volume | PIER Journals

Abstract

Reconfigurable Intelligent Surfaces (RISs) can support physical-layer security in sixth-generation (6G) vehicular networks by reconfiguring the wireless channel. However, RIS-assisted vehicular links are affected by Doppler-induced channel aging, imperfect channel state information (CSI), feedback delay, and finite-resolution phase control. This paper develops a bounded-uncertainty Doppler-Aware Robust Quantized Alternating Optimization (DA-RQ-AO) framework for secure RIS-assisted 6G vehicular communication under imperfect and delayed CSI. The system includes a multi-antenna transmitter, a legitimate receiver, a passive eavesdropper, and a roadside RIS. A robustness-aware secrecy-rate surrogate is formulated by jointly optimizing the transmit beamformer and quantized RIS phase shifts under power, unit-modulus, CSI-uncertainty, and discrete-phase constraints. The non-convex problem is addressed through alternating optimization, where the beamformer is updated using a conservative generalized eigenvector-based solution, and the RIS phase vector is refined using an explicitly derived chain-rule-based phase-gradient update followed by finite-resolution quantization with an acceptance safeguard. Numerical results show improved secrecy rate and lower secrecy outage probability than no-RIS, random-RIS, Q-AO, and robust AO benchmarks. For N=64, the proposed scheme improves secrecy rate by 118.8% over no-RIS and 73.8% over random RIS, while 2-bit RIS control shows only 5.94% loss relative to continuous phase control.

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Mr. Ravi Patel

Dr. Atul Patel