Minimum Throughput Maximization in UAV-Aided Wireless Powered Communication Networks

TL;DR

This paper proposes joint trajectory, power, and time resource optimization algorithms for UAV-assisted wireless powered communication networks to maximize the minimum throughput among ground terminals, considering integrated and separated UAV configurations.

Contribution

It introduces novel optimization algorithms for UAV trajectory, power control, and resource allocation in both integrated and separated UAV WPCNs, addressing non-convex problems with iterative solutions.

Findings

Proposed algorithms outperform conventional schemes in simulations.

Joint optimization significantly improves minimum throughput.

Effective handling of non-convex constraints via concave-convex procedure.

Abstract

This paper investigates unmanned aerial vehicle (UAV)-aided wireless powered communication network (WPCN) systems where a mobile access point (AP) at the UAV serves multiple energy-constrained ground terminals (GTs). Specifically, the UAVs first charge the GTs by transmitting the wireless energy transfer (WET) signals in the downlink. Then, by utilizing the harvested wireless energy from the UAVs, the GTs send their uplink wireless information transmission (WIT) signals to the UAVs. In this paper, depending on the operations of the UAVs, we adopt two different scenarios, namely integrated UAV and separated UAV WPCNs. First, in the integrated UAV WPCN, a UAV acts as a hybrid AP in which both energy transfer and information reception are processed at a single UAV. In contrast, for the separated UAV WPCN, we consider two UAVs each of which behaves as an energy AP and an information AP independently, and thus the energy transfer and the information decoding are separately performed at two different UAVs. For both systems, we jointly optimize the trajectories of the UAVs, the uplink power control, and the time resource allocation for the WET and the WIT to maximize the minimum throughput of the GTs. Since the formulated problems are non-convex, we apply the concave-convex procedure by deriving appropriate convex bounds for non-convex constraints. As a result, we propose iterative algorithms which efficiently identify a local optimal solution for the minimum throughput maximization problems. Simulation results verify the efficiency of the proposed algorithms compared to conventional schemes.