Min-sum decoding algorithm of LDPC codes based on integer quantisation

Low-density parity-check (LDPC) codes become popular for its near Shannon limit performance and relatively simple decoding structure. The min-sum decoding algorithm of LDPC codes is studied detailedly. And the variable message and check message of each iteration become integers through a variety of methods quantifying the initial message. Then the integer arithmetic based on the min-sum decoding algorithm is realized. Finally, these algorithms are compared and analyzed. Simulation results show that all variables of the min-sum decoding algorithm are fixed length integers after quantification. It is easy for hardware implementation. And the decoding time is greatly shortened under the condition that the decoding performance degrades less than the sum-product (SP) decoding. The greater the average mutual information of the quantitative method is, the better the quantized level will be. The min-sum decoding algorithm of the maximum average mutual information quantization has the best performance. The maximum average mutual information quantization is the best quantitative method to keep the source information as much as possible, and it does not increase the complexity of decoding.