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International Conference on Electronic Information Engineering and Computer Science (EIECS)

A Multivariate LDPC Decoding Simplification Method and Performance Simulation Analysis

Xiaojun Wang, Yang Cao

Published Sep 22, 2023• 2 citations

Abstract

Aiming at the problem of large computation and high decoding complexity when updating the check node in the LLR-BP algorithm of multicode LDPC code, a simplified method of dimensionality reduction in accordance with the weights is proposed, in which the q-dimensional likelihood ratio information of a variable node is descending-ordered and a weight is set for each dimension of the node, and the dimensional information of two variable nodes will be summed up according to the weight value size set in the process of updating check node. The size of the weight value will be added according to the set rule, which effectively reduces the wasted addition operation resources on the low likelihood ratio information. The simplified algorithm reduces about 90% of computation compared to the LLR-BP algorithm during one iteration of the algorithm. The BER performance simulation of the algorithm shows that the simplified decoding algorithm has only a very small difference in performance compared to the LLR-BP algorithm, and the overall decoding iteration speed is greatly improved.

DOI: 10.1109/eiecs59936.2023.10435463

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At present, Low-Density Parity-Check (LDPC) codes widely used in many fields of communications have the best performance of all the Error Correcting Codes (ECC). This paper mainly studies the decoding algorithms of LDPC. It proposes an improved algorithm which is named Check-Variable nodes Hybrid(CVH) algorithm on the basis of the existing algorithms. The CVH algorithm can reduce the computational complexity during the check-node update while overcome with the correlation between the variable-node news in a code with circles. As well as, comparing with the original algorithms the performance of the new one saves 0.1 and 0.3 dB than Log-likelihood Ratios (LLR) Belief Propagation (BP) and BP - based algorithms under Additive White Gaussian Noise (AWGN) channel when the Bit Error Rate (BER) falls to through the simulation. This point shows that this algorithm can increase the decoding performance and reduce the error rate effectively.