Article

Joint Source-Channel Estimation Using Accumulated LDPC Syndrome

Coll. of Inf. Eng., Northwest A&F Univ., Yangling, China
IEEE Communications Letters (Impact Factor: 1.16). 12/2010; DOI: 10.1109/LCOMM.2010.091710.101062
Source: IEEE Xplore

ABSTRACT 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.

0 Bookmarks
 · 
56 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Currently, many practical SWC systems are implemented using the low-density parity-check (LDPC) codes in which the virtual correlation channel between source and side information is modeled as a binary symmetric channel (BSC) characterized by the crossover probability. This paper is contributed to the estimation of crossover probability through the probability mass function (PMF) of the magnitudes of loglikelihood ratio (LLR) messages. Simulation results are given to verify our proposed method.
    IEEE Communications Letters 01/2009; 13:37-39. · 1.16 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we review recent developments concerning the application of low- density parity-check (LDPC) codes to the Gilbert-Elliott (GE) channel. Firstly, we discuss the analysis of LDPC estimation-decoding in these channels using density evolution. We show that the required conditions of density evolution are satisfied in the GE channel, and that analysis demonstrates that large potential gains over the memoryless assumption. We also give results which mitigate the complexity of characterizing the GE parameter space using DE. Subsequently, we give a design tool for finding good degree sequences for irregular LDPC codes in the GE channel. The degree sequences obtained using this technique are the best available codes for the GE channel.
    11/2003;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We show how low-density parity-check (LDPC) codes can be used to compress close to the Slepian-Wolf limit for correlated binary sources. Focusing on the asymmetric case of compression of an equiprobable memoryless binary source with side information at the decoder, the approach is based on viewing the correlation as a channel and applying the syndrome concept. The encoding and decoding procedures are explained in detail. The performance achieved is seen to be better than recently published results using turbo codes and very close to the Slepian-Wolf limit.
    IEEE Communications Letters 11/2002; · 1.16 Impact Factor