一种低迭代次数的极化码置信传播译码算法

针对置信传播（Belief Propagation，BP）译码算法在迭代次数较多时吞吐量和译码时延性能提升受限的问题，提出了一种低迭代次数的极化码BP译码算法，通过采用比特翻转和子信道冻结的方式，降低译码过程中的迭代次数。仿真结果表明，相对于传统极化码BP译码算法（设置最大迭代次数为40次），所提算法在信噪比为3 dB时可将平均迭代次数减少约53%，处理单元平均计算次数减少约68%。该算法所带来的低时延和低功耗效益可运用在对功耗要求较高的大规模机器类型通信，以及对时延要求较高的超可靠低延迟通信等5G场景下的极化码译码中。

A Low-iteration BP Polar Code Decoding Algorithm

For the problem that the throughput and decoding delay performance of the belief propagation(BP) decoding algorithm are limited in the condition of a large number of iterations,a low-iteration BP polar code decoding algorithm is proposed to reduce the number of iterations in the decoding process by bit flipping and sub-channel freezing.Simulation results show that,when the signal-to-noise ratio(SNR) is 3 dB,compared with that of the traditional polar codes BP decoding algorithm(the maximum number of iterations is 40),the average number of iterations is reduced by about 53%,and the average calculative number of processing elements is reduced by about 68%.This algorithm can be applied to polar codes decoding in 5G scenarios such as massive machine type of communication(mMTC) that requires higher power consumption and ultra-reliable low latency communications(uRLLC) that requires lower delay.