Compressive Sensing-Based Array Antenna Optimization for Adaptive Beamforming

2020 
In the digital beamforming, each antenna element usually corresponds to a front-end chain, which dramatically increases the hardware costs. In this paper, compressive sensing-based array antenna optimization technique is used for adaptive beamforming, which can decrease the hardware complexity while suppressing the interfering signals. Compressive sensing is utilized to reduce the sampling channel number, and the sparse reconstruction based on the convex optimization model is applied to accurately recover the full-array data. Then, the weight vector can be obtained by the recovered data. Simulation results are carried out to demonstrate the effectiveness of the proposed method.
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