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IEEE Transactions on Communications

Constrained designs for maximum likelihood soft decoding of RM(2,m) and the extended Golay codes

Moshe Ran, Jakov Snyders

Published Feb 1, 1995• 16 citations
Publisher

Abstract

We present algorithms for maximum likelihood soft decoding of the second order Reed-Muller codes RM(2,m) and the extended (24,12,8) Golay code. The decoding procedures are based on a concise representation of appropriately selected cosets of a subcode of the code considered. Such representation enables application of certain elimination rules. A structure, called constrained design, is established to support the elimination procedures. Remarkably efficient algorithms are obtainable by this approach. The method of elimination is applicable also in combination with existing coset decoding schemes.>

DOI
10.1109/26.380113

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Constructs Reed-Muller codes by generalized multiple concatenation of binary block codes of length 2. As a consequence of this construction, a new decoding procedure is derived that uses soft-decision information. The algorithm is designed for low decoding complexity and is applicable to all Reed-Muller codes. It gives better decoding performance than soft-decision bounded-distance decoding. Its decoding complexity is much lower than that of maximum-likelihood trellis decoding of Reed-Muller codes, especially for long codes.>

IEEE Transactions on Information Theory•Jan 1, 1995•90 citations
We present algorithms for maximum likelihood soft decoding of the second order Reed-Muller codes RM(2,m) and the extended (24,12,8) Golay code. The decoding procedures are based on a concise representation of appropriately selected cosets of a subcode of the code considered. Such representation enables application of certain elimination rules. A structure, called constrained design, is established to support the elimination procedures. Remarkably efficient algorithms are obtainable by this approach. The method of elimination is applicable also in combination with existing coset decoding schemes.>
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.
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
Maximum-likelihood soft-decision decoding of linear block codes is addressed. A binary multiple-check generalization of the Wagner rule is presented, and two methods for its implementation, one of which resembles the suboptimal Forney-Chase algorithms, are described. Besides efficient soft decoding of small codes, the generalized rule enables utilization of subspaces of a wide variety, thereby yielding maximum-likelihood decoders with substantially reduced computational complexity for some larger binary codes. More sophisticated choice and exploitation of the structure of both a subspace and the coset representatives are demonstrated for the (24, 12) Golay code, yielding a computational gain factor of about 2 with respect to previous methods. A ternary single-check version of the Wagner rule is applied for efficient soft decoding of the (12, 6) ternary Golay code.>
A soft-input sequential decoder for Reed-Muller (RM) codes of length2m2^{m}2mand orderm−3m-3m−3is proposed. The considered algorithm sequentially processes different permuted versions of the received vector using a decoder of an extended Hamming code, with permutations being selected on-the-fly from the RM codes' automorphism group based on soft information from a channel. It is shown that the proposed algorithm outperforms the recursive list decoder with similar computational complexity and achieves near maximum-likelihood decoding performance with reasonable computational complexity for RM codes of length 512 and 1024.
Reed-Muller (RM) codes are classical codes that have enjoyed unabated interest since their introduction in 1954 due to their simple recursive structure and low-complexity decoding. The main goal of the thesis is to develop new coding techniques that can improve the performance of RM codes. In this work, we wish to keep the recursive low-complexity structure of RM codes while extending the sets of possible parameters and decoding algorithms. We address this task using two different methods. First, we consider new code constructions that extend code parameters using puncturing. Second, we design new decoding algorithms that repeatedly use the gradient properties of the classic recursive structure to improve code performance of RM codes. In the first part of the thesis, we propose a new class of codes that enjoy the recursive structure of RM codes, but reduce the exponential length of RM codes to a polynomial in m. These codes are obtained by puncturing classical RM codes, i.e. by restricting binary RM codes to small subsets of their positions. We study new recursive properties of these codes and analyze their parameters. In the second part of the thesis we develop new decoding algorithms for binary RM codes of second order that achieve near optimal performance for short and moderate code lengths. RM codes enjoy some simple decoding procedures; however, these algorithms fall short of optimal performance on moderate block lengths. We propose a suboptimal algorithm that reduces the complexity of maximum-likelihood decoding from super-polynomial order O(n(m+1)/2) to polynomial order O(mn2). At the same time, our numerical simulations show that the new algorithm performs very closely to its maximum-likelihood counterpart for blocks of up to several thousand bits.
Constructs Reed-Muller codes by generalized multiple concatenation of binary block codes of length 2. As a consequence of this construction, a new decoding procedure is derived that uses soft-decision information. The algorithm is designed for low decoding complexity and is applicable to all Reed-Muller codes. It gives better decoding performance than soft-decision bounded-distance decoding. Its decoding complexity is much lower than that of maximum-likelihood trellis decoding of Reed-Muller codes, especially for long codes.>