Abstract
As a novel reconfigurable intelligent surface (RIS) architecture, the simultaneous transmitting and reflecting RIS (STAR-RIS) provides full-space coverage and has strong potential to enhance communication security in future 6G networks through optimized beamforming. Motivated by this, we investigate the physical-layer security issues in STAR-RIS-assisted multi-user multiple input and single output (MISO) communication systems. Considering the difficulty in obtaining the channel state information (CSI) of eavesdropping users, we propose a robust beamforming optimization scheme with artificial noise (AN) under imperfect CSI. Specifically, we aim to maximize the system weighted sum secrecy rate by jointly optimizing the base station (BS) beamforming, AN vector and STAR-RIS transmission-reflection coefficients, subject to system transmit power and user information rate constraints. Due to the non-convex constraints and strong coupling of variables, the problem is difficult to solve directly. To address this, we propose an alternating optimization algorithm using successive convex approximation (SCA) and penalized concave convex process (PCCP), and utilize S-procedure to handle the uncertainty of eavesdropping CSI. Simulation results show that the proposed algorithm exhibits excellent convergence and robustness. Moreover, it outperforms other benchmark schemes in terms of secrecy performance.
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Vehicular Technology |
| DOIs | |
| Publication status | Accepted/In press - 2026 |
| Externally published | Yes |
Keywords
- Beamforming
- Robust optimization
- Secure communication
- reconfigurable intelligent surface (RIS)
- simultaneous transmitting and reflecting RIS (STAR-RIS)
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