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IEEE 5G World Forum (5GWF)

A sectional degree match approximate Min-sum decoding algorithm for LDPC

Ruizhen Wu, Lin Wang, Tao Yuan, Hua Feng

Published Sep 1, 2019• 0 citations
Publisher

Abstract

A sectional degree match approximate Min-sum decoding algorithm for LDPC is proposed in this paper. The degradation factor from BP to MS is analyzed and a proposal to offset it, is explained, with expansion and optimization based on principles of hardware implementation. The decoding algorithm summarizes three correction approximate algorithms considering different LLR values, matrix degrees and rules of hardware implementation. Simulation is following LDPC NR 3GPP 38.212 release and the comparison results demonstrate that the proposed sectional degree match approximate Min-sum decoding algorithm has a better BER and less iteration time. The hardware implementation of this algorithm is strived from Min-Sum decoder and the extra cost is minor besides the memory.

DOI
10.1109/5gwf.2019.8911623

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In this paper a modified Offset Min-Sum decoding algorithm for Low-Density Parity Check Codes is presented. In this modified algorithm, the offset factor in the original Offset Min-Sum algorithm is adjusted iteratively with the assistance of the check-node computation outputs of the Normalized Min-Sum algorithm. As a result, the offset factor in our modified algorithm can be calculated adaptively and more efficiently according to the previous decoding procedure, which can minimize the decoding degradation compared with the Belief Propagation decoding algorithm. The simulation results show that, compared with the original Offset Min-Sum decoding algorithm, our modified algorithm can achieve noticeable performance improvement with minor extra hardware complexity. For example, when BER is 10−5, our algorithm can achieve 0.1dB and 0.2dB decoding gain over Offset Min-Sum algorithm for regular and irregular LDPC codes respectively.
Min-sum algorithm(MSA) and its modification are used in LDPC decoder implementations because of its error performance and low computation complexity. In this paper a modified min-sum LDPC decoding algorithm through approximation enhancement using the smallest three minimum values is presented. The proposed algorithm improves error performance and reduces decoder iterations. From the simulation results for 5G NR LDPC codes, we show that the proposed algorithm can achieve about 1.6dB improvement of FER compared to the min-sum decoding algorithm and provide about 10% reduction of the average iteration numbers compare to NMSA with optimum normalization factor.
A check node degree-based modified min-sum algorithm which classifies the codes was developed to reduce the complexity and improve the performance of decoding algorithm for low-density parity-check(LDPC) codes.The algorithm corrects both the minimum and sub-minimum absolute values of incoming messages in the check nodes.Two correction factors are obtained by calculating the offset between the belief propagation(BP) algorithm and the min-sum algorithm based on the check node degree.Simulations show that the algorithm achieves better performance than the BP algorithm at high signal noise ratio.The algorithm is also less complex than the BP algorithm and provides a good tradeoff between performance and complexity for any check node degree distribution in the LDPC codes.