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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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Journal ArticleDOI
TL;DR: A generalized VA (GVA) is proposed that makes comparisons on the basis of a label of length L(L\leq K) that decoding theorems for a discrete memoryless channel are proved for GVA decoding and shown to be natural generalizations of those for VA decoding.
Abstract: The Viterbi algorithm (VA), an optimum decoding rule for a Q -ary trellis code of constraint length K , operates by taking the best survivor from each of Q^{K-1} lists of candidates at each decoding step. A generalized VA (GVA) is proposed that makes comparisons on the basis of a label of length L(L\leq K) . It selects, incorporating the notion of list decoding, the S best survivors from each of Q^{L-1} lists of candidates at each decoding step. Coding theorems for a discrete memoryless channel are proved for GVA decoding and shown to be natural generalizations of those for VA decoding. An example of intersymbol interference removal is given to illustrate the practical benefits that the GVA can provide.

155 citations

Journal ArticleDOI
Thomas Richardson1
TL;DR: The geometric perspective clearly indicates the relationship between turbo-decoding and maximum-likelihood decoding, and analysis of the geometry leads to new results concerning existence of fixed points, condition for uniqueness, conditions for stability, and proximity to maximum- likelihood decoding.
Abstract: The spectacular performance offered by turbo codes sparked intense interest in them. A considerable amount of research has simplified, formalized, and extended the ideas inherent in the original turbo code construction. Nevertheless, the nature of the relatively simple ad hoc turbo-decoding algorithm has remained something of a mystery. We present a geometric interpretation of the turbo-decoding algorithm. The geometric perspective clearly indicates the relationship between turbo-decoding and maximum-likelihood decoding. Analysis of the geometry leads to new results concerning existence of fixed points, conditions for uniqueness, conditions for stability, and proximity to maximum-likelihood decoding.

154 citations

Proceedings ArticleDOI
25 Nov 2001
TL;DR: Two decoding schedules and the corresponding serialized architectures for low-density parity-check (LDPC) decoders are presented and the performance of these decoding schedules is evaluated through simulations on a magnetic recording channel.
Abstract: Two decoding schedules and the corresponding serialized architectures for low-density parity-check (LDPC) decoders are presented. They are applied to codes with parity-check matrices generated either randomly or using geometric properties of elements in Galois fields. Both decoding schedules have low computational requirements. The original concurrent decoding schedule has a large storage requirement that is dependent on the total number of edges in the underlying bipartite graph, while a new, staggered decoding schedule which uses an approximation of the belief propagation, has a reduced memory requirement that is dependent only on the number of bits in the block. The performance of these decoding schedules is evaluated through simulations on a magnetic recording channel.

154 citations

Journal ArticleDOI
TL;DR: Simulation results show that this method provides significant gain over hard decision decoding and is superior to some other popular soft decision methods for short RS codes.
Abstract: This letter presents an iterative decoding method for Reed-Solomon (RS) codes. The proposed algorithm is a stochastic shifting based iterative decoding (SSID) algorithm which takes advantage of the cyclic structure of RS codes. The performances of different updating schemes are compared. Simulation results show that this method provides significant gain over hard decision decoding and is superior to some other popular soft decision methods for short RS codes.

152 citations

Journal ArticleDOI
TL;DR: Simulation results show that for all RM codes of length 256 and many subcodes of length 512, these algorithms approach maximum-likelihood (ML) performance within a margin of 0.1 dB.
Abstract: Recursive list decoding is considered for Reed-Muller (RM) codes. The algorithm repeatedly relegates itself to the shorter RM codes by recalculating the posterior probabilities of their symbols. Intermediate decodings are only performed when these recalculations reach the trivial RM codes. In turn, the updated lists of most plausible codewords are used in subsequent decodings. The algorithm is further improved by using permutation techniques on code positions and by eliminating the most error-prone information bits. Simulation results show that for all RM codes of length 256 and many subcodes of length 512, these algorithms approach maximum-likelihood (ML) performance within a margin of 0.1 dB. As a result, we present tight experimental bounds on ML performance for these codes

152 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202384
2022153
202179
202078
201982
201894