UAV Trajectory and Communication Co-Design: Flexible Path Discretization and Path Compression | IEEE Journals & Magazine | IEEE Xplore

UAV Trajectory and Communication Co-Design: Flexible Path Discretization and Path Compression


Abstract:

The performance optimization of UAV communication systems requires the joint design of UAV trajectory and communication efficiently. To tackle the challenge of infinite d...Show More

Abstract:

The performance optimization of UAV communication systems requires the joint design of UAV trajectory and communication efficiently. To tackle the challenge of infinite design variables arising from the continuous-time UAV trajectory optimization, a commonly adopted approach in the existing literature is by approximating the UAV trajectory with piecewise-linear path segments connected via a finite number of waypoints in three-dimensional (3D) space. However, this approach may still incur prohibitive computational complexity in practice when the UAV flight period/distance becomes long, as the distance between consecutive waypoints needs to be kept sufficiently small to retain high approximation accuracy. To resolve this fundamental issue, we propose in this paper a new and general framework for UAV trajectory and communication co-design with flexible number of waypoint optimization variables (called designable waypoints) or their sub-path representations. First, we propose a flexible path discretization scheme that optimizes only a number of selected waypoints (designable waypoints) along the UAV path for complexity reduction, while all the designable and non-designable waypoints are used in calculating the approximated communication utility along the UAV trajectory for ensuring high trajectory discretization accuracy. Next, we propose a novel path compression scheme, which treats the UAV trajectory as a signal and compresses its path representation based on the basis decomposition. Specifically, the UAV 3D path is first decomposed into three one-dimensional (1D) sub-paths and each sub-path is then approximated by superimposing a number of selected basis paths (which are generally less than the number of designable waypoints) weighted by their corresponding path coefficients, thus further reducing the path design complexity. Finally, we provide a case study on UAV trajectory design for aerial data harvesting from distributed sensors, and numerically show that the pro...
Published in: IEEE Journal on Selected Areas in Communications ( Volume: 39, Issue: 11, November 2021)
Page(s): 3506 - 3523
Date of Publication: 14 June 2021

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