Separate source and channelcoding is known to be sub-optimal for communicating correlated sources over a Gaussian multiple access channel (GMAC). This paper presents an approach to designing distributedjointsource-...
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Separate source and channelcoding is known to be sub-optimal for communicating correlated sources over a Gaussian multiple access channel (GMAC). This paper presents an approach to designing distributedjointsource-channel (DJSC) codes for encoding correlated binary sources over a two-user GMAC, using systematic irregular low-density parity check (LDPC) codes. The degree profile defining the LDPC code is optimized for the jointsource probabilities using extrinsic information transfer (EXIT) analysis and linear programming. A key issue addressed is the Gaussian modeling of log-likelihood ratios (LLRs) generated by nodes representing the jointsource probabilities in the combined factor graph of the two LDPC codes, referred to as source-channel factor (SCF) nodes. It is shown that the analytical expressions based on additive combining of incoming LLRs, as done in variable nodes and parity check nodes of the graph of a single LDPC code, cannot be used with SCF nodes. To this end, we propose a numerical approach based on Monte-Carlo simulations to fit a Gaussian density to outgoing LLRs from the SCF nodes, which makes the EXIT analysis of the joint decoder tractable. Experimental results are presented which show that LDPC codes designed with the proposed approach outperforms previously reported DJSC codes for GMAC. Furthermore, they demonstrate that when the sources are strongly dependent, the proposed DJSC codes can achieve code rates higher than the theoretical upper-bound for separate source and channelcoding.
Extending recent works on distributedsourcecoding, this paper considers distributedsource-channelcoding and targets at the important application of scalable video transmission over wireless networks. The idea is t...
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Extending recent works on distributedsourcecoding, this paper considers distributedsource-channelcoding and targets at the important application of scalable video transmission over wireless networks. The idea is to use a single channel code for both video coimpression (via Slepian-Wolf coding) and packet loss protection. First, we provide a theoretical code design framework for distributed joint source-channel coding over erasure channels and then apply it to the targeted video application. The resulting video coder is based on a cross-layer design where video compression and protection are performed jointly. We choose Raptor codes - the best approximation to a digital fountain - and address in detail both encoder and decoder designs. Using the received packets together with a correlated video available at the decoder as side information, we devise a new iterative soft-decision decoder for joint Raptor decoding. Simulation results show that, compared to one separate design using Slepian-Wolf compression plus erasure protection and another based on FGS coding plus erasure protection, the proposed joint design provides better video quality at the same number of transmitted packets. Our work represents the first in capitalizing the latest in distributedsourcecoding and near-capacity channelcoding for robust video transmission over erasure channels.
We consider the problem of transmission of several discrete sources over a multiple access channel (MAC) with side information at the sources and the decoder. source-channel separation does not hold for this channel. ...
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ISBN:
(纸本)9781424422562
We consider the problem of transmission of several discrete sources over a multiple access channel (MAC) with side information at the sources and the decoder. source-channel separation does not hold for this channel. Sufficient conditions are provided for transmission of sources with a given distortion. The channel could have continuous alphabets (Gaussian MAC is a special case). Various previous results are obtained as special cases.
作者：
Fang, YongNW A&F Univ
Coll Informat Engn Yangling 712100 Shaanxi Peoples R China
source correlation estimation is an important issue remained in Slepian-Wolf coding (SWC), while a counterpart issue in noisy transmission is channel noise estimation. This letter considers the transmission of SWC bit...
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source correlation estimation is an important issue remained in Slepian-Wolf coding (SWC), while a counterpart issue in noisy transmission is channel noise estimation. This letter considers the transmission of SWC bitstream over a noisy channel. We show that it is possible to estimate both source correlation and channel noise using an accumulated Low-Density Parity-Check (LDPC) syndrome.
This paper studies compress- forward (CF) coding with BPSK modulation for the half-duplex Gaussian relay channel. In CF relaying, Wyner-Ziv coding is applied at the relay to exploit the joint statistics between signal...
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This paper studies compress- forward (CF) coding with BPSK modulation for the half-duplex Gaussian relay channel. In CF relaying, Wyner-Ziv coding is applied at the relay to exploit the joint statistics between signals at the relay and the destination. We propose Slepian-Wolf coded nested scalar quantization (SWCNSQ) for practical Wyner-Ziv coding at the relay. We first provide the achievable rate of SWCNSQ based CF relaying as a performance benchmark, and then present a practical code design using low-density parity-check (LDPC) codes for error protection at the source, and nested scalar quantization plus irregular-repeat accumulation (IRA) codes for CF coding at the relay. The degree distributions of the LDPC and IRA codes are optimized using extrinsic information transfer charts and Gaussian approximation. Under discretized density evolution for asymptotically large block lengths, our optimized code design operates 0.11-0.21 dB away from the SWCNSQ limit for CF relaying. Simulations with LDPC/IRA codes of length 2 X 10(5) show a performance gap of 0.27-0.38 dB from the achievable rate.
