[Paper Review] Reconfigurable Intelligent Surface Aided Secure Transmission: Outage-Constrained Energy-Efficiency Maximization.

Zongze Li, Shuai Wang+2 more|arXiv (Cornell University)|Oct 29, 2020

Advanced Wireless Communication Technologies4 citations

TL;DR

This paper proposes a novel energy-efficient secure transmission scheme using reconfigurable intelligent surfaces (RIS) under imperfect eavesdropper channel state information. By transforming probabilistic constraints and decoupling variables, it employs alternating difference-of-convex programming and semidefinite relaxation to optimize phase shifts, power allocation, and transmission rates, achieving high energy efficiency. A low-complexity first-order algorithm reduces computation time by two orders of magnitude while matching performance, significantly outperforming random, fixed, and CSI-ignoring RIS schemes.

ABSTRACT

Reconfigurable intelligent surface (RIS) has the potential to significantly enhance the network secure transmission performance by reconfiguring the wireless propagation environment. However, due to the passive nature of eavesdroppers and the cascaded channel brought by the RIS, the eavesdroppers' channel state information is imperfectly obtained at the base station. Under the channel uncertainty, the optimal phase-shift, power allocation, and transmission rate design for secure transmission is currently unknown due to the difficulty of handling the probabilistic constraint with coupled variables. To fill this gap, this paper formulates a problem of energy-efficient secure transmission design while incorporating the probabilistic constraint. By transforming the probabilistic constraint and decoupling variables, the secure energy efficiency maximization problem can be solved via alternatively executing difference-of-convex programming and semidefinite relaxation technique. To scale the solution to massive antennas and reflecting elements scenario, a fast first-order algorithm with low complexity is further proposed. Simulation results show that the proposed first-order algorithm achieves identical performance to the conventional method but saves at least two orders of magnitude in computation time. Moreover, the resultant RIS aided secure transmission significantly improves the energy efficiency compared to baseline schemes of random phase-shift, fixed phase-shift, and RIS ignoring CSI uncertainty.

Motivation & Objective

• Address the challenge of secure transmission in RIS-assisted networks with imperfect and uncertain eavesdropper channel state information.
• Formulate a secure energy efficiency maximization problem under probabilistic quality-of-service constraints due to channel uncertainty.
• Design joint optimization of RIS phase shifts, power allocation, and transmission rates to maximize energy efficiency under imperfect CSI.
• Develop a scalable, low-complexity first-order algorithm for massive MIMO and large-scale RIS deployments.
• Evaluate performance gains over baseline schemes such as random phase-shift, fixed phase-shift, and RIS without CSI uncertainty handling.

Proposed method

• Transform the probabilistic constraint into a deterministic equivalent using convex approximation techniques to handle channel uncertainty.
• Decouple the coupled variables in the optimization problem through alternating optimization of phase shifts, power allocation, and rates.
• Apply difference-of-convex (DC) programming to handle the non-convexity in the phase-shift optimization subproblem.
• Use semidefinite relaxation (SDR) to approximate the non-convex subproblems and obtain near-optimal solutions.
• Design a fast first-order algorithm with low computational complexity to scale to massive antenna and reflecting element scenarios.
• Iteratively solve the subproblems using sequential convex approximation, ensuring convergence and scalability.

Experimental results

Research questions

• RQ1 How can energy efficiency be maximized in RIS-aided secure transmission under imperfect eavesdropper CSI?
• RQ2 What is the optimal joint design of phase shifts, power allocation, and transmission rates under probabilistic secrecy outage constraints?
• RQ3 How can the coupled non-convex optimization problem with probabilistic constraints be effectively decoupled and solved?
• RQ4 Can a low-complexity first-order algorithm achieve comparable performance to high-complexity methods while scaling to large-scale systems?
• RQ5 What performance gain does the proposed scheme offer over baseline RIS configurations like random or fixed phase shifts?

Key findings

• The proposed first-order algorithm achieves identical performance to the conventional method but reduces computation time by at least two orders of magnitude.
• The RIS-aided secure transmission scheme significantly improves energy efficiency compared to baseline schemes, including random phase-shift, fixed phase-shift, and RIS ignoring CSI uncertainty.
• The joint optimization of phase shifts, power allocation, and transmission rates under probabilistic constraints leads to a substantial improvement in secure energy efficiency.
• The transformation of probabilistic constraints and variable decoupling enable effective handling of the non-convex, coupled optimization problem.
• The proposed method maintains high performance even in large-scale scenarios with massive antennas and reflecting elements.
• The use of DC programming and semidefinite relaxation enables convergence to high-quality solutions despite the non-convex nature of the problem.