一种面向IRS辅助的无线通信盲源分离算法

Blind source separation algorithm for IRS-assisted wireless communication

针对智能反射面(Intelligent Reflecting Surface,IRS)辅助的无线通信系统中同频干扰和通信信号混叠的问题,提出一种小波阈值去噪的快速独立成分分析(Fast Independent Component Analysis,FastICA)盲源分离算法。将观测信号进行小波阈值去噪处理,滤除无线通信环境中的噪声,再采用基于最大化负熵的FastICA算法处理去噪后的混叠信号,实现对通信信号与干扰信号的分离和提取。仿真结果表明,所提算法可以提高通信系统的信干噪比(Signal-to-Interference-Plus-Noise Ratio,SINR),能够有效地实现IRS辅助无线通信系统中的同频混叠信号分离。

In order to address the issue of signal mixed with co-channel interference in an intelligent reflecting surface(IRS)-assisted wireless communication system,FastICA blind source separation(BSS)algorithm with wavelet threshold denoising is proposed.The observed signal is denoised by the wavelet threshold to filter the noise in wireless communication environment,and the FastICA algorithm based on the maximum negative entropy is adopted to process the mixed signal after denoising,and to realize the separation and extraction of the communication signal and the interference signal.Simulation results demonstrate that this algorithm enhances the signal-to-interference-plus-noise ratio(SINR)in the communication system,and can successfully separate the co-channel interference signal in IRS assisted wireless communication systems.