Abstract
The scarcity of energy resources and spectrum resources has become an urgent problem with the exponential increase of communication devices. Meanwhile, unmanned aerial vehicle (UAV) is widely used to help communication network recently due to its maneuverability and flexibility. In this paper, we consider a UAV-assisted energy and spectrum harvesting (ESH) network to better solve the spectrum and energy scarcity problem, where nearby secondary users (SUs) harvest energy from the base station (BS) and perform data transmission to the BS, while remote SUs harvest energy from both BS and UAV but only transmit data to UAV to reduce the influence of near-far problem. We propose an unaligned time allocation scheme (UTAS) in which the uplink phase and downlink phase of nearby SUs and remote SUs are unaligned to achieve more flexible time schedule, including schemes (a) and (b) in remote SUs due to the half-duplex of energy harvesting circuit. In addition, maximum throughput optimization problems are formulated for nearby SUs and remote SUs respectively to find the optimal time allocation. The optimization problem can be divided into three cases according to the relationship between practical data volume and theoretical throughput to avoid the waste of time resource. The expressions of optimal energy harvesting time and data transmission time of each node are derived. Lastly, a successive convex approximation based iterative algorithm (SCAIA) is designed to get the optimal UAV trajectory in broadcast mode. Simulation results show that the proposed UTAS can achieve better performance than traditional time allocation schemes.
Highlights
W ITH the rapid development of wireless communication network, the number of devices is growing at an exponential speed [1]–[5]
SIMULATION RESULTS we simulate the optimal results of the nearby secondary users (SUs) and the remote SUs, and analyze the simulation results compared with the optimization results in the previous paper [18]
We set up Pb = 40W, Pu = 5W, H = 3m, tf = 20s, g = h = 30dBm and the simulation area is assumed to be a rectangle of 100 ∗ 100, in which 10 nearby SUs and 10 remote SUs are randomly distributed
Summary
W ITH the rapid development of wireless communication network, the number of devices is growing at an exponential speed [1]–[5]. It is estimated that billions of devices will be connected with each other in the future, which brings much convenience to everyone daily life. At the same time, energy consumption [6] [7] and spectrum scarcity [8] become two huge challenges as communication among large quantity pieces of equipment. Battery replacement will bring huge economic cost and cause environmental pollution. Battery power supply can not solve the problem of huge energy [9]. How to provide energy and spectrum resource for a large number of devices becomes a hot research issue
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