[Paper Review] Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks

Qingqing Wu, Yong Zeng+1 more|arXiv (Cornell University)|May 8, 2017

UAV Applications and Optimization21 references54 citations

TL;DR

The paper proposes a joint optimization framework to maximize the minimum throughput in a multi-UAV downlink by jointly optimizing user scheduling/association, UAV trajectories, and transmit powers, solved via an iterative block coordinate descent with successive convex optimization.

ABSTRACT

Unmanned aerial vehicles (UAVs) have attracted significant interest recently in assisting wireless communication due to their high maneuverability, flexible deployment, and low cost. This paper considers a multi-UAV enabled wireless communication system, where multiple UAV-mounted aerial base stations (BSs) are employed to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users in the downlink communication by optimizing the multiuser communication scheduling and association jointly with the UAVs' trajectory and power control. The formulated problem is a mixed integer non-convex optimization problem that is challenging to solve. As such, we propose an efficient iterative algorithm for solving it by applying the block coordinate descent and successive convex optimization techniques. Specifically, the user scheduling and association, UAV trajectory, and transmit power are alternately optimized in each iteration. In particular, for the non-convex UAV trajectory and transmit power optimization problems, two approximate convex optimization problems are solved, respectively. We further show that the proposed algorithm is guaranteed to converge to at least a locally optimal solution. To speed up the algorithm convergence and achieve good throughput, a low-complexity and systematic initialization scheme is also proposed for the UAV trajectory design based on the simple circular trajectory and the circle packing scheme. Extensive simulation results are provided to demonstrate the significant throughput gains of the proposed design as compared to other benchmark schemes.

Motivation & Objective

• Motivate and enable fair performance in multi-UAV downlink communications with high mobility and interference.
• Maximize the minimum average rate among ground users through joint design of scheduling, UAV trajectories, and power control.
• Develop an efficient algorithm with convergence guarantees for a mixed-integer non-convex problem.
• Provide initialization and reconstruction methods to improve convergence and practical applicability.

Proposed method

• Formulate a mixed-integer non-convex optimization problem to maximize the minimum user rate under trajectory, power, and association constraints.
• Relax binary scheduling variables to continuous values and apply block coordinate descent to iteratively optimize three blocks: scheduling/association, UAV trajectory, and transmit power.
• Use successive convex optimization to handle non-convex trajectory and power problems by constructing convex bounds and linearizations.
• Introduce a circular trajectory-based initialization and circle-packing scheme to speed up convergence.
• Prove convergence of the iterative algorithm and provide a method to reconstruct binary decisions from the relaxed solution.

Experimental results

Research questions

• RQ1 Can the minimum average rate of ground users be maximized by jointly designing scheduling/association, UAV trajectories, and transmit powers in a multi-UAV downlink?
• RQ2 What is the impact of UAV mobility and interference management on throughput fairness in multi-UAV networks?
• RQ3 How can a tractable algorithm with convergence guarantees be developed for the resulting mixed-integer non-convex problem?
• RQ4 Does a circular trajectory initialization improve convergence and throughput performance?
• RQ5 How can relaxed continuous scheduling decisions be effectively mapped back to binary associations?

Key findings

• The proposed algorithm achieves significant throughput gains over benchmark schemes with static UAVs or heuristic trajectories.
• Throughput improves with the trajectory design period, illustrating a throughput-access delay tradeoff in multi-UAV systems.
• Using multiple UAVs substantially alleviates the throughput-access delay tradeoff compared to a single-UAV setup.
• The block coordinate descent with successive convex optimization converges to a stationary point under the proposed relaxations and approximations.
• An efficient initialization scheme based on circular trajectories and circle packing speeds up convergence and improves performance.