Artificial Noise Versus Artificial Noise Elimination: Redefining Scaling Laws of Physical Layer Security

2026-03-09

AI Summary

This study investigates the detrimental impact of artificial noise elimination (ANE) on the physical-layer security performance of artificial noise (AN) schemes, with a focus on the sustainability of secrecy rates in multi-antenna eavesdropping channels. Employing information-theoretic methods, the work establishes, for the first time, scaling laws for both average and instantaneous secrecy rates to quantitatively characterize the erosion of AN’s security gains due to ANE. The key contribution lies in uncovering a critical relationship among the numbers of antennas at the transmitter, legitimate receiver, and eavesdropper: secure communication may fail when the eavesdropper’s antenna count exceeds twice that of the transmitter. Furthermore, the paper provides a sufficient condition under which AN remains effective despite ANE. These findings offer theoretical foundations and practical design guidelines for robust physical-layer security systems resilient to ANE attacks.

Technology Category

• Philosophy and Ethics of AI: Privacy & Security
• Machine Learning: Hardware-aware ML
• Multiagent Systems: Adversarial Agents

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Measurement, analysis, and circumvention of Web censorship

Abstract

Artificial noise (AN) is a key physical-layer security scheme for wireless communications over multiple-input multiple-output wiretap channels. Recently, artificial noise elimination (ANE) has emerged as a strategy to mitigate the impact of AN on eavesdroppers. However, the influence of ANE on the secrecy rate when counteracting AN has not been investigated. In this paper, we address this issue by establishing scaling laws for both average and instantaneous secrecy rates in the presence of AN and ANE. Based on the scaling laws, several derived corollaries provide insights into the mutual constraints between the number of transmit antennas, receive antennas, and antennas at eavesdroppers, revealing the interplay between these factors. A key corollary reveals that when the eavesdropper possesses more than twice as many antennas as the transmitter, secure communication may no longer be guaranteed. Additionally, by comparing scenarios where ANE counteracts AN with those where AN is not employed, this study identifies sufficient conditions under which AN remains effective. Finally, the derived secrecy rates provide guidelines for system design, even in the presence of advanced ANE countermeasures implemented by the eavesdropper.

Problem

• Artificial Noise
• Artificial Noise Elimination
• Physical Layer Security
• Secrecy Rate
• MIMO Wiretap Channel

Innovation

• Artificial Noise
• Artificial Noise Elimination
• Scaling Laws
• Physical Layer Security
• MIMO Wiretap Channel