UAV-Enabled Wireless Power Transfer: Trajectory Design and Energy Optimization (1709.07590v1)

Abstract: This paper studies a new unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system, where a UAV-mounted mobile energy transmitter (ET) is dispatched to deliver wireless energy to a set of on-ground energy receivers (ERs). We investigate how the UAV should optimally exploit its mobility via trajectory design to maximize the energy transferred to all ERs during a finite period. First, we consider the maximization of the sum energy received by all ERs by optimizing the UAV's trajectory subject to its maximum speed constraint. We obtain its optimal solution, which shows that the UAV should hover at one single fixed location during the whole period. However, the sum-energy maximization incurs a "near-far" fairness issue. To overcome this issue, we consider a different problem to maximize the minimum received energy among all ERs. We first consider an ideal case by ignoring the UAV's maximum speed constraint, and show that the relaxed problem can be optimally solved via the Lagrange dual method. Then, for the general case with the UAV's maximum speed constraint considered, we propose a new successive hover-and-fly trajectory motivated by the optimal trajectory in the ideal case, and obtain efficient trajectory designs by applying the successive convex programing (SCP).

• The paper proposes UAV trajectory designs that optimize total energy delivery by leveraging exhaustive search and dual methods.
• It introduces a 'successive hover-and-fly' strategy to balance UAV speed limits with multi-location hovering for enhanced fairness.
• Numerical results validate that multi-location hover approaches outperform single-location tactics in improving wireless power transfer efficiency.

UAV-Enabled Wireless Power Transfer: Trajectory Design and Energy Optimization

The paper "UAV-Enabled Wireless Power Transfer: Trajectory Design and Energy Optimization" by Jie Xu, Yong Zeng, and Rui Zhang explores an innovative approach for enhancing the efficiency of wireless power transfer (WPT) by employing unmanned aerial vehicles (UAVs) as mobile energy transmitters (ETs). This system presents a significant evolution from traditional fixed-location ET deployments to address limitations such as high propagation loss and the necessity for ultra-dense infrastructure in wide-coverage WLAN networks.

Problem Formulation

The paper focuses on optimizing UAV trajectories for maximizing energy transfer to ground-based energy receivers (ERs) during a fixed charging period. Two primary optimization objectives are considered:

1. Sum-Energy Maximization: The goal here is to maximize the total energy received by all ERs. Solving this non-convex problem, the paper reveals that the UAV should hover at a single optimal location throughout the charging period, determined through a two-dimensional exhaustive search. This solution, however, leads to a significant "near-far" fairness issue, where ERs closer to the UAV receive disproportionately more energy.
2. Min-Energy Maximization: To address fairness, this objective aims to maximize the minimum energy received among all ERs. For the relaxed scenario without UAV speed constraints, the Lagrange dual method provides an optimal solution where the UAV hovers over multiple fixed locations, ensuring energy fairness across ERs. Practical scenarios with speed constraints inspire a novel "successive hover-and-fly" trajectory informed by multi-location hovering.

Numerical Analysis and Insights

The paper provides substantial numerical evidence comparing the proposed trajectory designs against various benchmarks, demonstrating significant performance improvements in both total energy efficiency and fairness. Notable insights include:

• For short distances between ERs, hovering above the midpoint maximizes both sum and min-energy metrics. As distance increases, trajectory designs that incorporate multiple hovering locations outperform single-location strategies due to their enhanced fairness.
• The "successive hover-and-fly" approach balances practical constraints like the UAV’s maximum speed, providing robust performance even with limited charging durations.
• Iterative refinement techniques, such as the successive convex programming (SCP)-based algorithm, further enhance trajectory designs for scenarios with multiple ERs, achieving results close to theoretical upper bounds.

Implications and Future Directions

This research extends the potential applications of UAVs in WPT systems, presenting a compelling case for their adaptation in future IoT networks. By effectively leveraging UAV mobility, the paper demonstrates possibilities for reducing infrastructure costs while improving service coverage and energy distribution fairness.

Future research could explore multi-UAV scenarios, which introduce complexities in collaborative trajectory design and inter-UAV interference management. Additionally, considering stochastic elements like variable receiver positions and environmental factors could offer a more comprehensive understanding of UAV-enabled WPT systems in dynamic real-world conditions. As UAV technologies and energy harvesting techniques continue to advance, the integration and optimization innovations presented in this paper are likely to inform broader wireless communication and power transfer strategies.