Clustered and Thinned Antenna Array for Adaptive Interference Suppression via K-Medoids of Desired-Signal Steering Vector

Both clustering and thinning are effective ways to reduce the implementation complexity of large-size antenna arrays. In this communication, we propose simple but efficient approaches to cluster and thin the antenna array for adaptive interference suppression. First, antenna elements are grouped using the $K$ -Medoids algorithm according to the knowledge of the desired-signal steering vector. Based on the clustered result, the minimum-variance distortionless response (MVDR) criterion with reduced dimension is then applied to ensure good adaptive-beamforming performance. To lower the implementation complexity and power consumption further, selected antenna elements are turned off on the basis of the perception from clustering. Simulation results show that under suitable settings, the adaptive interference-suppression capability of the proposed clustered and thinned antenna array can be consistently close to that of the optimal MVDR beamformer, and some reasonable compromises between the performance and both the required hardware and computational complexity are achieved.