An Accurate Beam-Tracking Algorithm with Adaptive Beam Reconstruction via UAV-BSs for Mobile Users
Jing Zhang, Sheng Gao, Xin Feng, Hongwei Yang, and Geng Sun

TL;DR
This paper introduces a novel beam-tracking algorithm for UAV base stations that adaptively reconstructs beams to accurately track high-speed mobile users, enhancing communication reliability in dynamic environments.
Contribution
The study proposes the BAB-AR algorithm combining angle-aware tracking, Gaussian process regression, and adaptive beam reconstruction, which is a new integrated approach for real-time UAV beam alignment.
Findings
BAB-AR outperforms benchmark algorithms in beam accuracy.
The algorithm effectively tracks high-speed mobile users.
Simulation results confirm timely beam coverage for fast-moving users.
Abstract
Unmanned aerial vehicles (UAVs) with flexible deployment contribute to enlarging the distance of information transmission to mobile users (MUs) in constrained environment. However, due to the high mobility of both UAVs and MUs, it is challenging to establish an accurate beam towards the target MU with high beam gain in real-time. In this study, UAV base stations (UAV-BSs) consisting of position-known assisted UAVs (A-UAVs) and position-unknown assisted UAVs (U-UAVs) are employed to transmit data to MUs. Specifically, a bi-directional angle-aware beam tracking with adaptive beam reconstruction (BAB-AR) algorithm is proposed to construct an optimal beam that can quickly adapt the movement of the target MU. First, the angle-aware beam tracking is realized within the UAVBSs using a proposed global dynamic crow search algorithm without historical trajectory. Furthermore, the Gaussian process…
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Taxonomy
TopicsAntenna Design and Optimization
