Secure Wireless Communication via Intelligent Reflecting Surface (1905.10770v1)

Abstract: An intelligent reflecting surface (IRS) can adaptively adjust the phase shifts of its reflecting units to strengthen the desired signal and/or suppress the undesired signal. In this letter, we investigate an IRS-aided secure wireless communication system where a multi-antenna access point (AP) sends confidential messages to a single-antenna user in the presence of a single-antenna eavesdropper. In particular, we consider the challenging scenario where the eavesdropping channel is stronger than the legitimate communication channel and they are also highly correlated in space. We maximize the secrecy rate of the legitimate communication link by jointly designing the AP's transmit beamforming and the IRS's reflect beamforming. While the resultant optimization problem is difficult to solve, we propose an efficient algorithm to obtain high-quality suboptimal solution for it by applying the alternating optimization and semidefinite relaxation methods. Simulation results show that the proposed design significantly improves the secrecy communication rate for the considered setup over the case without using the IRS, and outperforms a heuristic scheme.

• The paper demonstrates an IRS-assisted approach that jointly optimizes active transmit and passive reflect beamforming to enhance secrecy rate.
• The proposed alternating optimization algorithm uses semidefinite relaxation and Gaussian randomization to overcome non-convex constraints.
• Simulations reveal significant secrecy rate improvements with increased AP power and more IRS units, achieving near-optimal performance.

Secure Wireless Communication via Intelligent Reflecting Surface

The paper "Secure Wireless Communication via Intelligent Reflecting Surface" by Miao Cui, Guangchi Zhang, and Rui Zhang explores the utilization of Intelligent Reflecting Surfaces (IRS) to enhance secure wireless communication. Specifically, the authors address the challenging scenario where the communication channel to the intended user is weaker than the eavesdropping channel, and these channels are highly correlated in space.

In traditional wireless communication, the eavesdropping threat increases when the legitimate channel conditions are unfavorable compared to the eavesdropper's channel. To mitigate this, the IRS can adaptively adjust its phase shifts to amplify the desired signals and suppress undesired ones. The core contribution of this paper is the joint optimization of active transmit beamforming at the multi-antenna access point (AP) and passive reflect beamforming at the IRS to maximize the secrecy rate of the wireless communication link.

System Model and Assumptions

The system comprises a multi-antenna AP, a single-antenna legitimate user, and a single-antenna eavesdropper. An IRS with numerous low-cost, passive reflecting units is deployed to assist in secure communication. The authors assume perfect channel state information (CSI) availability at the AP and IRS for the optimal design of transmit and reflect beamforming.

Optimization Problem

The objective is to maximize the secrecy rate, defined as the difference between the achievable rates of the legitimate link and the eavesdropper link. The problem formulation is non-convex due to the coupling of variables in the transmit and reflect beamforming vectors and the unit-modulus constraints of the IRS phase shifts. To address this, the authors propose an alternating optimization algorithm using semidefinite relaxation (SDR) and Gaussian randomization techniques.

Proposed Algorithm

The algorithm iteratively optimizes the AP's transmit beamforming while keeping the IRS phase shifts fixed, and then vice versa, until convergence. The main steps include:

1. Transmit Beamforming Optimization: Given the IRS phase shifts, the AP’s beamforming vector is derived by solving a generalized eigenvalue problem.
2. Reflect Beamforming Optimization: Given the AP’s beamforming vector, the IRS’s phase shifts are optimized by solving a semidefinite program (SDP) followed by Gaussian randomization to ensure the unit-modulus condition.

Simulation Results

Simulations demonstrate significant improvements in secrecy rate using IRS. Key findings include:

• Transmit Power Impact: The secrecy rate increases significantly with higher AP transmit power when IRS is used, unlike the minimal gains observed without IRS.
• Number of Reflecting Units: An increase in the number of IRS reflecting units leads to substantial improvements in secrecy rate. The joint design of AP beamforming and IRS phase shifts outperforms heuristic schemes by a considerable margin.
• Near-Optimal Performance: The proposed algorithm achieves performance close to the secrecy rate upper bound derived using relaxed SDR-based optimization.

Practical and Theoretical Implications

Practically, the proposed IRS-assisted design offers a scalable solution to enhance security in wireless networks, especially in environments where eavesdropping threats are pronounced due to spatial correlation and channel strength disparities. Theoretically, the work extends the understanding of physical-layer security by integrating recent advancements in IRS technology, which could pave the way for further research in optimizing large-scale IRS deployments, dynamic IRS configurations based on real-time CSI, and multi-user scenarios.

Future Developments

Future work may explore:

• Adaptive Beamforming Strategies: Real-time adaptation to dynamic environmental changes remains an open challenge.
• Multi-User Interference Management: Extending the design to support multiple legitimate users and multiple eavesdroppers.
• Hardware Realizations: Investigating practical IRS implementations and the associated hardware constraints.

In conclusion, this paper provides a comprehensive analysis and a promising solution for secure wireless communication using IRS, establishing a foundation for future exploration and practical deployment in enhancing physical-layer security in wireless networks.