Ph.D thesis, we propose new techniques in order to improve the quality of the SI. First, successive refinement of the SI is performed after each decoded DCT band, using a Partially Decoded WZF (PDWZF), along with the ...

Source coding concerns the representation of information in a source signal using as few bits as possible. In the case of lossy source coding, it is the encoding of a source signal using the fewest possible bits at a given distortion or, at the lowest possible distortion given a specified bit rate. Channel coding is usually applied in combination with source coding to ensure reliable transmission of the (source coded) information at the maximal rate across a channel given the properties of this channel. In this thesis, we consider the coding of auto-regressive (AR) sources which are sources that can be modeled as auto-regressive processes. The coding of AR sources lends itself to linear predictive coding. We address the problem of joint source/channel coding in the setting of linear predictive coding of AR sources. We consider channels in which individual ...

In the modern wireless age, lightweight multimedia technology stimulates attractive commercial applications on a grand scale as well as highly specialized niche markets. In this regard, the design of efficient video compression systems meeting such key requirements as very low encoding complexity, transmission error robustness and scalability, is no straightforward task. The answer can be found in fundamental information theoretic results, according to which efficient compression can be achieved by leveraging knowledge of the source statistics at the decoder only, giving rise to distributed, or alias Wyner-Ziv, video coding. This dissertation engineers efficient lightweight Wyner-Ziv video coding schemes emphasizing on several design aspects and applications. The first contribution of this dissertation focuses on the design of effective side information generation techniques so as to boost the compression capabilities of Wyner-Ziv video coding systems. To this end, overlapped block motion estimation ...

Reducing interference noise in a noisy speech recording has been a challenging task for many years yet has a variety of applications, for example, in handsfree mobile communications, in speech recognition, and in hearing aids. Traditional single-channel noise reduction schemes, such as Wiener filtering, do not work satisfactorily in the presence of non-stationary background noise. Alternatively, supervised approaches, where the noise type is known in advance, lead to higher-quality enhanced speech signals. This dissertation proposes supervised and unsupervised single-channel noise reduction algorithms. We consider two classes of methods for this purpose: approaches based on nonnegative matrix factorization (NMF) and methods based on hidden Markov models (HMM). The contributions of this dissertation can be divided into three main (overlapping) parts. First, we propose NMF-based enhancement approaches that use temporal dependencies of the speech signals. In a standard NMF, the important temporal ...

In this thesis, we present low latency general concatenated code structures suitable for parallel processing. We propose parallel decodable serially con- catenated codes (PDSCCs) which is a general structure to construct many variants of serially concatenated codes. Using this most general structure we derive parallel decodable serially concatenated convolutional codes (PDSC- CCs). Convolutional product codes which are instances of PDSCCCs are studied in detail. PDSCCCs have much less decoding latency and show al- most the same performance compared to classical serially concatenated con- volutional codes. Using the same idea, we propose parallel decodable turbo codes (PDTCs) which represent a general structure to construct parallel con- catenated codes. PDTCs have much less latency compared to classical turbo codes and they both achieve similar performance. We extend the approach proposed for the construction of parallel decod- able concatenated codes to trellis coded ...

In this dissertation we focus on statistical signal processing for Data Fusion, with a particular focus on wireless sensor networks. Six topics are studied: (i) Data Fusion for classification under model uncertainty; (ii) Decision Fusion over coherent MIMO channels; (iii) Performance analysis of Maximum Ratio Combining in MIMO decision fusion; (iv) Decision Fusion over non-coherent MIMO channels; (v) Decision Fusion for distributed classification of multiple targets; (vi) Data Fusion for inverse localization problems, with application to wideband passive sonar platform estimation. The first topic of this thesis addresses the problem of lack of knowledge of the prior distribution in classification problems that operate on small data sets that may make the application of Bayes' rule questionable. Uniform or arbitrary priors may provide classification answers that, even in simple examples, may end up contradicting our common sense about the problem. Entropic ...

Vision sensor networks and video cameras find widespread usage in several applications that rely on effective representation of scenes or analysis of 3D information. These systems usually acquire multiple images of the same 3D scene from different viewpoints or at different time instants. Therefore, these images are generally correlated through displacement of scene objects. Efficient compression techniques have to exploit this correlation in order to efficiently communicate the 3D scene information. Instead of joint encoding that requires communication between the cameras, in this thesis we concentrate on distributed representation, where the captured images are encoded independently, but decoded jointly to exploit the correlation between images. One of the most important and challenging tasks relies in estimation of the underlying correlation from the compressed correlated images for effective reconstruction or analysis in the joint decoder. This thesis focuses on developing efficient ...

Throughout this work, channel estimation techniques have been analyzed and proposed for moderate and very high mobility DVB (digital video broadcasting) receivers, focusing on the DVB-T2 (Digital Video Broadcasting - Terrestrial 2) framework and the forthcoming DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) standard. Mobility support is one of the key features of these DVB specifications, which try to deal with the challenge of enabling HDTV (high definition television) delivery at high vehicular speed. In high-mobility scenarios, the channel response varies within an OFDM (orthogonal frequency-division multiplexing) block and the subcarriers are no longer orthogonal, which leads to the so-called ICI (inter-carrier interference), making the system performance drop severely. Therefore, in order to successfully decode the transmitted data, ICI-aware detectors are necessary and accurate CSI (channel state information), including the ICI terms, is required at the receiver. With the ...

This PhD dissertation analyzes the performance of second generation digital video broadcasting (DVB) systems in mobile terrestrial environments and proposes an iterative detection algorithm based on factor graphs (FG) to reduce the distortion caused by the time variation of the channel, providing error-free communication in very severe mobile conditions. The research work focuses on mobile scenarios where the intercarrier interference (ICI) is very high: high vehicular speeds when long orthogonal frequency-division multiplexing (OFDM) blocks are used. As a starting point, we provide the theoretical background on the main topics behind the transmission and reception of terrestrial digital television signals in mobile environments, long with a general overview of the main signal processing techniques included in last generation terrestrial DVB systems. The proposed FG-based detector design is then assessed over a simpli ed bit-interleaved coded modulation (BICM)-OFDM communication scheme for a ...

Error control coding is an essential part of modern communications systems. LDPC codes have been demonstrated to offer performance near the fundamental limits of channels corrupted by random noise. Optimal maximum likelihood decoding of LDPC codes is too complex to be practically useful even at short block lengths and so a graph-based message passing decoder known as the belief propagation algorithm is used instead. In fact, on graphs without closed paths known as cycles the iterative message passing decoding is known to be optimal and may converge in a single iteration, although identifying the message update schedule which allows single-iteration convergence is not trivial. At finite block lengths graphs without cycles have poor minimum distance properties and perform poorly even under optimal decoding. LDPC codes with large block length have been demonstrated to offer performance close to that predicted for ...

Scalable representation of a source (e.g., image/video/3D mesh) enables decoding of the encoded bit-stream on a variety of end-user terminals with varying display, storage and processing capabilities. Furthermore, it allows for source communication via channels with different transmission bandwidths, as the source rate can be easily adapted to match the available channel bandwidth. From a different perspective, error-resilience against channel losses is also very important when transmitting scalable source streams over lossy transmission channels. Driven by the aforementioned requirements of scalable representation and error-resilience, this dissertation focuses on the analysis and design of scalable single and multiple description scalar quantizers. In the first part of this dissertation, we consider the design of scalable wavelet-based semi-regular 3D mesh compression systems. In this context, our design methodology thoroughly analyzes different modules of the mesh coding system in order to single-out appropriate design ...