AN APPROXIMATION OF VARIABLE NODE LAYERING FOR DECODING LDPC CODES

摘要

Low Density Parity Check (LDPC) code approaches Shannon limit performance for binary field and long code lengths when decoded with the belief-propagation (BP) or the Sum-Product algorithm. However, performance of binary LDPC code is degraded when the code word length is small. Layered decoding is known to provide efficient and high-throughput implementation of LDPC decoders. The Variable-Node Layered Belief Propagation (VL-BP) algorithm is a modification of Belief Propagation algorithm (BP), where the varible nodes are divided in subgroups called layers and each iteration is broken into multiple sub-iterations. Min-Sum VL-BP (MS VL-BP) algorithm is an approximation of the VL-BP algorithm since the check node update is replaced by a selection of the minimum input value. An optimized MS VL-BP algorithm for LDPC code is proposed in this paper. In this algorithm, unlike other decoding methods, we consider for the first layer a set of variable nodes that has a low value of the intrinsic information. An optimization factor is introduced in check node update rule for each sub-iterations of the proposed algorithm. Simulation results show that the proposed Optimized MS VL-BP decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum VL-BP decoding, that is low complexity and independence with respect to noise variance estimation errors.