Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 72, Issue 3, Pages 3647-3662Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2022.3220696
Keywords
Orbits; Autonomous aerial vehicles; Throughput; Relays; Radio frequency; Reinforcement learning; Wireless communication; LEO satellite; UAV; non-terrestrial network; hybrid FSO/RF; multi-agent deep reinforcement learning
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This study investigates the problem of forwarding packets between two faraway ground terminals through SAT and UAV relays using RF or FSO link within a NTN. The associations with orbiting SATs and the trajectories of UAVs are optimized to maximize communication efficiency. A multi-agent deep reinforcement learning approach with action dimensionality reduction technique is proposed to overcome the challenges. Simulation results show that the SAT-UAV integrated scheme achieves higher end-to-end sum throughput and energy efficiency compared to benchmark schemes, and the proposed scheme utilizing hybrid FSO/RF links achieves significantly higher peak and worst-case throughput, highlighting the importance of co-designing SAT-UAV associations, UAV trajectories, and hybrid FSO/RF links in beyond-5 G NTNs.
Integrating low-altitude earth orbit (LEO) satellites (SATs) and unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN), we investigate the problem of forwarding packets between two faraway ground terminals through SAT and UAV relays using either radio-frequency (RF) or free-space optical (FSO) link. Towards maximizing the communication efficiency, the associations with orbiting SATs and the trajectories of UAVs should be optimized, which is challenging due to the time-varying network topology and a huge number of possible control actions. To overcome the difficulty, we lift this problem to multi-agent deep reinforcement learning with a novel action dimensionality reduction technique. Simulation results corroborate that our proposed SAT-UAV integrated scheme achieves 1.99x higher end-to-end sum throughput compared to a benchmark scheme with fixed ground relays. While improving the throughput, our proposed scheme also aims to reduce the UAV control energy, yielding 2.25x higher energy efficiency than a baseline method only maximizing the throughput. Lastly, thanks to utilizing hybrid FSO/RF links, the proposed scheme achieves up to 62.56x higher peak throughput and 21.09x higher worst-case throughput than the cases utilizing either RF or FSO links, highlighting the importance of co-designing SAT-UAV associations, UAV trajectories, and hybrid FSO/RF links in beyond-5 G NTNs.
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