OTFS-Based Proactive Dynamic UAV Positioning for High-Speed Train Coverage

Abstract

The continuous wireless coverage of high-speed trains (HSTs) constitutes a big challenge due to their incredible speed reaching hundreds of kilometers per hour (km/hr). This necessitates the deployment of massive number of ground base stations (BS), which is costly particularly in rural and wilderness areas. Likewise, satellites will not provide the required ultra-high speed communication rates due to their lower operating frequencies and high path losses. Instead, in this paper, unmanned aerial vehicles (UAVs) are utilized for providing continuous coverage for HST with high data rate connectivity thanks to their flying, hovering and maneuvering capabilities at low altitudes. However, UAVs are flying at speeds much lower than HST, which necessities proactive and dynamic UAV positioning according to HST and UAV relative velocities. Hence, we propose to utilize the estimated UAV-HST channel parameters in the delay-doppler (DD) domain, employing orthogonal time-frequency space (OTFS) modulation, to facilitate proactive dynamic UAV positioning for continuous HST coverage. The UAV-HST DD channel allows for the estimation of relative velocities between UAV and HST as well as their separation distance, essential for predicting HST positions and proactively placing UAV to optimize HST coverage time and data transmission rates. Mathematical and numerical analysis demonstrate the effectiveness of the proposed approach compared to other benchmarks under various scenarios.