Anti-Mobile UAV Cluster Interference Algorithm based on online BSS for multi-satellite MIMO communication system with FFR

The multi-satellite multiple-input multiple-output (MIMO) communication system with full frequency reuse (FFR) has high spectral efficiency. However, satellite communications are highly susceptible to interference, and the communication quality of multi-satellite MIMO communication systems with FFR will be seriously affected when suffering from close-range interference from mobile unmanned aerial vehicle (UAV) Cluster. Therefore, we utilize an online blind source separation (BSS) algorithm without the aid of a priori information for the anti-jamming of mobile UAV clusters, which can avoid the additional occupation of channel resources, as well as process the mixed signals of time-varying systems and output separated signals in real-time. In this paper, the R-V-M-EASI algorithm is proposed, which adjusts the adaptive step size and momentum term factor using the crosstalk index as a separation performance index. The mutation point of the time-varying mixing matrix can be determined by detecting the change of the error function and then using a better converged separation matrix before the mutation to separate the observation signal retrospectively. Simulation results show that the R-V-M-EASI algorithm can effectively separate the mixed signals in both stationary and non-stationary environments, and it has faster convergence speed and lower steady error. For scenarios where the mixed matrix mutates, the proposed algorithm is effective in improving the separation accuracy of the separation matrix at the initial stage.