利用Gibbs采样的同频混合信号单通道盲分离

Single-channel blind separation of co-frequency modulated signals based on Gibbs sampler

针对非合作接收的单通道同频数字调制混合信号,提出一种基于Gibbs采样的分离算法。该算法利用统计的方法获得未知符号序列概率密度的随机样本,运算复杂度随信道阶数的增加不呈指数增长。重点研究了基于单符号对、多符号对的分离算法和信道响应的跟踪,并对Gibbs分离算法和PSP分离算法的性能进行了详细的分析比较。仿真结果表明,针对2路QPSK调制的混合信号,在与L=4时的PSP算法具有近似分离性能的同时,Gibbs分离算法可使复杂度降低近17倍。

A Gibbs-sampler-based separation algorithm was proposed for single-channel co-frequency digital-modulated signals, which were received in non-cooperative ways. The probability density samples of unknown symbol sequences can be obtained by statistic method, and the computation complexity was not growing exponentially with the increase of channel order. With special emphasis on the separation algorithms of single pair of symbols, multiple pair of symbols and the tracking of channel responses. Moreover, the separation performance between Gibbs sampler and per-survivor proc- essing（PSP） algorithm were analyzed and compared in detail. Simulation results show that, compared with PSP algorithm with L=4 for two co-frequency QPSK-modulated signals, Gibbs sampler can be nearly 17 times lower in computation complexity when the approximately performance is obtained.