article · Security and Privacy
Wireless networks face security challenges from mobile eavesdroppers, particularly when real-time channel state information is unavailable. A dual reconfigurable intelligent surface framework addresses secrecy energy efficiency in downlink multiple-input single-output communications under statistical channel conditions. Instead of assuming instant eavesdropper tracking, the channel is modelled using a statistical mean-covariance representation alongside an uncertainty-aware robustness penalty. To solve the complex non-convex optimisation problem involving coupled beamforming and reflective surface phases, a low-complexity alternating optimisation algorithm relies on Dinkelbach fractional programming. Performance assessments show the dual-surface setup reaches a secrecy energy efficiency of 9.62 megabits per joule at 30 dBm transmit power. This design outperforms single-surface equivalents while approaching the performance of benchmarks that assume perfect channel information, remaining effective when accounting for operational overhead.
Securing wireless transmissions against mobile eavesdroppers typically demands unrealistic, real-time knowledge of an interceptor's movements. By relying on statistical channel estimates, this approach enables energy-efficient, secure communications without needing continuous surveillance of unauthorised devices. This reduces the energy needed to protect sensitive wireless data in dynamic environments.
This work offers an algorithmic foundation for telecommunications equipment manufacturers and network operators developing energy-conscious, secure wireless communications. The research represents early-stage, algorithm-level design evaluated through mathematical modelling and simulation rather than physical hardware trials, meaning real-world deployment would require extensive practical prototyping and integration into future wireless standards.
AI-generated from the published abstract. Always read the original work before citing.
ABSTRACT In this paper, the secrecy energy efficiency (SEE) maximization problem is investigated in a dual‐reconfigurable intelligent surface (RIS)‐assisted downlink multiple‐input single‐output (MISO) system with an intermittently active mobile eavesdropper under statistical channel state information (CSI). The proposed framework models the eavesdropper channel using a statistical mean‐covariance representation, rather than conventional approaches that assume instantaneous eavesdropper CSI. A deterministic secrecy‐rate surrogate is obtained based on the expected eavesdropper signal‐to‐interference‐plus‐noise ratio (SINR) and an uncertainty‐aware robustness penalty. The resulting SEE optimization problem is nonconvex due to the fractional objective function, coupled beamforming and RIS phase variables, and unit‐modulus RIS constraints. To address this issue, a low‐complexity alternating optimization algorithm is designed using Dinkelbach fractional programming. The results demonstrate that the proposed dual‐RIS statistical‐CSI framework achieves 9.62 Mbit/J SEE at 30 dBm transmit power, outperforming the single‐RIS statistical‐CSI benchmark while approaching the perfect‐CSI dual‐RIS benchmark. Overhead‐aware evaluation further confirms the effectiveness of the proposed dual‐RIS framework under practical operating conditions.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1002/spy2.70244
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
