Topic
List decoding
About: List decoding is a research topic. Over the lifetime, 7251 publications have been published within this topic receiving 151182 citations.
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06 Dec 2004
TL;DR: The previously devised irregular partitioned permutation LDPC codes have a construction that easily accommodates a layered decoding and it is shown that the decoding performance is improved by a factor of two in the number of iterations required.
Abstract: We apply layered belief propagation decoding to our previously devised irregular partitioned permutation LDPC codes These codes have a construction that easily accommodates a layered decoding and we show that the decoding performance is improved by a factor of two in the number of iterations required We show how our previous flexible decoding architecture can be adapted to facilitate layered decoding This results in a significant reduction in the number of memory bits and memory instances required, in the range of 45-50% The faster decoding speed means the decoder logic can also be reduced by nearly 50% to achieve the same throughput and error performance In total, the overall decoder architecture can be reduced by nearly 50%
628 citations
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614 citations
TL;DR: A new distance measure is introduced which permits likelihood information to be used in algebraic minimum distance decoding techniques and an efficient decoding algorithm is given, and exponential bounds on the probability of not decoding correctly are developed.
Abstract: We introduce a new distance measure which permits likelihood information to be used in algebraic minimum distance decoding techniques. We give an efficient decoding algorithm, and develop exponential bounds on the probability of not decoding correctly. In one application, this technique yields the same probability of error as maximum likelihood decoding.
614 citations
TL;DR: It is shown that soft decision maximum likelihood decoding of any (n,k) linear block code over GF(q) can be accomplished using the Viterbi algorithm applied to a trellis with no more than q^{(n-k)} states.
Abstract: It is shown that soft decision maximum likelihood decoding of any (n,k) linear block code over GF(q) can be accomplished using the Viterbi algorithm applied to a trellis with no more than q^{(n-k)} states. For cyclic codes, the trellis is periodic. When this technique is applied to the decoding of product codes, the number of states in the trellis can be much fewer than q^{n-k} . For a binary (n,n - 1) single parity check code, the Viterbi algorithm is equivalent to the Wagner decoding algorithm.
612 citations
TL;DR: This letter describes the SISO APP module that updates the APP corresponding to the input and the output bits, of a code, and shows how to embed it into an iterative decoder for a new hybrid concatenation of three codes, to fully exploit the benefits of the proposed S ISO APP module.
Abstract: Concatenated coding schemes consist of the combination of two or more simple constituent encoders and interleavers. The parallel concatenation known as "turbo code" has been shown to yield remarkable coding gains close to theoretical limits, yet admitting a relatively simple iterative decoding technique. The recently proposed serial concatenation of interleaved codes may offer superior performance to that of turbo codes. In both coding schemes, the core of the iterative decoding structure is a soft-input soft-output (SISO) a posteriori probability (APP) module. In this letter, we describe the SISO APP module that updates the APP's corresponding to the input and the output bits, of a code, and show how to embed it into an iterative decoder for a new hybrid concatenation of three codes, to fully exploit the benefits of the proposed SISO APP module.
609 citations