Maximum Average Mutual Information Quantisation of Low Density Parity Check Codes for Eight-Phase-Shift Keying Modulation

Abstract

Low density parity check (LDPC) codes enjoy the good properties of approaching the Shannon limit, and its practical application is of great significance. In this paper, the decoding algorithm of LDPC codes for eight-phase-shift keying modulation is particularly studied, and the specific methods of the maximum average mutual information quantisation are analysed and deduced. With this method to quantify the initial message, the variable messages and check messages are converted into integers when each iteration has been finished, and then the min-sum decoding algorithm based on integer arithmetic is implemented. Simulation results demonstrate that the performance of the min-sum decoding algorithm with maximum average mutual information quantisation is close to that of the high-precision floating-point sum-product decoding algorithm. Meanwhile, It is convenient for hardware implementation since all the variables in the algorithm are fixed-length integers. Although the bit error rate is slightly worse than that of the sum-product decoding algorithm, the decoding time consumption is greatly reduced.