Optimization of a reduced-complexity decoding algorithm for LDPC codes by density evolution

In this paper, an algorithm for Low-Density Parity-Check (LDPC) codes with reduced complexity is presented. The complexity reduction is achieved by calculating a linear function for updating the check nodes in each iteration, instead of an exponential and logarithmic function. The, parameters of the linear function are optimized by density evolution. Simulation results show that there is nearly no loss in the performance by using this approximation compared to the exact calculation of the belief propagation decoding algorithm, even for very large block lengths.