A New OMVDR Adaptive Anti-inference Beamforming Algorithm

Beamforming is a key technology in millimeter-wave communication. By controlling the transmitter and receiver of a millimeter-wave antenna array, the signal-to-noise ratio (SNR) can be effectively improved, and interference and noise can be suppressed. In order to further enhance the anti-interference ability of beamforming, under the condition of minimum variance distortionless response (MVDR) linear constraint, this paper uses the gray wolf optimization (GWO) algorithm numerical search capability to optimize the weights. An optimized minimum variance distortionless response (OMVDR) adaptive beamforming algorithm is presented. In the selection of the fitness function, the idea of separating amplitude and phase is adopted, and the fitness function is set to the weighted sum of the mean square error of the output signal and the input signal, thereby realizing the simultaneous optimization of the weight amplitude and phase. Simulation results show that OMVDR has lower sidelobe level and null and better anti-interference ability than traditional MVDR algorithms and PSO-MVDR.