Performance Analysis of Algebraic Soft-Decision Decoding of Reed-Solomon Codes

Abstract

We investigate the decoding region for Algebraic Soft-Decision Decoding (ASD) of Reed-Solomon codes in a discrete, memoryless, additive-noise channel. An expression is derived for the error correction radius within which the soft-decision decoder produces a list that contains the transmitted codeword. The error radius for ASD is shown to be larger than that of Guruswami-Sudan hard-decision decoding for a subset of low-rate codes. These results are also extended to multivariable interpolation in the sense of Parvaresh and Vardy. An upper bound is then presented for ASD's probability of error, where an error is defined as the event that the decoder selects an erroneous codeword from its list. This new definition gives a more accurate bound on the probability of error of ASD than the results available in the literature.