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Resource-Scalable joint source-channel MAP and MMSE Estimation of Multiple Descriptions

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2009年第1期57卷 279-288页

作者： Wu, Xiaolin Wang, Xiaohan Wang, Zhe McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada

A joint source-channel multiple description (JSC-MD) framework for signal estimation and communication in resource-constrained lossy networks is presented. To keep the encoder complexity at a minimum, a signal is coded by a multiple description quantizer (MDQ) with neither entropy nor channel coding. The code diversity of MDQ and the path diversity of the network are exploited by decoders to combat transmission errors. A key design objective is resource scalability: powerful nodes in the network can perform JSC-MD estimation under the criteria of maximum a posteriori probability (MAP) or minimum mean-square error (MMSE), while primitive nodes resort to simpler MD decoding, all working with the same MDQ code. The application of JSC-MD to distributed estimation of hidden Markov models in a sensor network is demonstrated. The proposed JSC-MD MAP estimator is an algorithm of the longest path in a weighted directed acyclic graph, while the JSC-MD MMSE decoder is an extension of the well-known forward-backward algorithm to multiple descriptions. Both algorithms simultaneously exploit the source memory, the redundancy of the fixed-rate MDQ and the inter-description correlations. They outperform the existing hard-decision MDQ decoders by large margins (up to 8 dB). For Gaussian Markov sources, the complexity of JSC-MD distributed MAP sequence estimation can be made as low as that of typical single description Viterbi-type algorithms.

关键词： Complexity distributed estimation forward-backward algorithm hidden Markov model joint source-channel coding multiple descriptions sensor networks

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Tradeoffs Between Weak-Noise Estimation Performance and Outage Exponents in Nonlinear Modulation

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第8期65卷 5189-5196页

作者： Merhav, Neri Technion Andrew & Erna Viterbi Fac Elect Engn Haifa Israel

We focus on the problem of modulating a parameter onto a power-limited signal transmitted over a discrete-time Gaussian channel and estimating this parameter at the receiver. Considering the well-known threshold effect in the non-linear modulation systems, our approach is the following: instead of deriving upper and lower bounds on the total estimation error, which weighs both weak-noise errors and anomalous errors beyond the threshold, we separate the two kinds of errors. In particular, we derive upper and lower bounds on the best achievable tradeoff between the exponential decay rate of the weak-noise expected error cost and the exponential decay rate of the probability of the anomalous error event, also referred to as the outage event. This outage event is left to be defined as a part of the communication system design problem. Our achievability scheme, which is based on lattice codes, meets the lower bound at the high signal-to-noise limit and for a certain range of tradeoffs between the weak-noise error cost and the outage exponent.

关键词： Modulation parameter estimation joint source-channel coding Shannon-Kotel'nikov mappings lattice codes error exponents

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Fountain Code Design for Data Multicast with Side Information

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2009年第10期8卷 5155-5165页

作者： Sejdinovic, Dino Piechocki, Robert J. Doufexi, Angela Ismail, Mohamed Univ Bristol Dept Elect & Elect Engn Ctr Commun Res Bristol Avon England Toshiba Res Europe Ltd Telecommun Res Lab Bristol Avon England

Fountain codes are a robust solution for data multi-casting to a large number of receivers which experience variable channel conditions and different packet loss rates. However, the standard fountain code design becomes inefficient if all receivers have access to some side information correlated with the source information. We focus our attention on the cases where the correlation of the source and side information can be modelled by a binary erasure channel (BEC) or by a binary input additive white Gaussian noise channel (BIAWGNC). We analyse the performance of fountain codes in data multicasting with side information for these cases, derive bounds on their performance and provide a fast and robust linear programming optimization framework for code parameters. We demonstrate that systematic Raptor code design can be employed as a possible solution to the problem at the cost of higher encoding/decoding complexity, as it reduces the side information scenario to a channel coding problem. However, our results also indicate that a simpler solution, non-systematic LT and Raptor codes, can be designed to perform close to the information theoretic bounds.

