基于独立分量分析的PCMA信号盲分离算法

Blind Separation Algorithm of PCMA Signal Based on Independent Component Analysis

针对非协作通信中成对载波多址(Paired Carrier Multiple Acess,PCMA)信号的盲分离问题,提出了一种基于独立分量分析(Independent Component Analysis,ICA)的单通道盲分离算法。首先对接收到的单路PCMA信号进行参数估计得到其残余载波频率,再对其处理得到2路基带混合信号,最后利用Fast ICA算法分离出源基带信号。该算法在未知2个卫星地面站发送信号的情况下,从接收到的PCMA信号中恢复出2路源基带信号。仿真实验表明,该算法在信噪比为-10 d B时仍具有良好的分离效果,2路基带信号的波形相似系数可分别达到0.94与0.86以上。

Aiming at the problem of blind source separation of paired carrier Multiple acess （PCMA） signal in non-cooperative communication, a blind single channel separation algorithm based on independent component analysis（ICA） is proposeed. Firstly, parameter estimation is applied on the single PCMA signal to get the estimation of residual carrier frequency, then two baseband mixed signal is obtained by processing. Finally,the source baseband signal is isolated by using FastlCA algorithm. Two source baseband signals are demodulated from the received PCMA signal under the precondition of not knowing the signals sended by two ground station. Tbe simulation test show that the algorithm in this paper can get high separation performance at low signal-to-noise ratio level（-10 dB） , the waveform similarity cofficient of two baseband signal can reach at 0. 94 and 0. 86 respectively.