在加性高斯白噪声(AddITIVE WHITE gAuSSIAn nOISE,AWgn)信道中设计一种低密度奇偶校验(lOW-dEnSITy PArITy-CHECk,ldPC)码的最大似然译码算法是一项具有挑战性的工作。麦克斯韦译码算法在二进制擦除信道下具有优越的性能,但把这种算法移植到其他信道却非常困难。引入了信道转换的思想实现两个不同信道之间的转换,并利用该方法成功地将麦克斯韦算法应用到AWgn信道中,提出了一种将信度传播算法和麦克斯韦算法有机结合的联合译码算法,即信度传播-麦克斯韦译码算法,该算法可缩小与最大似然译码算法之间的性能差距。仿真表明,该译码算法可打破大多数小陷阱集从而获得比信度传播译码算法更低的误帧率,并且可消除大多数信度传播译码后出现的小错误。Designing a realizable maximum likelihood(ML) decoder for low-density parity-check(LDPC) codes is always a challenging work over an additive white Gaussian noise(AWGN) channel.Although Maxwell decoder is well known for its excellent performance over the binary erasure channel(BEC),it seems that generalizing this algorithm for other channels is difficult.This paper introduces an idea called channel transformation which could realize the conversation between two different channels.A Maxwell decoder is applied to an AWGN channel.In terms of this method,and a joint decoder-BP-Maxwell(BM) decoder is proposed which combines a belief propagation(BP) decoder and a Maxwell decoder,to reduce the gap to the ML decoder in performance.Simulation results show that the BM decoding algorithm could break most small trapping sets to accomplish a lower frame error rate(FER).Moreover it also could eliminate most of the small-scale errors compared with a BP decoder.国家自然科学基金(60972053)资助课
