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Data Extraction from Wireless Sensor Networks Using Distributed Fountain Codes

IEEE TRANSACTIONS ON COMMUNICATIONS 2009年第9期57卷 2607-2618页

作者： Oka, Anand Lampe, Lutz Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada

A Wireless Sensor Network (WSN) observes a natural field and aims to recreate it with sufficient fidelity at a, perhaps distant, Fusion Center (FC) using a wireless communication channel of arbitrary capacity. We propose a universal and power efficient method for such data extraction, based on Digital Fountain Codes (DFCs) and joint-source channel decoding. Our method implements a distributed 'rate-less' DFC which automatically tunes the number of transmissions to the channel capacity. Furthermore, instead of directly compressing the WSN data, we achieve rate reduction by treating the spatiotemporal dependencies in the field as an outer code, and jointly decoding this concatenation at the FC using a multi-stage iterative decoder. We demonstrate that a power efficiency close to the capacity-rate-distortion limit is achieved at moderate distortion levels, irrespective of the channel capacity or field dependencies. As compared to the traditional approach of source-channel separation, the proposed data extraction scheme is particularly attractive for WSN applications due its computationally simple encoding procedure, low latency and the ability to seamlessly trade-off fidelity of reconstruction for power consumption.

关键词： Wireless sensor networks distributed compression joint source-channel decoding fountain codes

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Unequal Error Protection Based on DVFS for JSCD in Low-Power Portable Multimedia Systems

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ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS 2012年第2期11卷 1–21页

作者： Yang, Yoon Seok Choi, Gwan Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA

This article presents a low-power decoder design for joint source-channel decoding (JSCD) based on a novel unequal error protection (UEP) scheme over additive white gaussian noise (AWGN) channels. Conventional JSCD schemes, adopting low-density parity check (LDPC) codes for multimedia devices, typically operate at a fixed-time decoding loop, regardless of the quality of data received. We present a JSCD scheme that achieves reduction in power through minimum energy decoding and dynamic voltage and frequency scaling (DVFS). Consequently, up to 39% power reduction is achieved in Foreman, Akiyo, and Mobile video streams without performance degradation in reconstructed video quality.

关键词： Design Performance Dynamic voltage and frequency scaling H.264 data partitioning LDPC low-power joint source-channel decoding unequal error protection

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EXIT Chart Analysis of Turbo Compressed Sensing Using Message Passing Dequantization

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2016年第24期64卷 6600-6612页

作者： Movahed, Amin Reed, Mark C. Aboutorab, Neda Tajbakhsh, Shahriar Etemadi Univ New South Wales Sch Engn & Informat Technol Canberra NSW 2052 Australia Univ Oxford Dept Engn Sci Oxford OX1 3PJ England

We propose a joint compressed sensing-based encoding and an iterative-decoding method, which we call turbo compressed sensing (turbo-CS), for the robust to noise transmission of sparse signals over an additive white Gaussian noise (AWGN) channel. The turbo-CS encoder applies 1-bit compressed sensing as a source encoder concatenated serially with a convolutional channel encoder. At the turbo-CS decoder, an iterative joint source-channel decoding method is proposed for signal reconstruction. We analyze, for the first time, the convergence of the turbo-CS decoder by determining an extrinsic information transfer chart of the constituent decoders. We modify the soft-outputs of the constituent source decoder to improve the signal reconstruction performance of the turbo-CS decoder. Our results show that for a fixed received signal to noise ratio (RSNR) of 10 dB more than 5 dB of improvement in the channel SNR is achieved after six iterations of the turbo-CS decoder. Alternatively, for a fixed SNR of -1 dB, 10 dB improvement in RSNR is achieved. Moreover, it is shown that the turbo-CS decoder outperforms the state-of-the-art algorithms for 1-bit compressed sensing reconstruction in the presence of AWGN channel in terms of signal reconstruction performance and complexity.

关键词： Turbo-coding 1-bit compressed sensing joint source-channel decoding message passing de-quantization

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Improved Sequential MAP Estimation of CABAC Encoded Data with Objective Adjustment of the Complexity/Efficiency Tradeoff

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IEEE TRANSACTIONS ON COMMUNICATIONS 2009年第7期57卷 2014-2023页

作者： Jamaa, Salma Ben Kieffer, Michel Duhamel, Pierre Univ Paris Sud Supelec CNRS LSS F-91192 Gif Sur Yvette France

This paper presents an improved sequential MAP estimator to be used as a joint source-channel decoding technique for CABAC encoded data. The decoding process is compatible with realistic implementations of CABAC in standards like H.264, Le, handling adaptive probabilities, context modeling and integer arithmetic coding. Soft-input decoding is obtained using an improved sequential decoding technique, which allows to obtain a tradeoff between complexity and efficiency. The algorithms are simulated in a context reminiscent of H264. Error detection is realized by exploiting on one side the properties of the binarization scheme and on the other side the redundancy left in the code string. As a result, the CABAC compression efficiency is preserved and no additional redundancy is introduced in the bit stream. Simulation results outline the efficiency of the proposed techniques for encoded data sent over AWGN and UMTS-OFDM channels.

