类卷积译码的容错解扰算法

Convolutional Decoding Like Error-Resilient Descrambling Algorithm

针对自同步扰码系统的联合信源信道译码问题,本文将自同步扰码看作一种特殊的卷积编码,提出了类似卷积译码的软输入软输出(SISO)自同步去扰算法。该算法利用信源冗余更新扰码序列的外信息,在信道译码时作为先验信息进行译码,实现了自同步去扰与信道译码之间的软信息交互,充分利用了信源冗余信息,使得接收系统的性能得到了有效提升。仿真结果表明,在TPC编码条件下,当信源冗余度为70%时,联合信源信道译码的性能增益约为4.1dB。相比于单一纠错编码系统,当通信系统中存在自同步扰码时,联合信源信道译码具有更大的性能增益。

To realize joint source-channel decoding in the system with self-synchronization scrambling, a convolutional decoding like Soft-Input Soft-Output （SISO） descrambling algorithm is proposed in this paper by treating the self-synchronization scrambler as a special convolutional code. In this algorithm, residual source redundancy is used to update the extrinsic information of the scrambling sequence, which is then used as a prior information in the channel decoding process. So that, soft information exchanges with each other between the descrambler and the decoder, which efficiently improve the performance in the receiver. The performance of the proposed algorithm is verified by simulations. Results show that our approach outperforms the conventional descrambler by 4. ldB in the case of TPC encoder, while the residual source redundancy rate is 70%. Joint source-channel decoding in the system with self-synchronization scrambling can achieve larger gain compared with the system with only channel coding.