Joint optimization of SNR and motion energy consumption for UAV-enabled collaborative beamforming

被引：2
|
作者：
Zheng, Tingting [1 ]
Liu, Yanheng [1 ]
Sun, Geng [1 ,2 ]
Zhang, Jing [3 ]
Li, Jiahui [1 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China
[2] Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China
[3] Changchun Univ Sci & Technol, Sch Comp Sci & Technol, Changchun 130022, Peoples R China
来源：
WIRELESS NETWORKS | 2022年 / 28卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Unmanned aerial vehicle; Antenna array; Collaborative beamforming; Particle swarm optimization; COMMUNICATION; NETWORKS; DESIGN;
D O I：
10.1007/s11276-022-02954-6
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Unmanned aerial vehicles (UAVs) are usually resource constrained, and have the limited communication and energy storage capacity. Collaborative beamforming (CB) in UAV networks based on a virtual node antenna array (VNAA) can enhance the signal-to-noise-ratio (SNR) and energy efficiency of a single UAV node. The UAV nodes can move to better locations for constructing the VNAA to achieve a maximum SNR of CB. However, this will result in an extra motion energy consumption. In this paper, we formulate a joint optimization problem to simultaneously optimize the received SNR and motion energy consumption for UAV-enabled CB. Then, a mended particle swarm optimization with weed optimization mechanism algorithm is proposed to solve the formulated joint optimization problem. Simulation results verify the effectiveness of the proposed algorithm.
引用
收藏
页码：2001 / 2016
页数：16
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