关键词： Fountain codes distributed compression joint source-channel coding side information

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Iterative source-channel decoding with Markov random field source models

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2006年第10期54卷 3688-3701页

作者： Kliewer, Jorg Goertz, Norbert Mertins, Alfred Univ Notre Dame Dept Elect Engn Notre Dame IN 46556 USA Univ Edinburgh Inst Digital Commun Joint Res Inst Signal & Image Proc Edinburgh EH9 3JL Midlothian Scotland Carl von Ossietzky Univ Oldenburg Dept Phys D-26111 Oldenburg Germany

We propose a joint source-channel decoding approach for multidimensional correlated source signals. A Markov random field (MRF) source model is used which exemplarily considers the residual spatial correlations in an image signal after source encoding. Furthermore, the MRF parameters are selected via an analysis based on extrinsic information transfer charts. Due to the link between MPFs and the Gibbs distribution, the resulting soft-input soft-output (SISO) source decoder can be implemented with very low complexity. We prove that the inclusion of a high-rate block code after the quantization stage allows the MRF-based decoder to yield the maximum average extrinsic information. When channel codes are used for additional error protection the MRF-based SISO source decoder can be used as the outer constituent decoder in an iterative source-channel decoding scheme. Considering an example of a simple image transmission system we show that iterative decoding can be successfully employed for recovering the image data, especially when the channel is heavily corrupted.

关键词： EXIT charts iterative source-channel decoding joint source-channel coding Markov random fields

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Design of channel-optimized vector quantizers in the presence of channel mismatch

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IEEE TRANSACTIONS ON COMMUNICATIONS 2000年第1期48卷 118-124页

作者： Jafarkhani, H Farvardin, N Univ Maryland Dept Elect Engn College Pk MD 20742 USA Univ Maryland Syst Res Inst College Pk MD 20742 USA

We study the design of channel-optimized vector quantizers in the presence of channel mismatch, We show that when the statistics of the channel bit-error rate (BER) are not known, a minimax solution is the one obtained by designing for the worst possible channel. Then, we consider the case when the probability density function of channel BER is known and propose an algorithm that provides a minimum average distortion. Also, by using an estimate of the channel BER at the decoder, we develop a decoder-adaptive scheme that further improves the performance. In all cases, me have limited ourselves to table-lookup decoders, which amount to very small computational complexities. Finally, the utilization of lookup tables at the encoder and the effects of imperfect estimation of channel BER's are considered.

关键词： channel mismatch decoder-adaptive joint source-channel coding lookup tables vector quantization

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source-channel Communication Over Phase-Incoherent Multiuser channels

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IEEE TRANSACTIONS ON COMMUNICATIONS 2014年第8期62卷 2996-3003页

作者： Saffar, Hamidreza Ebrahimzadeh Alian, Ehsan Haj Mirza Mitran, Patrick Univ Waterloo Waterloo ON N2L 3G1 Canada

We study the transmission of two correlated and memoryless sources (U-1, U-2) over several multiuser phase asynchronous channels. Namely, we consider a multiple access relay channel (MARC) with causal, and a MARC with non-causal unidirectional cooperation between encoders, referred to as phase-incoherent causal (respectively, non-causal) cognitive MARCs. We also consider phase-incoherent interference channel models with and without relay, in the same context. In all cases, the input signals are assumed to undergo non-ergodic phase shifts, which are unknown to the transmitters and known to the receivers as a realistic assumption. Both necessary and sufficient conditions in order to reliably send the correlated sources to the destinations are derived. In particular, for all of the channel models, by using a key lemma, we first derive an outer bound for reliable communication. Then, using separate source and channel coding and under specific gain conditions, we establish the same region as the inner bound. We thus conclude that without the knowledge of the phase shifts at transmitters, and under specific gain conditions, separation is optimal.

关键词： joint source-channel coding phase uncertainty multiple access relay channel interference channel correlated sources

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Optimized Low-Delay source-channel-Relay Mappings

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IEEE TRANSACTIONS ON COMMUNICATIONS 2010年第5期58卷 1397-1404页

作者： Karlsson, Johannes Skoglund, Mikael Royal Inst Technol KTH Sch Elect Engn SE-10044 Stockholm Sweden Royal Inst Technol KTH ACCESS Linnaeus Ctr SE-10044 Stockholm Sweden

The three-node relay channel with a Gaussian source is studied for transmission subject to a low-delay constraint. A design algorithm for joint source-channel mappings is proposed and numerically evaluated. The designed system is compared with reference systems, based on modular source and channel coding, and the distortion-rate function for the Gaussian source using known achievable rates for the relay channel. There is a significant gain, in terms of decreased power, in using the (locally) optimized systems compared with the reference systems. The structure of the resulting source mapping and the relay mapping is visualized and discussed in order to gain understanding of fundamental properties of optimized systems. Interestingly, the design algorithm generally produces relay mappings with a structure that resembles Wyner-Ziv compression.

