一种低复杂度非对称混合信号盲分离算法

Low Complexity Blind Separation Algorithm of Asymmetric Mixed Signal

针对符号速率相同的功率非对称混合信号盲分离问题,提出一种低复杂度盲分离算法。该算法仅需确定强信号最佳采样点,进而消除强信号影响,避免了传统算法波形重构过程,并且通过迭代译码结构来改善强弱信号的分离性能,重点研究了混合信号中强信号的消除以及强弱信号的迭代译码结构。仿真实验表明,对采用(2,1,2)卷积码的QPSK混合信号,强弱信号幅度比为0.5时,可以达到最佳分离性能,混合信号经2次迭代译码后,分离性能提升约1d B。

A low complexity blind separation algorithm was proposed to realize blind separation of asymmetric mixed signal with the same data rates. This new algorithm only needs the best sampling time of strong signal. As such, the interference of strong signal was removed, and thus the waveform reconstruction process in traditional algorithm was avoided. The iterative decoding structure was used to improve the separation performance. Special emphasis was put on strong signal removing in asym- metric mixed signal and the iterative decoding structure of the asymmetric mixed signal. Simulation results show that, for QPSK signals with （2,1,2） convolutional codes, the best separation performance can be obtained when the amplitude ratio between strong signal and weak signal is 0.5, and a gain of about ldB separation performance can be obtained after two iterations.