一种低复杂度Turbo乘积码自适应Chase译码算法

针对Turbo乘积码(Turbo Product Codes, TPCs)中的译码问题，该文提出一种全新的低复杂度TPC自适应Chase迭代译码算法。与已有的报道不同，在译码过程中，新算法首先统计TPC码块内每一行(列)产生的代数译码后的备选序列与接收序列的相同最小欧氏距离的个数，然后根据统计结果，按照算法步骤调整译码所需的不可靠位数值。通过Monte Carlo仿真可验证，当TPC行列编码采用相同的扩展汉明码，且编码效率为0.879时，该算法与Pyndiah采用固定不可靠位数值迭代译码算法相比，在误码率BER为10-4处仅损失约0.08 dB的性能，但是译码平均复杂度降低可达到约40.4%。

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%.