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IEEE Convention of Electrical and Electronics Engineers in Israel

A lower bound on the probability of decoding error over a BSC channel

Osnat Keren, Simon N. Litsyn

Published Nov 11, 2002• 7 citations
Publisher

Abstract

For a code C of length n and size |C, we estimate the error probability of the maximum likelihood decoding. In this paper we address this problem for the binary symmetric channel (BSC) defined by its transition probability p. We discuss the case when we know the distance distribution of the code. We also assume that the code is regular in the sense that the distribution of the distances from a codeword to other codewords does not depend on the choice of the initial codeword.

DOI
10.1109/eeei.2000.924389

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For a code C of length n and size |C, we estimate the error probability of the maximum likelihood decoding. In this paper we address this problem for the binary symmetric channel (BSC) defined by its transition probability p. We discuss the case when we know the distance distribution of the code. We also assume that the code is regular in the sense that the distribution of the distances from a codeword to other codewords does not depend on the choice of the initial codeword.
An efficient algorithm for calculating the ith bit error probability of a binary linear code over the binary symmetric channel (BSC) is presented. It is proved that the exact ith bit error probability of maximum-likelihood (ML) decoding, bounded distance decoding, and symbol-wise maximum a posteriori probability (MAP) decoding can be obtained with time complexity O(n2/sup n-k/), where n and k denote the length and the dimension of the target code. The proposed methods are applicable to any binary linear code with redundancy up to nearly 25-30 bits with a typical personal computer.
A lower bound on the error rate of linear binary block codes(under maximum likelihood decoding) over BSC channels is proposed.According to the principle of the maximum likelihood(ML) decoding algorithm,the decoding error probability is firstly converted into the joint probability of the error events,and the judge rule of the redundant error events is deduced based on the optimization rule of the improved Dawson-Sankoff bound.Moreover,the calculation expression about lower bound of the error probability solely depends on the Hamming weight enumerator function of the code and the crossover probability of the channel.The simulation results applying to various LDPC codes show that the new lower bound outperforms those generic lower bounds and the sphere packing bound.Its computational complexity is also lower.
Abstract The error exponent of the regular graph-based binary low-density parity-check (LDPC) codes under the maximum likelihood (ML) decoding algorithm in the binary symmetric channel (BSC) is analyzed. Unlike most other papers where error exponents are considered for the case when the length of LDPC codes tends to infinity (asymptotic analysis), the finite length case (finite length analysis) is considered. In this paper, a method of deriving the lower bound on the error exponent for a regular graph-based LDPC code with finite length under ML decoding is described. Also we analyze Dependences of the error exponent on various LDPC code parameters are also analyzed. The numerical results obtained for the considered lower bound are represented and analyzed at the end of the paper.