Multi-UAV Assisted Mixed FSO/RF Communication Network for Urgent Tasks: Fairness Oriented Design With DRL

Wireless communications can be improved by employing free space optical (FSO) channels. Since optical signals can only be transmitted via line-of-sight paths, UAVs are employed to forward data from a base station (BS) to remote users for urgent tasks using multi-hop mixed FSO/RF links. The UAVs employ the decode and forward protocol to relay data. The last UAV decodes and forwards the data to multiple users through RF links using non-orthogonal multiple access (NOMA). To improve fairness, a modified deep reinforcement learning (DRL) algorithm is used to optimize the transmit power allocation in real-time to minimize the maximum user decoding outage probability. Numerical results are presented to illustrate the system design tradeoffs. In addition, the validity of the proposed approach are verified by comparing it with exhaustive search algorithm.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2024-09-03
DOI
https://doi.org/10.1109/tvt.2024.3453333
Citations
22
Primary Topic
Optical Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
4.59

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article

Multi-UAV Assisted Mixed FSO/RF Communication Network for Urgent Tasks: Fairness Oriented Design With DRL

Luozhi Zhang, Tingnan Bao, Yiyuan Xie, Thomas Aaron Gulliver et al.
22 citations
IEEE Transactions on Vehicular Technology
Optical Wireless Communication Technologies
4.59
article

Multi-UAV Assisted Mixed FSO/RF Communication Network for Urgent Tasks: Fairness Oriented Design With DRL

Luozhi Zhang, Tingnan Bao, Yiyuan Xie, Thomas Aaron Gulliver, Fang Xu, Yuanchen Wang, Gaofeng Pan, Yichen Ye, Yandong Yang, Bin Duo
article en
22 citations

Abstract

Wireless communications can be improved by employing free space optical (FSO) channels. Since optical signals can only be transmitted via line-of-sight paths, UAVs are employed to forward data from a base station (BS) to remote users for urgent tasks using multi-hop mixed FSO/RF links. The UAVs employ the decode and forward protocol to relay data. The last UAV decodes and forwards the data to multiple users through RF links using non-orthogonal multiple access (NOMA). To improve fairness, a modified deep reinforcement learning (DRL) algorithm is used to optimize the transmit power allocation in real-time to minimize the maximum user decoding outage probability. Numerical results are presented to illustrate the system design tradeoffs. In addition, the validity of the proposed approach are verified by comparing it with exhaustive search algorithm.

IEEE Transactions on Vehicular TechnologyVol. 74(1)
Beijing Institute of Technology (CN), Southwest University (CN), University of Ottawa (CA), University of Victoria (CA), Chengdu University of Technology (CN), DHC Software (China) (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Chongqing
Openalex Percentile: Top 5%
Optical Wireless Communication Technologies
4.59
DOISourceOpenAlex
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