Joint RIS Phase Profile Design and Power Allocation for Parameter Estimation in Presence of Eavesdropping
원문 초록
We consider secure transmission of a deterministic complex-valued parameter vector from a transmitter to an intended receiver in the presence of an eavesdropper in a reconfigurable intelligent surface (RIS)-integrated environment. We aim to jointly optimize the RIS phase profile and the power allocation matrix at the transmitter to enhance the estimation accuracy at the intended receiver while limiting that at the eavesdropper. We utilize the trace of the Fisher information matrix (FIM), equivalently, the average Fisher information, as the estimation accuracy metric, and obtain its closed form expression for the intended receiver and the eavesdropper. Accordingly, the joint RIS phase profile and power allocation problem is formulated, and it is solved via alternating optimization. When the power allocation matrix is fixed during alternating optimization, the optimal RIS phase profile design problem is formulated as a non-convex problem and it is solved via semidefinite relaxation and rank reduction. When the RIS phase profile is fixed, a linear programming formulation is obtained for optimal power allocation. Via simulations, the effects of RIS phase design and power allocation are illustrated individually and jointly. Moreover, extensions are provided by considering the presence of line of sight paths in the environment and the availability of RIS elements with adjustable magnitudes.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots
Analytic estimation of parameters of stochastic volatility diffusion models with exponential-affine characteristic function for currency option pricing
A Simple Approximate Bayesian Inference Neural Surrogate for Stochastic Petri Net Models
Robust Spatiotemporal Epidemic Modeling with Integrated Adaptive Outlier Detection
IMC-PINN-FE: A Physics-Informed Neural Network for Patient-Specific Left Ventricular Finite Element Modeling with Image Motion Consistency and Biomechanical Parameter Estimation
Adjustment for Confounding using Pre-Trained Representations
토론
이 논문과 연결된 포럼 글이 아직 없습니다.