Throughput Maximization for Multi-Cluster NOMA-UAV Networks

被引：1
作者：
Huang, Qiulei [1 ]
Wang, Wei [1 ]
Lu, Weidang [2 ]
Zhao, Nan [1 ]
Nallanathan, Arumugam [3 ]
Wang, Xianbin [4 ]
机构：
[1] Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116024, Peoples R China
[2] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310058, Peoples R China
[3] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London WC1E 7HU, England
[4] Western Univ, Dept Elect & Comp Engn, London, ON, Canada
来源：
2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022) | 2022年
基金：
国家重点研发计划;
关键词：
Genetic algorithm; K-means; non-orthogonal multiple access; resource allocation; unmanned aerial vehicle; POWER OPTIMIZATION;
D O I：
10.1109/GLOBECOM48099.2022.10000720
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Combining non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAVs) can achieve better performance for wireless networks. In this paper, we propose an effective scheme for NOMA-UAV network with multiple clusters. Due to the limited resource, the user clustering and optimal routing are first developed by the K-means algorithm and genetic algorithm, respectively. Then, the sum throughput is maximized by jointly optimizing the transmission power, hovering locations and transmission duration of UAV. To solve this non-convex problem with coupled variables, we decompose it into three subproblems. Among them, the non-convex subproblems can be transformed into convex ones by successive convex approximation. Then, we propose an iterative algorithm to solve these three subproblems alternately. Finally, simulation results are presented to show the effectiveness of the proposed scheme.
引用
收藏
页码：3730 / 3735
页数：6
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