Enhanced Multi-Objective Optimization Approach for Low-Interference UAV Communication Based on Collaborative Beamforming

Unmanned aerial vehicles (UAVs) are widely used in the field of wireless communications due to their inherent advantages such as easy deployment and low cost. Employing collaborative beamforming techniques to form a UAV-based virtual antenna array (UVAA) is a promising solution to achieve remote and low-cost communications. Owing to the nature of electromagnetic waves, UVAA may cause interference to unaffiliated users when deployed in densely populated areas. To address this issue, UAVs must identify the most suitable positions to achieve optimal beam patterns. However, considering their limited energy capacity and the increased power consumption associated with excessive flight, a multi-objective optimization analysis is necessary to balance these factors. Thus, we formulate a low-interference communication multi-objective problem (LIMOP), aiming to maximize transmission rate, minimize interference, and reduce energy consumption through the optimization of UAV positions, excitation currents, and the selection of target BS. Given the complexity of LIMOP, we introduce multiple improvement strategies to propose an improved swarm intelligence method. According to simulation results, the proposed IMOAHA is effective in addressing the formulated LIMOP and is superior to other algorithms.