In this paper, a turbo-based distributed joint source-channel coding scheme, for efficient compression and communication of two dependent sources with time memory over noisy channels, is presented. Specifically, we co...
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ISBN:
(纸本)9781424448562
In this paper, a turbo-based distributed joint source-channel coding scheme, for efficient compression and communication of two dependent sources with time memory over noisy channels, is presented. Specifically, we consider the asymmetric case for two binary sources, where one of the sources is available at the decoder as side information. The problem is of particular interest for low complexity compression and communication in data gathering sensor network and multimedia applications. Aiming at exploiting the spatial dependency of the sources, first, a distributedjointsource-channel turbo (DJSCT) decoder is developed. Then, a novel decoding scheme is proposed, which benefits from both time memory and spatial dependency between samples of the sources. The proposed decoder is composed of two DJSCT constituent decoders and a maximum a-posteriori constituent decoder, which operate in an iterative manner. As the results validate, the proposed schemes provide effective solutions for compression and robust reconstruction of distributed dependent sources with time memory.
In a typical sensor network scenario a goal is to monitor a spatio-temporal process through a number of inexpensive sensing nodes, the key parameter being the fidelity at which the process has to be estimated at dista...
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ISBN:
(纸本)9781424402694;9781424402700
In a typical sensor network scenario a goal is to monitor a spatio-temporal process through a number of inexpensive sensing nodes, the key parameter being the fidelity at which the process has to be estimated at distant locations. We study such a scenario in which multiple encoders transmit their correlated data at finite rates to a distant, common decoder over a discrete time multiple access channel under various side information assumptions. In particular, we derive an achievable rate region for this communication problem.
Based on recent works on Wyner-Ziv coding (WZC) (or lossy sourcecoding with decoder side information), this paper considers the case with noisy channel and addresses distributed joint source-channel coding (JSCC), wh...
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Based on recent works on Wyner-Ziv coding (WZC) (or lossy sourcecoding with decoder side information), this paper considers the case with noisy channel and addresses distributed joint source-channel coding (JSCC), while targeting at the important application of scalable video transmission over wireless networks. In WZC, after quantization, Slepian-Wolf coding (SWC) is used to reduce the rate. SWC is traditionally realized by sending syndromes of a linear channel code. Since syndromes of the channel code can only compress but cannot protect, for transmission over noisy channels, additional error protection is needed. However, instead of using one channel code for SWC and one for error protection, our idea is to use a single channel code to achieve both compression and protection. We replace the traditional syndrome-based SWC scheme by the parity-based one, where only parity bits of the Slepian-Wolf channel code are sent. If the amount of transmitted parity bits increases above the Slepian-Wolf limit, the added redundancy is exploited to cope against the noise in the transmission channel. Using irregular repeat-accumulate codes for practical parity-based SWC, we design a novel layered Wyner-Ziv video coder which is robust to channel failures and thus very suitable for wireless communications. Our simulation results show great advantages of the proposed solution based on JSCC compared to the traditional approach where source and channelcoding are performed separately. (c) 2006 Elsevier B.V. All rights reserved.
In a typical sensor network scenario a goal is to monitor a spatio-temporal process through a number of inexpensive sensing nodes, the key parameter being the fidelity at which the process has to be estimated at dista...
详细信息
In a typical sensor network scenario a goal is to monitor a spatio-temporal process through a number of inexpensive sensing nodes, the key parameter being the fidelity at which the process has to be estimated at distant locations. We study such a scenario in which multiple encoders transmit their correlated data at finite rates to a distant, common decoder over a discrete time multiple access channel under various side information assumptions. In particular, we derive an achievable rate region for this communication problem.
Based on recent works on Wyner-Ziv coding (or lossy sourcecoding with decoder side information), we consider the case with noisy channel and addresses distributed joint source-channel coding, while targeting at the i...
详细信息
ISBN:
(纸本)0819459763
Based on recent works on Wyner-Ziv coding (or lossy sourcecoding with decoder side information), we consider the case with noisy channel and addresses distributed joint source-channel coding, while targeting at the important application of scalable video transmission over wireless networks. In Wyner-Ziv coding, after quantization, Slepian-Wolf coding (SWC) is used to reduce the rate. SWC is traditionally realized by sending syndromes of a linear channel code. Since syndromes of the channel code can only compress but cannot protect, for transmission over noisy channels, additional error protection is needed. However, instead of using one channel code for SWC and one for error protection, our idea is to use a single channel code to achieve both compression and protection. We replace the traditional syndrome-based SWC scheme by the parity-based one, where only parity bits of the Slepian-Wolf channel code are sent. If the amount of transmitted parity bits increases above the Slepian-Wolf limit, the added redundancy is exploited to cope against the noise in the transmission channel. Using IRA codes for practical parity-based SWC, we design a novel layered Wyner-Ziv video coder which is robust to channel failures and thus very suitable for wireless communications. Our simulation results show great advantages of the proposed solution based on jointsource-channelcoding compared to the traditional approach where source and channelcoding are performed separately.
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