基于机器学习的物理层验证与相位损伤

IF 2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication Pub Date : 2024-11-23 DOI:10.1016/j.phycom.2024.102545

Zahra Ezzati Khatab , Abbas Mohammadi , Vahid Pourahmadi , Ali Kuhestani

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引用次数: 0

摘要

本文提出了一种基于机器学习（ML）的物理层验证（PLA）方法，利用了 I/Q 不平衡、相位噪声和载波频率偏移（CFO）损伤等物理特征。通过检查存在这些损伤时的相位信息，实现了所提出的 PLA 方法。系统模型包括一个使用正交频分复用（OFDM）调制的合法单天线发射器、一个合法多天线接收器和一个外部攻击者。我们对利用相位噪声和 CFO、利用 I/Q 不平衡和利用所有三种损伤的三种情况进行了综合研究。模拟结果表明，在上述情况下，接收器单天线的 PLA 精确度超过 98%。如果使用更多的接收天线，精度甚至还能提高。我们的结果突出表明，PLA 精度还受到 OFDM 子载波数量和接收信噪比的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A machine learning-based physical layer authentication with phase impairments

In this paper, we propose a machine learning (ML) based physical layer authentication (PLA) using the physical features of I/Q imbalance, phase noise and carrier frequency offset (CFO) impairments. By examining the phase information in the presence of these impairments, the proposed PLA method is implemented. The system model includes one legal single-antenna transmitter using orthogonal frequency-division multiplexing (OFDM) modulation, one legal multiple-antennas receiver and one external attacker. The comprehensive studies are conducted for three cases phase noise and CFO utilization, I/Q imbalance utilization, and all three impairments utilization. Our simulations show that the PLA accuracy for the mentioned these cases is more than 98% for single antenna at the receiver. The accuracy can be even improved by using more received antennas. Our results highlight that the PLA accuracy is also affected by the number of OFDM subcarriers and the received signal-to-noise-ratio.

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来源期刊

Physical Communication ENGINEERING, ELECTRICAL & ELECTRONICTELECO-TELECOMMUNICATIONS

CiteScore

5.00

自引率

9.10%

发文量

212

审稿时长

55 days

期刊介绍： PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published. Topics of interest include but are not limited to: Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.