Variable Correction for Min-Sum LDPC Decoding Applied in ATSC3.0

Abstract

Min-sum (MS) algorithm is a low-complexity approximation of belief propagation (BP) algorithm, but has a severe decline in decoding performance. To reduce this degradation, Normalized min-sum (NMS) algorithm and offset min-sun (OMS) algorithm of a fixed correction factor were proposed. In the literature, extensive empirical results have been provided on NMS and OMS for ATSC 3.0 LDPC codes. It indicates that NMS is approaching BP's performance, though NMS may have error floors for some codes. Meanwhile, OMS have better performance than NMS in most cases under perfect estimation assumptions. However, in real cases, due to OMS's sensitivity to channel estimation which is imperfect, it suffers from performance loss. In this paper, the variable correction MS (VCMS) algorithm is introduced, based on which we run extensive simulations for all ATSC 3.0 LDPC codes. Results of frame error rate show that VCMS algorithm not only has a noticeable gain in waterfall region over NMS, but can also eliminate any possible error floors occurred. This algorithm is also better than OMS in many cases. Although in some cases OMS seems to be a little bit better than the VCMS, the VCMS is not sensitive to the imperfect channel estimation. The study of this paper aims to give more options and advice for the implementation of the ATSC 3.0 LDPC decoders.