Robust Secure Beamforming Design for Multi-RIS-Aided MISO Systems With Hardware Impairments and Channel Uncertainties

To overcome the impact of information leakage, obstacle blocking, channel uncertainties, and hardware impairments (HWIs) in wireless communication systems, we design a robust secure transmission strategy for a multi-reconfigurable intelligent surface (RIS)-aided communication system with HWIs and ch...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on communications 2024-08, p.1-1
Hauptverfasser: Xu, Yongjun, Tian, Qinyu, Chen, Qianbin, Wu, Qingqing, Huang, Chongwen, Zhang, Haijun, Yuen, Chau
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:To overcome the impact of information leakage, obstacle blocking, channel uncertainties, and hardware impairments (HWIs) in wireless communication systems, we design a robust secure transmission strategy for a multi-reconfigurable intelligent surface (RIS)-aided communication system with HWIs and channel uncertainties, where a multi-antenna base station (BS) serves multiple wireless users aided by multiple RISs and overcomes information leakage caused by multiple eavesdroppers. Based on bounded channel uncertainties, a total transmit power minimization problem is investigated subject to the secrecy rates of users, the maximum transmit power of the BS, and the phase shifts of RISs. To deal with the formulated non-convex problem with parameter perturbations, it is transformed into a deterministic problem by using the worst-case approach, S-procedure, and successive convex approximation. Then, the problem is decomposed into an active beamforming and artificial noise subproblem and a passive beamforming subproblem. The subproblems are converted into convex ones via the semi-definite relaxation method, singular value decomposition, penalty function, and eigenvalue decomposition approaches. Finally, an iteration-based robust resource allocation algorithm is proposed. Simulation results verify that by deploying more RISs or increasing the number of reflection elements, the impacts of eavesdroppers and HWIs can be effectively decreased even with channel estimation errors.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2024.3451617