关键词： Arithmetic coding joint source-channel decoding MAP estimation sequential decoding

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Deep Learning for Waveform Level Receiver Design With Natural Redundancy

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2023年第2期9卷 317-331页

作者： Zhu, Zhaorui Shen, Caiyao Yu, Hongyi Wang, Zhenyu Shen, Zhixiang Du, Jianping PLA Strateg Support Force Informat Engn Univ Informat Engn Coll Zhengzhou 450000 Henan Peoples R China

High-speed information transmission system demands more powerful communication receivers. In this paper, we integrate deep learning algorithms into constructing waveform level receiver, which is capable of harnessing natural redundancy (NR) in raw message sources. Owing to end-to-end learning paradigm of neural network (NN), the proposed NN receiver can accomplish joint symbol timing synchronization and demodulation based on oversampled waveform sequences directly. The prevalent bidirectional LSTM (BiLSTM) and Transformer structures, suitable for excavating sequential correlation of complex sources and waveform sequences, are considered as the backbone of NN receivers. Under the cases of clean label and noisy label, we conceive two novel training algorithms and interpret their principles in theory. The clean label bits are accessible from original source encoding schemes, while noisy label bits are available from the decision results of canonical receivers with independently noised waveform sequences. When noisy labels possess sufficiently small error rates, optimized NN receiver is competitive with that adopting the accurate labels. As for Markov sources and natural language text sources, simulation results show that the proposed NN receivers' performances are superior to the classical receivers without a priori knowledge, especially when high spectral efficiency modulation schemes are encountered and random noise is significant.

关键词： Receivers Artificial neural networks Noise measurement Training Synchronization Markov processes decoding Deep learning receiver design natural redundancy noisy label MAP detector joint source-channel decoding synchronization joint receiver design

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Distributed source Coding and Its Applications in Relaying-Based Transmission

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IEEE ACCESS 2016年 4卷 1940-1970页

作者： Aljohani, Abdulah Jeza Ng, Soon Xin Hanzo, Lajos Univ Southampton Southampton SO17 1BJ Hants England Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

Distributed source coding (DSC) schemes rely on separate encoding but joint decoding of statistically dependent sources, which exhibit correlation. DSC has numerous promising applications ranging from reduced-complexity handheld video communications to onboard hyperspectral image coding under computational limitations. The concept of separate encoding at the first sight compromises the attainable encoding performance. However, the DSC theory proves that independent encoding can in fact be designed as efficiently as joint encoding, as long as joint decoding is allowed. More specifically, distributed joint source-channel coding (DJSC) is associated with the scenario, where the correlated source signals are transmitted through a noisy channel. In this paper, we present a concise historic background of DSC concerning both its theory and its practical aspects. In addition, a series of turbo trellis-coded modulation (TTCM)-aided DJSC-based cooperative transmission schemes are proposed. DJSC scheme is conceived for the transmission of a pair of correlated sources to a destination node (DN). The first source sequence is TTCM encoded, and then, it is compressed before it is transmitted both over a Rayleigh fading channel, where the second source signal is assumed to be perfectly decoded side-information at the DN for the sake of improving the achievable decoding performance of the first source. The proposed scheme is capable of performing reliable communications for various levels of correlation near to the theoretical Slepian-Wolf/Shannon (SW/S) limit. Pursuing our objective of designing practical DJSC schemes, we further extended the above-mentioned arrangement to a more realistic cooperative communication system, where the pair of correlated sources are transmitted to a DN with the aid of a relay node (RN). Explicitly, the pair of correlated source sequences are TTCM encoded and compressed before transmission over a Rayleigh fading multiple access channel, where our propo

关键词： Distributed joint source coding distributed source coding Slepian-Wolf Coding joint source-channel decoding TTCM superposition modulation

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Monotonicity-based fast algorithms for MAP estimation of Markov sequences over noisy channels

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IEEE TRANSACTIONS ON INFORMATION THEORY 2004年第7期50卷 1539-1544页

作者： Wu, XL Dumitrescu, S Wang, Z McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada

