Intelligent Dynamic Scheduling-Based Extended Min-Sum LDPC Decoding Algorithm in Cyber-Physical Systems

With the construction process of smart cities, cyber-physical systems (CPS) are going to become a link to connect all things with intelligence. The low-density parity check (LDPC) code is an import information encryption format in computer networks. In this article, from the perspective of LDPC code decoding algorithm scheduling strategy, we design a dynamic check node scheduling (DCNS) strategy for extended min-sum LDPC decoding in cyber-physical systems. In this strategy, the reliability of the node is checked to determine whether to update. For the un-updated variable node, it is optimized according to the results of real-time scheduling. Compared with the flooding mechanism and LBP scheduling of the usual algorithms, this proposed scheduling strategy improves the error correction performance by selecting some nodes for decoding and performing message optimization, while not significantly increasing the decoding computation. Especially, compared with the LBP, the bit error rate and frame error rate of the proposed algorithm are reduced by 48.3% and 53.2% on average in the finite domain 64F range. Compared with BP, the bit error rate and frame error rate of the proposed algorithm are reduced by 11.3% and 13.2% on average in the finite domain 64F range.