Trajectory Optimization for Rotary-Wing UAVs in Wireless Networks with Random Requests

Abstract

This paper studies the trajectory optimization problem in a scenario where a single rotary-wing UAV acts as a relay of data payloads for downlink transmission requests generated randomly by two ground nodes (GNs) in a wireless network. The goal is to optimize the UAV trajectory in order to minimize the expected average communication delay to serve these random requests. It is shown that the problem can be cast as a semi-Markov decision process (SMDP), and the resulting minimization problem is solved via multi-chain policy iteration. The optimality of a twoscale optimization approach is proved: the optimal trajectory in the communication phase greedily minimizes the communication delay of the current request while moving between the current start position and a target end position (inner optimization); the end positions are selected to minimize the expected average long-term delay in the SMDP (outer optimization). Numerical simulations show that the expected average delay is minimized when the UAV moves towards the geometric center of the GNs during phases in which it is not actively servicing transmission requests, and demonstrate significant improvements over sensible heuristics. Finally, it is revealed that the optimal end positions of communication phases become increasingly independent of the data payload, for large data payload values.

Secrecy Rate of Resource-Constrained Mobile Relay Model under Two-Way Wiretap Channel

“…Ref. [11][12][13] aim to develop unmanned aerial vehicle(UAV)-based relay systems. They indeed provide flexible moving relays to implement air-to-ground or air-to-air wireless communication, while our ground mobile vehicle-based relay system is designed to solve the ground secure transmission problem, especially the indoor complicated pitch case.…”

“…Contrary to expectations, we all utilize successive convex optimization techniques to solve the intractable optimization problem. Nevertheless, there are other different aspects among [11][12][13] and our scheme. Firstly, there is no eavesdropper in [11,13]; thus, it is not the maximum secrecy rate but the minimum communication delay in [11] and the maximum throughput in [13].…”

“…Nevertheless, there are other different aspects among [11][12][13] and our scheme. Firstly, there is no eavesdropper in [11,13]; thus, it is not the maximum secrecy rate but the minimum communication delay in [11] and the maximum throughput in [13]. Secondly, multi-user communication scheduling and association in [13] are regarded as the integer constraints, while in our scheme, the integer constraints are the graph mobility model.…”

“…In comparison with [12], no jamming is added in our scheme, which leads to a notably different system model from that in [12]. Finally, unlike [11][12][13] employing the block coordinate descent method, we propose an iterative algorithm described as Algorithm 2 with Algorithm 1 embed in it, which is capable of obtaining a local optimal solution with much lower complexity.…”

“…On the other hand, in order to improve energy utilization efficiency, energy harvesting [7] or wireless energy transfer [8] is adopted to provide the relay and users with sufficient energy. Nowadays, there is a growing interest in deploying unmanned aerial vehicles (UAVs) in two-way relay systems [11][12][13]. UAV schemes indeed provide flexible mobile relays to implement air-to-ground or air-to-air wireless communication.…”