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A simple proof of threshold saturation for coupled scalar recursions
- in Proc. Intl. Symp. on Turbo Codes and Iter. Inform. Proc. (ISTC), 2012
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Universal codes for the gaussian mac via spatial coupling
- in Proc. 49th Ann. Allerton Conf. Comm. Control Comput
"... Abstract—We consider transmission of two independent and separately encoded sources over a two-user binary-input Gaus-sian multiple-access channel. The channel gains are assumed to be unknown at the transmitter and the goal is to design an encoder-decoder pair that achieves reliable communication fo ..."
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Cited by 8 (2 self)
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Abstract—We consider transmission of two independent and separately encoded sources over a two-user binary-input Gaus-sian multiple-access channel. The channel gains are assumed to be unknown at the transmitter and the goal is to design an encoder-decoder pair that achieves reliable communication for all channel gains where this is theoretically possible. We call such a system universal with respect to the channel gains. Kudekar et al. recently showed that terminated low-density parity-check convolutional codes (a.k.a. spatially-coupled low-density parity-check ensembles) have belief-propagation thresh-olds that approach their maximum a-posteriori thresholds. This was proven for binary erasure channels and shown empirically for binary memoryless symmetric channels. It was conjectured that the principle of spatial coupling is very general and the phenomenon of threshold saturation applies to a very broad class of graphical models. In this work, we derive an area theorem for the joint decoder and empirically show that threshold saturation occurs for this problem. As a result, we demonstrate near-universal performance for this problem using the proposed spatially-coupled coding system. Index Terms—Gaussian MAC, LDPC codes, spatial coupling, EXIT functions, density evolution, joint decoding, protograph, area theorem. I.
Performance improvement of iterative multiuser detection for large sparsely-spread CDMA systems by spatial coupling,” submitted to
- IEEE Trans. Inf. Theory, 2012, [Online]. Available
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New Codes on Graphs Constructed by Connecting Spatially Coupled Chains
, 2013
"... A novel code construction based on spatially coupled low-density parity-check (SC-LDPC) codes is presented. The proposed code ensembles are described by protographs, comprised of several protograph-based chains characterizing individual SC-LDPC codes. We demonstrate that code ensembles obtained by c ..."
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Cited by 2 (1 self)
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A novel code construction based on spatially coupled low-density parity-check (SC-LDPC) codes is presented. The proposed code ensembles are described by protographs, comprised of several protograph-based chains characterizing individual SC-LDPC codes. We demonstrate that code ensembles obtained by connecting appropriately chosen SC-LDPC code chains at specific points have improved iterative decoding thresholds compared to those of single SC-LDPC coupled chains. In addition, it is shown that the improved decoding properties of the connected ensembles result in reduced decoding complexity required to achieve a specific bit error probability. The constructed ensembles are also asymptotically good, in the sense that the minimum distance grows linearly with the block length. Finally, we show that the improved asymptotic properties of the connected chain ensembles also translate into improved finite length performance.
Threshold Saturation for Spatially-Coupled LDPC and LDGM Codes on BMS Channels
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1Adaptive Slepian-Wolf Decoding Based On Expectation Propagation
"... Abstract—A major difficulty that plagues the practical use of Slepian-Wolf (SW) coding (and distributed source coding in general) is that the precise correlation among sources needs to be known a priori. However, belief propagation (BP) algorithm cannot adapt efficiently to the statistical change of ..."
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Abstract—A major difficulty that plagues the practical use of Slepian-Wolf (SW) coding (and distributed source coding in general) is that the precise correlation among sources needs to be known a priori. However, belief propagation (BP) algorithm cannot adapt efficiently to the statistical change of the correlation. This paper proposes an adaptive SW decoding scheme which can perform online time-varying correlation estimation at the bit-level by incorporating expectation propagation (EP) algorithm. More-over, we compare the proposed EP-based approach with Monte Carlo method using particle filtering (PF) algorithm. Our results show that the proposed EP estimator obtains the comparable estimation accuracy with less computational complexity than the PF method. Index Terms—Adaptive decoding, Distributed algorithms, Source coding, Data compression
