2,920 research outputs found
On the Performance of Lossless Joint Source-Channel Coding Based on Linear Codes
A general lossless joint source-channel coding scheme based on linear codes
is proposed and then analyzed in this paper. It is shown that a linear code
with good joint spectrum can be used to establish limit-approaching joint
source-channel coding schemes for arbitrary sources and channels, where the
joint spectrum of the code is a generalization of the input-output weight
distribution.Comment: To appear in Proc. 2006 IEEE Information Theory Workshop, October
22-26, 2006, Chengdu, China. (5 pages, 2 figures
Linear-Codes-Based Lossless Joint Source-Channel Coding for Multiple-Access Channels
A general lossless joint source-channel coding (JSCC) scheme based on linear
codes and random interleavers for multiple-access channels (MACs) is presented
and then analyzed in this paper. By the information-spectrum approach and the
code-spectrum approach, it is shown that a linear code with a good joint
spectrum can be used to establish limit-approaching lossless JSCC schemes for
correlated general sources and general MACs, where the joint spectrum is a
generalization of the input-output weight distribution. Some properties of
linear codes with good joint spectra are investigated. A formula on the
"distance" property of linear codes with good joint spectra is derived, based
on which, it is further proved that, the rate of any systematic codes with good
joint spectra cannot be larger than the reciprocal of the corresponding
alphabet cardinality, and any sparse generator matrices cannot yield linear
codes with good joint spectra. The problem of designing arbitrary rate coding
schemes is also discussed. A novel idea called "generalized puncturing" is
proposed, which makes it possible that one good low-rate linear code is enough
for the design of coding schemes with multiple rates. Finally, various coding
problems of MACs are reviewed in a unified framework established by the
code-spectrum approach, under which, criteria and candidates of good linear
codes in terms of spectrum requirements for such problems are clearly
presented.Comment: 18 pages, 3 figure
Network vector quantization
We present an algorithm for designing locally optimal vector quantizers for general networks. We discuss the algorithm's implementation and compare the performance of the resulting "network vector quantizers" to traditional vector quantizers (VQs) and to rate-distortion (R-D) bounds where available. While some special cases of network codes (e.g., multiresolution (MR) and multiple description (MD) codes) have been studied in the literature, we here present a unifying approach that both includes these existing solutions as special cases and provides solutions to previously unsolved examples
Low-Complexity Approaches to Slepian–Wolf Near-Lossless Distributed Data Compression
This paper discusses the Slepian–Wolf problem of distributed near-lossless compression of correlated sources. We introduce practical new tools for communicating at all rates in the achievable region. The technique employs a simple “source-splitting” strategy that does not require common sources of randomness at the encoders and decoders. This approach allows for pipelined encoding and decoding so that the system operates with the complexity of a single user encoder and decoder. Moreover, when this splitting approach is used in conjunction with iterative decoding methods, it produces a significant simplification of the decoding process. We demonstrate this approach for synthetically generated data. Finally, we consider the Slepian–Wolf problem when linear codes are used as syndrome-formers and consider a linear programming relaxation to maximum-likelihood (ML) sequence decoding. We note that the fractional vertices of the relaxed polytope compete with the optimal solution in a manner analogous to that observed when the “min-sum” iterative decoding algorithm is applied. This relaxation exhibits the ML-certificate property: if an integral solution is found, it is the ML solution. For symmetric binary joint distributions, we show that selecting easily constructable “expander”-style low-density parity check codes (LDPCs) as syndrome-formers admits a positive error exponent and therefore provably good performance
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