A Low-complexity Adaptive Chase Decoding Algorithm for Turbo Product Code

This paper proposes a novel and low-complexity adaptive Chase iterative decoding algorithm for Turbo Product Codes (TPCs). Different from the previous reported results, during decoding, the new adaptive algorithm is based on the statistics of the number of the candidate sequences with the same minimum squared Euclidean distance in each row or column of TPC block firstly, and then the Least Reliable Bits (LRBs) can change according to the statistical results via the proposed steps. It can be verified by Monte Carlo simulations, when using the same extended Hamming code as TPC subcodes with coding efficiency of 0.879 and the Bit Error Rate (BER) is 10-4, the coding loss of the proposed adaptive algorithm is just about 0.08 dB compared with Pyndiahs iterative decoding algorithm using the fixed LRBs parameter in Chase decoder, but the average complexity of the proposed algorithm could be reduced about 40.4%.