Abstract:
In this paper, we propose collaborative beamforming (CB) in unmanned aerial vehicle (UAV)-assisted communication networks to improve transmission data rate with minimum e...Show MoreMetadata
Abstract:
In this paper, we propose collaborative beamforming (CB) in unmanned aerial vehicle (UAV)-assisted communication networks to improve transmission data rate with minimum energy consumption. Specifically, CB allows a group of UAVs forming a virtual element antenna array (VEAA) and transmitting data collaboratively in a synchronous manner through a high-gain mainlobe (ML) beam. The goal is to optimize the deployment locations of UAVs in the VEAA and excitation current weights for performing CB transmissions considering the energy cost for UAV deployment. Accordingly, we formulate an Energy-Efficient Communication Multi-objective Optimization Problem (EECMOP) to jointly maximize the transmission rate and minimize the maximum sidelobe level (SLL) as well as UAV energy consumption. Then, we propose an Enhanced Multi Objective Ant Lion Optimizer (EMOALO) algorithm which incorporates a chaos theory to develop chaotic initialization and adjustable mode operators for solving the problem. Simulation results demonstrate the effectiveness of the EMOALO algorithm in improving energy efficiency for UAV-assisted communication networks.
Published in: 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
Date of Conference: 05-08 September 2023
Date Added to IEEE Xplore: 31 October 2023
ISBN Information: