Error rate estimation of finite-length low-density parity-check codes decoded by soft-decision iterative algorithms

This paper describes a combinatorial approach to estimate the error rate performance of low-density parity-check (LDPC) codes decoded by (quantized) soft-decision iterative decoding algorithms. The method is based on efficient enumeration of input vectors with small distances to a reference vector whose elements are selected to be the most reliable values from the input alphabet. Several techniques, including modified cycle enumeration, are employed to reduce the complexity of the enumeration. The error rate estimate is derived by testing the input vectors of small distances and estimating the contribution of larger distance vectors. We demonstrate by a number of examples that the proposed method provides accurate estimates of error rate with computational complexity much lower than that of Monte Carlo simulations, especially at the error floor region.

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