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Enabling Secure Wireless Communications via Intelligent Reflecting Surfaces (1904.09573v4)

Published 21 Apr 2019 in cs.IT and math.IT

Abstract: In this paper, we propose to utilize intelligent reflecting surfaces (IRSs) for enhancing the physical layer security of wireless communications systems. In particular, an IRS-assisted secure wireless system is considered, where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. To maximize the secrecy rate, both the beamformer at the transmitter and the IRS phase shifts are jointly optimized. Based on the block coordinate descent (BCD) and minorization maximization (MM) techniques, two efficient algorithms are developed to solve the resulting non-convex optimization problem for small- and large-scale IRSs, respectively. Simulation results show that IRSs can significantly improve physical layer security if the proposed algorithms are employed. Furthermore, we reveal that deploying large-scale IRSs is more efficient than enlarging the antenna array size of the transmitter for both boosting the secrecy rate and enhancing the energy efficiency.

Citations (273)

Summary

  • The paper demonstrates IRS-enhanced security by jointly optimizing beamforming and phase shifts to maximize secrecy rates.
  • It introduces BCD and MM algorithms to efficiently solve non-convex optimization challenges across small and large-scale IRS deployments.
  • Simulation results show that larger IRSs yield superior security performance and energy savings compared to traditional methods.

Secure Wireless Communications via Intelligent Reflecting Surfaces

The paper "Enabling Secure Wireless Communications via Intelligent Reflecting Surfaces" by Yu, Xu, and Schober presents an examination of Intelligent Reflecting Surfaces (IRSs) as a method to enhance physical layer security in wireless communications systems. The authors address the challenge of securing information in a scenario where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. The paper focuses on optimizing the secrecy rate by jointly optimizing the beamforming at the transmitter and the phase shifts at the IRS. This research is motivated by the need for more energy-efficient and cost-effective solutions compared to traditional methods such as cooperative relaying and noise-aided beamforming.

Key Contributions

In the proposed setup, IRSs are integrated into the wireless systems to intelligently adjust the propagation environment, enhancing the signal-to-noise ratio (SNR) at the legitimate receiver and minimizing eavesdropper intercepts. Two algorithms are presented utilizing block coordinate descent (BCD) and minorization maximization (MM) to address the non-convex optimization challenge. The authors distinctly approach optimization for both cases: small-scale and large-scale IRSs.

The innovation lies in the joint optimization strategy, wherein the beamformer and the phase shifts are locally optimized, setting this paper apart from traditional IRS research focusing on non-security-related performance metrics. The algorithms showcase significant improvements in both security and energy efficiency, outperforming traditional systems without IRSs or with large antenna arrays. Particularly, the results highlight that deploying larger IRSs yields better performance gains than merely increasing the transmitter's antenna size, thus emphasizing energy efficiency.

Analytical Approach and Results

The presented solutions involve reformulating the beamforming vector's design problem into a generalized eigenvalue problem, yielding a closed-form solution. For small-scale IRSs, an element-wise BCD method achieves each phase shift's maximal enhancement iteratively while ensuring rapid convergence for smaller configurations. For large-scale IRS configurations, the MM technique optimizes the phase shifts in parallel, trading off individual phase precision for computational efficiency to cope with the increasing dimensions of IRSs.

Simulation results underline the substantial gain in secrecy rates brought by IRS implementations. The comparative analysis also reveals that the security improvements from integrating IRSs exceed those from increasing antenna size alone, especially in massive scale setups. The paper concludes that incorporating IRSs offers a strategic advantage for secure wireless networks, promising better secrecy performance while keeping power consumption low due to the passive nature of IRSs.

Implications and Future Directions

This research paves the way for advanced secure communication systems by leveraging the passive capabilities and the effective manipulation of wireless propagation through IRSs. From a theoretical perspective, the combination of BCD and MM algorithms enriches the toolkit available for handling complex non-convex optimization problems prevalent in IRS deployments.

Future explorations might delve into real-world IRS implementations' constraints, such as imperfect channel state information (CSI) acquisition and phase noise. Such studies would enhance the robustness of IRS-assisted systems. Additionally, expanding this research to multiuser environments or extending IRS utility to dynamic scenarios could unlock further applications of IRSs in practical secure wireless systems.

In summary, this paper illustrates how intelligent utilization of reflecting surfaces enhances wireless security, presenting a scalable solution to optimize the secrecy performance in emerging communications networks.