In this correspondence, we study algorithmic approach to solving the problem of maximum a posteriori (MAP) estimation of Markov sequences transmitted over noisy channels, which is also known as the MAP decoding problem. For the class of memoryless binary channels that produce independent substitution and erasure errors, the MAP sequence estimation problem can be formulated and solved as one of the longest path in a weighted directed acyclic graph. But for algorithm efficiency, we transform the graph problem to one of matrix search. If the underlying matrix is totally monotone, then the complexity of MAP sequence estimation can be greatly reduced. We give a sufficient condition for the matrix induced by MAP sequence estimation to be totally monotone, which is indeed the case if the input sequence is Gaussian Markov. Under this condition, the complexity of MAP decoding can be reduced from O(N-2 M) to O(NM), where N is the size of source alphabet and M is the length of input sequence. Furthermore, for Markov sequences of fixed-length code we propose a block parsing strategy to reduce the complexity of MAP sequence estimation to O (M + N-2 M / log M) or to O (M + NM / log M), depending on if the total monotonicity holds. Another significance of this correspondence lies in the applicability of the presented algorithmic approach, which has been thoroughly studied in computer science literature, to many other discrete optimization problems encountered in both source and channel coding, ranging from optimal multiresolution and multiple-description quantizer design, to context quantization for minimum conditional entropy, and to optimal packetization with uneven error protection.

关键词： Gaussian Markov source joint source-channel decoding maximum a posteriori (MAP) sequence estimation Monge inequality string parsing weighted directed acyclic graph

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joint decoding of Unequally Protected JPEG2000 Bitstreams and Reed-Solomon Codes

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2010年第10期19卷 2693-2704页

作者： Bahmani, Sohail Bajic, Ivan V. HajShirmohammadi, Atousa Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada

In this paper we present joint decoding of JPEG2000 bitstreams and Reed-Solomon codes in the context of unequal loss protection. Using error resilience features of JPEG2000 bitstreams, the joint decoder helps to restore the erased symbols when the Reed-Solomon decoder fails to retrieve them on its own. However, the joint decoding process might become time-consuming due to a search through the set of possible erased symbols. We propose the use of smaller codeblocks and transmission of a relatively small amount of side information with high reliability as two approaches to accelerate the joint decoding process. The accelerated joint decoder can deliver essentially the same quality enhancement as the nonaccelerated one, while operating several times faster.

关键词： joint source-channel decoding JPEG2000 Reed-Solomon code unequal loss protection

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The Capacity Region of Multiway Relay channels Over Finite Fields With Full Data Exchange

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IEEE TRANSACTIONS ON INFORMATION THEORY 2011年第5期57卷 3016-3031页

作者： Ong, Lawrence Johnson, Sarah J. Kellett, Christopher M. Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW 2308 Australia

The multiway relay channel is a multicast network where L users exchange data through a relay. In this paper, the capacity region of a class of multiway relay channels is derived, where the channel inputs and outputs take values over finite fields. The cut-set upper bound to the capacity region is derived and is shown to be achievable by our proposed functional-decode-forward coding strategy. More specifically, for the general case where the users can transmit at possibly different rates, functional-decode-forward, combined with rate splitting and joint source-channel decoding, is proved to achieve the capacity region;while for the case where all users transmit at a common rate, rate splitting and joint source-channel decoding are not required to achieve the capacity. That the capacity-achieving coding strategies do not utilize the users' received signals in the users' encoding functions implies that feedback does not increase the capacity region of this class of multiway relay channels.

关键词： Bidirectional relaying capacity channel coding finite field functional-decode-forward joint source-channel decoding multiway relay channel (MWRC)

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Distributed video coding in pixel domain using spatial correlation at the decoder

Distributed video coding in pixel domain using spatial corre...

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Data Compression Conference (DCC)

作者： Lahsini, Cyrine Zaibi, Sonia Pyndiah, Ramesh Bouallegue, Ammar Telecom Bretagne Signal & Commun Dept Brest France ENIT Syscom Lab Tunis Tunisia

ISBN: (纸本)9780769543529

Distributed coding is a new paradigm for video compression based on Slepian-Wolf (1973) and Wyner-Ziv (1976) theorems. In this paper, we propose a new pixel-domain Distributed Video Coding (DVC) scheme, in which both the temporal and the spatial correlations are exploited only at the decoder. A joint source-channel decoding is implemented to exploit the source statistics. Iterations between the Map channel decoder and the BCJR source decoder are made to improve the global decoder performance. Simulations results show that a gain is obtained, in term of rate, with iterative joint source-channel decoding, compared to the basic decoding.

关键词： distributed video coding joint source-channel decoding turbo coding Video coding decoders Video compression channel Decoder turbo codes decoding Combined source-channel coding

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