Journal ArticleDOI
On the design of low-density parity-check codes within 0.0045 dB of the Shannon limit
TLDR
Improved algorithms are developed to construct good low-density parity-check codes that approach the Shannon limit very closely, especially for rate 1/2.Abstract:
We develop improved algorithms to construct good low-density parity-check codes that approach the Shannon limit very closely. For rate 1/2, the best code found has a threshold within 0.0045 dB of the Shannon limit of the binary-input additive white Gaussian noise channel. Simulation results with a somewhat simpler code show that we can achieve within 0.04 dB of the Shannon limit at a bit error rate of 10/sup -6/ using a block length of 10/sup 7/.read more
Citations
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Wireless communications
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Design of capacity-approaching irregular low-density parity-check codes
TL;DR: This work designs low-density parity-check codes that perform at rates extremely close to the Shannon capacity and proves a stability condition which implies an upper bound on the fraction of errors that a belief-propagation decoder can correct when applied to a code induced from a bipartite graph with a given degree distribution.
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Convergence behavior of iteratively decoded parallel concatenated codes
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Regular and irregular progressive edge-growth tanner graphs
TL;DR: Simulation results show that the PEG algorithm is a powerful algorithm to generate good short-block-length LDPC codes.
References
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Book
Low-Density Parity-Check Codes
TL;DR: A simple but nonoptimum decoding scheme operating directly from the channel a posteriori probabilities is described and the probability of error using this decoder on a binary symmetric channel is shown to decrease at least exponentially with a root of the block length.
Proceedings ArticleDOI
Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1
TL;DR: In this article, a new class of convolutional codes called turbo-codes, whose performances in terms of bit error rate (BER) are close to the Shannon limit, is discussed.
Journal ArticleDOI
Good error-correcting codes based on very sparse matrices
TL;DR: It is proved that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit, and experimental results for binary-symmetric channels and Gaussian channels demonstrate that practical performance substantially better than that of standard convolutional and concatenated codes can be achieved.
Journal ArticleDOI
Design of capacity-approaching irregular low-density parity-check codes
TL;DR: This work designs low-density parity-check codes that perform at rates extremely close to the Shannon capacity and proves a stability condition which implies an upper bound on the fraction of errors that a belief-propagation decoder can correct when applied to a code induced from a bipartite graph with a given degree distribution.