Interference Mitigation via Collaborative Beamforming in UAV-Enabled Data Collections: A Multi-objective Optimization Method

Abstract

Unmanned aerial vehicles (UAVs) are adopted as promising platforms to provide aerial wireless communications and networks. However, due to the line-of-sight (LoS) dominant air-ground channels, UAVs cause stronger interference to the terrestrial network devices. In this work, we study a novel interference mitigation method via collaborative beamforming (CB) under a UAV-enabled data collection scenario. Specifically, we form a UAV-enabled virtual antenna array (UVAA) to transmit the collected data to the terrestrial base stations (BSs), and formulate an interference mitigation multi-objective optimization problem (IMMOP) to simultaneously enhance the data transmission efficiency, reduce the interference affection and increase the network lifetime. Due to the complexity and NP-hardness of IMMOP, a chaotic multi-objective multi-verse optimizer (CMOMVO) is proposed for solving the problem. Simulation results show that the CMOMVO can effectively solve the IMMOP and has better performance than some benchmark algorithms.