关键词： Estimation joint source-channel coding relay channel quantization sensor networks

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Iterative list decoding of concatenated source-channel codes

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EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING 2005年第6期2005卷 954-960页

作者： Hedayat, A Nosratinia, A Univ Texas Multimedia Commun Lab Richardson TX 75083 USA

Whenever variable-length entropy codes are used in the presence of a noisy channel, any channel errors will propagate and cause significant harm. Despite using channel codes, some residual errors always remain, whose effect will get magnified by error propagation. Mitigating this undesirable effect is of great practical interest. One approach is to use the residual redundancy of variable-length codes for joint source-channel decoding. In this paper, we improve the performance of residual redundancy source-channel decoding via an iterative list decoder made possible by a nonbinary outer CRC code. We show that the list decoding of VLCs is beneficial for entropy codes that contain redundancy. Such codes are used in state-of-the-art video coders, for example. The proposed list decoder improves the overall performance significantly in AWGN and fully interleaved Rayleigh fading channels.

关键词： joint source-channel coding variable-length codes list decoding iterative decoding

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DeepWiVe: Deep-Learning-Aided Wireless Video Transmission

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2022年第9期40卷 2570-2583页

作者： Tung, Tze-Yang Gunduz, Deniz Imperial Coll London Informat Proc & Commun Lab IPC Lab London SW7 2AZ England

We present DeepWiVe, the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. Our DNN decoder predicts residuals without distortion feedback, which improves the video quality by accounting for occlusion/disocclusion and camera movements. We simultaneously train different bandwidth allocation networks for the frames to allow variable bandwidth transmission. Then, we train a bandwidth allocation network using reinforcement learning (RL) that optimizes the allocation of limited available channel bandwidth among video frames to maximize the overall visual quality. Our results show that DeepWiVe can overcome the cliff-effect, which is prevalent in conventional separation-based digital communication schemes, and achieve graceful degradation with the mismatch between the estimated and actual channel qualities. DeepWiVe outperforms H.264 video compression followed by low-density parity check (LDPC) codes in all channel conditions by up to 0.0485 in terms of the multi-scale structural similarity index measure (MS-SSIM), and H.265+ LDPC by up to 0.0069 on average. We also illustrate the importance of optimizing bandwidth allocation in JSCC video transmission by showing that our optimal bandwidth allocation policy is superior to uniform allocation as well as a heuristic policy benchmark.

关键词： Bandwidth Video compression Wireless communication Distortion channel allocation Resource management Parity check codes Deep learning joint source-channel coding video compression wireless video transmission

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A unified framework for layered transmission over fading and packet erasure channels

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IEEE TRANSACTIONS ON COMMUNICATIONS 2008年第4期56卷 565-573页

作者： Etemadi, Farzad Jafarkhani, Hamid Univ Calif Irvine Dept EECS Irvine CA 92717 USA

We consider layered transmission of a successively refinable source over a quasi-static fading channel. We establish a duality relationship between this problem and that of packet transmission over erasure channels and use it to share solution techniques in both domains. For a Gaussian source and the fading channel, a low-complexity, optimal algorithm is proposed, and it is shown that the corresponding dual for packet erasure channels has linear complexity as opposed to the quadratic complexity of the best known optimal algorithms in the literature. For non-Gaussian sources, the optimal rate allocation problem for fading channels is solved using the dual solution for erasure channels. It is also shown that a single-layer system is optimal for fading channels if the goal is to maximize the rate. Numerical results for multiple antenna Rayleigh fading channels are presented for Gaussian sources and practical image coders. It is shown that a few number of layers significantly improves the performance. Finally, we numerically show that for practical operating conditions, optimizing the asymptotic measure of distortion exponent is not enough when there are more than one transmit or receive antennas.

关键词： joint source-channel coding MIMO fading channels successive refinement packet erasure channels outage capacity

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