Throughput Maximization for UAV-Enabled Wireless Powered Communication Networks (1801.04545v4)

Abstract: This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users periodically. The UAV employs the radio frequency (RF) wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send independent information to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory design, jointly with the wireless resource allocation optimization, to maximize the system throughput. In particular, we aim to maximize the uplink common (minimum) throughput among all ground users over a finite UAV's flight period, subject to its maximum speed constraint and the users' energy neutrality constraints. The resulted problem is non-convex and thus difficult to be solved optimally. To tackle this challenge, we first consider an ideal case without the UAV's maximum speed constraint, and obtain the optimal solution to the relaxed problem. The optimal solution shows that the UAV should successively hover above a finite number of ground locations for downlink WPT, as well as above each of the ground users for uplink communication. Next, we consider the general problem with the UAV's maximum speed constraint. Based on the above multi-location-hovering solution, we first propose an efficient successive hover-and-fly trajectory design, jointly with the downlink and uplink wireless resource allocation, and then propose a locally optimal solution by applying the techniques of alternating optimization and successive convex programming (SCP). Numerical results show that the proposed UAV-enabled WPCN achieves significant throughput gains over the conventional WPCN with fixed-location AP.

• The paper proposes a joint design of UAV trajectory and resource allocation to maximize uplink throughput in wireless powered networks.
• It introduces a successive hover-and-fly strategy and an alternating optimization with successive convex programming to address non-convex constraints.
• Numerical results demonstrate that UAV mobility significantly enhances throughput and user fairness compared to fixed access point designs.

Overview of UAV-Enabled Wireless Powered Communication Networks

The paper "Throughput Maximization for UAV-Enabled Wireless Powered Communication Networks" by Lifeng Xie, Jie Xu, and Rui Zhang presents a paper on the deployment of unmanned aerial vehicles (UAVs) as mobile access points (APs) in wireless powered communication networks (WPCNs). The work leverages the mobility of UAVs to enhance network performance, a marked departure from traditional fixed-location APs. The focus is on maximizing the uplink common throughput by optimizing the UAV's trajectory in conjunction with resource allocation.

Key Concepts and Approach

The proposed system utilizes radio frequency (RF) wireless power transfer (WPT) to supply energy to ground users in the downlink while using the harvested energy for data transmission in the uplink. The challenge addressed is to jointly design the UAV's trajectory and the wireless resource allocation to maximize system throughput subject to certain constraints, including the UAV's maximum speed and users' energy neutrality.

The core problem is non-convex due to the complicated interplay between UAV trajectory, user energy harvesting, and throughput maximization. The authors tackle this by first considering an ideal scenario without the UAV's speed constraint. This simplification allows them to derive an optimal multi-location hovering strategy for the UAV, where it alternately hovers above specified ground locations and individual users.

Optimization Techniques

To address the general problem inclusive of the speed constraint, the paper introduces two methods:

1. Successive Hover-and-Fly Trajectory: This strategy implements a heuristic where the UAV alternates between hovering and flying based on the initial hovering locations, maximizing efficiency by optimizing trajectory and wireless resource allocation simultaneously.
2. Alternating Optimization with Successive Convex Programming (SCP): This method refines the solution iteratively, ensuring improvements in throughput by alternating between optimizing wireless resources and the UAV's trajectory. It is demonstrated that this method can surpass the performance of the successive hover-and-fly strategy, particularly for smaller flight durations.

Numerical Results and Implications

Through numerical simulations, the paper illustrates that the UAV-enabled WPCN significantly outperforms conventional WPCNs with static APs, particularly when larger flight periods allow for greater UAV mobility. The proposed designs effectively manage the "doubly near-far" issue inherent in fixed AP configurations, enhancing user fairness and throughput across distributed users.

The paper paves the way for further exploration into multi-UAV systems and the intricacies involved in optimizing UAV mission durations to accommodate realistic operational constraints like battery life and communication delays. Such future work could expand the practical applicability of UAVs in enhancing wireless networks.

In conclusion, the paper provides a comprehensive framework for integrating UAV mobility with WPCNs to augment communication capabilities, suggesting substantial throughput improvements over conventional methods. The methodology and results offer compelling insights for researchers focusing on UAV applications in wireless networking and energy-efficient communication strategies.