Energy-Efficient Resource Allocation and Trajectory Design for UAV Relaying Systems

被引:54
作者
Zhang, Tong [1 ]
Liu, Gongliang [2 ]
Zhang, Haijun [3 ,4 ]
Kang, Wenjing [2 ]
Karagiannidis, George K. [5 ]
Nallanathan, Arumugam [6 ]
机构
[1] Harbin Inst Technol, Commun Engn, Harbin 150000, Peoples R China
[2] Harbin Inst Technol, Weihai 264209, Peoples R China
[3] Univ Sci & Technol Beijing, Beijing Adv Innovat Ctr Mat Genome Engn, Inst Artificial Intelligence, Beijing 100083, Peoples R China
[4] Univ Sci & Technol Beijing, Beijing Engn & Technol Res Ctr Convergence Networ, Beijing 100083, Peoples R China
[5] Aristotle Univ Thessaloniki, Elect & Comp Engn Dept, Thessaloniki 54124, Greece
[6] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London E1 4NS, England
基金
北京市自然科学基金; 中国国家自然科学基金; 国家重点研发计划;
关键词
Relays; Fuels; Trajectory; Resource management; Batteries; Fading channels; Communication systems; Energy efficiency; power allocation; mobile relay; trajectory design; POWER ALLOCATION; COMMUNICATION; OPTIMIZATION; MAXIMIZATION; MINIMIZATION; PERFORMANCE; NETWORKS; COVERAGE; NOMA;
D O I
10.1109/TCOMM.2020.3009153
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Fuel-powered UAVs have long endurance of flight, heavy payload and adaptation to extreme environment. The mechanical operation and communication power are supported independently by fuel and batteries. In the paper, we study the energy efficiency of the communication system with a fuel-powered UAV relay. We consider a three-node communication network, consisting of a mobile relay, a source node, and a destination node. The UAV relay is able to change its 3-D trajectory to maintain high probability of LoS channels, receiving information from the fixed source node and transmitting it to the fixed destination node. The power allocation scheme and UAV's trajectory are designed to maximize the system energy efficiency, considering the constraints of speeds, UAV's altitudes, communication and mechanical energy consumption, the required data rates of the destination node and information-causality. We solve the power allocation sub-problem by splitting the domain of variables and transforming it into a convex optimization problem. And then a suboptimal scheme is provided to design the trajectory based on successive convex approximation method. Numerical results show the convergence of the proposed schemes and the performance of the proposed algorithms. The influences of time slots, constraints of fuel, communication power and required data rates are discussed.
引用
收藏
页码:6483 / 6498
页数:16
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