53 research outputs found

    Combining the Burrows-Wheeler Transform and RCM-LDGM Codes for the Transmission of Sources with Memory at High Spectral Efficiencies

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    In this paper, we look at the problem of implementing high-throughput Joint SourceChannel (JSC) coding schemes for the transmission of binary sources with memory over AWGN channels. The sources are modeled either by a Markov chain (MC) or a hidden Markov model (HMM). We propose a coding scheme based on the Burrows-Wheeler Transform (BWT) and the parallel concatenation of Rate-Compatible Modulation and Low-Density Generator Matrix (RCM-LDGM) codes. The proposed scheme uses the BWT to convert the original source with memory into a set of independent non-uniform Discrete Memoryless (DMS) binary sources, which are then separately encoded, with optimal rates, using RCM-LDGM codes

    Rate-distortion performance for joint source and channel coding of images

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    Caption title.Includes bibliographical references (p. 31-32).Supported by the German Educational Exchange Service (DAAD) as part of the HSP II-program, and in part by ARPA. F30602-92-C-0030 Supported by the Laboratory for Information and Decision Systems, Massachusetts Institute of Technology. DAAH04-95-1-0103Michael J. Ruf, James W. Modestino

    Non-linear graph-based codes for joint source-channel coding

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    We study the behavior of a new family of nonlinear graph-based codes, previously introduced for compression of asymmetric binary memoryless sources, for the joint source-channel coding scenario in which the codewords are transmitted through an additive white Gaussian noise channel. We focus on low entropy sources (with high redundancy) and compression rates. Monte Carlo simulation and density evolution results show that the proposed family, with a regular and simple parametrization of the degree profiles, outperforms linear codes.Peer ReviewedPostprint (published version

    A simple one sweep algorithm for optimal APP symbol decoding of linear block codes

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    Soft-input/soft-output symbol decoding plays a significant role in iterative decoding. We propose a simple optimal soft-input/soft-output symbol decoding algorithm for linear block codes which requires one forward recursion using a trellis. For many codes the decoding complexity is lower than previous methods, such as the algorithm by Bahl et al. (1974), and the decrease is shown at its most when decoding Hamming codes

    Joint Design of Source-Channel Codes with Linear Source Encoding Complexity and Good Channel Thresholds Based on Double-Protograph LDPC Codes

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    We propose the use of a lower or upper triangular sub-base matrix to replace the identity matrix in the source-check-channel-variable linking protomatrix of a double-protograph low-density parity-check joint-source-channel code (DP-LDPC JSCC). The elements along the diagonal of the proposed lower or upper triangular sub-base matrix are assigned as "1" and the other non-zero elements can take any non-negative integral values. Compared with the traditional DP-LDPC JSCC designs, the new designs show a theoretical channel threshold improvement of up to 0.41 dB and a simulated source symbol error rate improvement of up to 0.5 dB at an error rate of 1e-6.Comment: 7 pages, 5 figures, 3 tables, to appear in IEEE Communications Letter
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