A New MAP-based Algorithm to Reduce the Complexity of Turbo Decoder

In this paper we investigate turbo decoding based on maximum a posteriori algorithm (MAP). A new reduced complexity scheme of turbo decoder is proposed in which we apply some modifications to the original MAP-based turbo decoder. The basic idea in the proposed method is to derive a simplified trellis at the end of each iteration, based on the information about transmitted symbols obtained in that iteration. The performance of convolutional turbo codes over additive white Gaussian noise (AWGN) channel using the proposed decoding algorithm is evaluated. Simulation results reveal that the proposed decoding algorithm reduces the computational complexity of the system and has negligible bit-error rate (BER) degradation in comparison with the full-search MAP-based decoding algorithm.