LT码的一种BP/ML混合译码算法

摘要

In order to eliminate the performance gap between the belief propagation (BP) decoding and the maximum-likelihood (ML) decoding for LT codes with small message length, the paper presents a BP/ML hybrid decoding algorithm to obtain a performance-complexity tradeoff for LT codes over the binary erasure channel (BEC). When BP decoding fails, the algorithm only uses the ML decoding to determine a few guessing bits for completely recovering the message. The simulation results show that, compared with the BP decoding, the BP/ML hybrid decoding has less than a 50％ increase in decoding time, which is still much smaller than that of the ML decoding. On the other hand, the proposed BP/ML hybrid decoding significantly decreases the probability of decoding failure, and its decoding performance is similar to the ML decoding when the overhead is larger than 10％.%针对LT码在短信息字长度时采用置信传播(BP)译码和最大似然(ML)译码存在大的性能差异问题,提出了一种BP/ML混合译码算法来实现LT码在二进制删除信道(BEC)中译码复杂度和性能的合理折中.此算法在BP译码失败时只需运用ML译码确定少数猜测比特就可实现成功译码.仿真结果显示,相比于BP译码,BP/ML混合译码的译码运行时间增加量少于50%,其仍远小于ML译码的译码运行时间.另一方面,BP/ML混合译码大大减少了译码失败概率,当译码开销大于10%时,BP/ML混合译码的性能接近于ML译码.