Physical Layer Algorithm Design for Secure Communications in 6G Networks
Yun Wen
Physical-layer security (PLS) is expected to play a crucial role in next-generation wirelessnetworks, where ultra-reliable and adaptive communication is required. Emergingtechnologies, particularly reconfigurable intelligent surfaces (RIS), offer new opportunitiesto enhance PLS by enabling programmable control of the wireless propagation environment.Designing effective RIS-assisted PLS frameworks under dynamic and imperfectchannel conditions therefore becomes a critical research challenge.In the first part of this thesis, we investigate an RIS-assisted secure uncrewed aerialvehicle (UAV) communication scheme with multiple colluding eavesdroppers, where theaverage secrecy rate (ASR) is enhanced through joint optimization of the UAV trajectory,artificial noise (AN) and information beamforming, as well as RIS phase shifts. To tacklethe high complexity of the resulting non-convex multi-variable problem, a block coordinatedescent (BCD) framework combined with successive convex approximation (SCA) andmajorization–minimization (MM) techniques is developed. Simulation results demonstratesignificant ASR improvements over benchmark schemes.In the second part, we propose a simultaneously transmitting and reflecting (STAR)-RIS-enabled full-duplex (FD) secure communication scheme. The proposed design notonly suppresses self-interference (SI) to a level comparable to conventional self-interferencecancellation (SIC) techniques, but also intelligently controls the jamming power receivedby the eavesdropper, thereby enhancing secrecy capacity. The transmission and reflectionphase shifts of the STAR-RIS are jointly optimized with beamforming vectors to simultaneouslyfacilitate SI suppression and jamming enhancement. Numerical results confirmthe superiority of the proposed scheme under different STAR-RIS operation modes.In the third part, we develop a STAR-RIS-aided integrated sensing and communication(ISAC) framework to address secure transmission in scenarios where the eavesdropper’schannel state information (CSI) is unavailable. Artificial noise signals are leveragedto simultaneously perform sensing and prevent information leakage, while a self-refiningmechanism is introduced to iteratively improve eavesdropper localization accuracy. Thetransmit beamforming and STAR-RIS coefficients are jointly optimized to enhance sensingperformance, mitigate SI in FD operation, and strengthen jamming effectiveness. Simulationresults in both static and mobile scenarios demonstrate that the proposed designsignificantly improves secrecy capacity through sensing-assisted channel acquisition.
•Jan 1, 2026•0 citations