Reduced-complexity MPA decoder based on multi-level dynamic input thresholds

As a key technology of the fifth generation （5G） wireless communications, sparse code multiple access （SCMA） system has quite high frequency utilization, but its message passing algorithm （MPA） decoder still has high time complexity. By the aid of the proposed multi-level dynamic threshold, the complexity of the MPA decoding can be greatly reduced with little error performance loss. In order to reduce a great deal of insignificant computational amounts of message update, we compare the multi-level symbols probability products with optimized multi-level thresholds step by step before they are used for message update calculation. The dynamic threshold configuration refers to the three factors： the level of input symbol probabilities, signal noise ratio （SNP.） and the number of iterations. Especially, in the joint iterative MPA-Turbo decoding procedure, since most encoded bits have good convergence, the inp^t thresholds can avoid more unnecessary computational overhead of message update and reduce the decoding time more significantly. The simulation results show that the proposed multi-level dynamic thresholds considerably reduce the decoding delay in both additive white Gaussian noise （AWGN） channel and frequency selective fading channel.