Deep Learning Based Secure Transmissions for the UAV-RIS Assisted Networks: Trajectory and Phase Shift Optimization

Jiawei Li, Dawei Wang, Jiankang Zhang, Osama Alfarraj, Yixin He, Saba Al-Rubaye, Keping Yu, Shahid Mumtaz

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper investigates the secure transmissions in the Unmanned Aerial Vehicle (UAV) communication network facilitated by a Reconfigurable Intelligent Surface (RIS). In this network, the RIS acts as a relay, forwarding sensitive information to the legitimate receiver while preventing eavesdropping. We optimize the positions of the UAV at different time slots, which gives another degree to protect the privacy information. For the proposed network, a secrecy rate maximization problem is formulated. The non-convex problem is solved by optimizing the RIS's phase shifts and UAV trajectory. The RIS phase shift optimization problem is converted into a series of subproblems, and a non-linear fractional programming approach is conceived to solve it. Furthermore, the first-order taylor expansion is employed to transform the UAV trajectory optimization into convex function, and then we use the deep Q-network (DQN) method to obtain the UAV's trajectory. Simulation results show that the proposed scheme enhances the secrecy rate by 18.7% compared with the existing approaches.

源语言英语
主期刊名GLOBECOM 2024 - 2024 IEEE Global Communications Conference
出版商Institute of Electrical and Electronics Engineers Inc.
1617-1622
页数6
ISBN(电子版)9798350351255
DOI
出版状态已出版 - 2024
活动2024 IEEE Global Communications Conference, GLOBECOM 2024 - Cape Town, 南非
期限: 8 12月 202412 12月 2024

出版系列

姓名Proceedings - IEEE Global Communications Conference, GLOBECOM
ISSN(印刷版)2334-0983
ISSN(电子版)2576-6813

会议

会议2024 IEEE Global Communications Conference, GLOBECOM 2024
国家/地区南非
Cape Town
时期8/12/2412/12/24

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