RIS辅助通信场景中一种基于展开信道的物理层密钥生成方法

杨立君; 陈子硕; 陆海涛; 郭林

doi:10.11999/JEIT240988

RIS辅助通信场景中一种基于展开信道的物理层密钥生成方法

doi: 10.11999/JEIT240988

杨立君¹,
陈子硕¹,
陆海涛^{2, 3},
郭林^4, ,

1.
南京邮电大学物联网学院南京 210003
2.
中兴通讯股份有限公司深圳 518057
3.
深圳市5G接入网安全技术研究及应用重点实验室深圳 518055
4.
南京邮电大学现代邮政学院南京 210003

基金项目: 国家自然科学基金( 62372244, 62172235)，中兴通讯产学研(2023ZTE08-02)，国家重点研发计划(2021YFB3101100)，江苏省重点研发计划重点项目(BE2023025)，南京邮电大学校级自然科学基金(NY222132)，江苏省研究生科研与实践创新计划项目(KYCX23_1057)

详细信息

作者简介:
杨立君：女，副教授，研究方向为无线网络与信息安全

陈子硕：男，硕士生，研究方向为物理层密钥生成

陆海涛：男，高级工程师，研究方向为 5G/B5G/6G 通信安全技术

郭林：男，讲师，研究方向为MIMO天线系统及安全技术

通讯作者:
郭林　guolin@njupt.edu.cn

中图分类号: TN92
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出版历程
- 收稿日期: 2024-11-05
- 修回日期: 2025-02-20
- 网络出版日期: 2025-02-24

An Unfolded Channel-based Physical Layer Key Generation Method For Reconfigurable Intelligent Surface-Assisted Communication Systems

YANG Lijun¹,
CHEN Zishuo¹,
LU Haitao^{2, 3},
GUO Lin^{4
, ,}

1.
School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2.
ZTE Corporation, Shenzhen 518057, China
3.
Shenzhen Key Laboratory of 5G RAN Security Technology Research and Application, Shenzhen 518055, China
4.
School of Modern Post, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Funds: The National Natural Science Foundation of China(62372244, 62172235), The ZTE Industry-university-Research Fund (2023ZTE08-02), The National Key Research and Development Program of China(2021YFB3101100), The Primary Research & Development Plan of Jiangsu Province (BE2023025), The Natural Science Foundation of Nanjing University of Posts and Telecommunications (NY222132), The Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX23_1057)

摘要

摘要: 在可重构智能超表面(RIS)辅助的通信场景中，基站(BS)与RIS的位置通常保持相对静止，而终端(UE)则处于移动状态。两段时变性不一致的信道级联会引起信道信息熵的损失，从而造成物理层密钥容量的劣化。针对该问题，该文首先从理论上分析了信道级联对密钥容量造成的劣化效应；为了缓解这一效应，该文提出一种基于展开信道的密钥生成方法，通过展开信道估计和相移矩阵的分离，充分利用了展开信道的信息熵；最后对级联信道劣化效应进行了仿真验证，并对所提出的方案进行了性能评估。仿真结果显示，与直接采用级联信道作为密钥源相比，该文所提方案在2 dB信噪比条件下，密钥生成率提升了72%。这一结果表明，该文方案能有效改善信道劣化效应，显著提高密钥生成效率。
- 物理层密钥生成 /
- 智能超表面 /
- 展开信道
Abstract: Objective Physical Layer Key Generation (PLKG) is an emerging key generation technique that exploits the reciprocity, time variability, and spatial decorrelation properties of wireless channels to enable real-time key generation. This technique has the potential to achieve one-time-pad encryption and demonstrates resilience against quantum attacks. PLKG typically consists of four key steps: channel probing, preprocessing and quantization, information reconciliation, and privacy amplification. Proper preprocessing can enhance channel reciprocity, remove redundancy, improve the Key Generation Rate (KGR), and reduce the Key Disagreement Rate (KDR). Reconfigurable Intelligent Surfaces (RIS) offer advantages such as low cost, low power consumption, and ease of deployment. They enable the manipulation of incident signals in terms of amplitude, phase, and polarization, thus constructing an intelligent communication environment. This provides a novel approach to mitigating the limitations of key generation imposed by the channel environment. However, existing preprocessing methods, such as Principal Component Analysis (PCA), Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), and nonlinear processing, treat channel data as a whole for noise reduction and redundancy elimination. These approaches do not account for the key capacity loss caused by channel cascading in RIS-assisted communication systems, thereby limiting KGR. To address this issue, this paper proposes a novel PLKG protocol based on unfolded channels, aiming to mitigate the key capacity loss induced by channel cascading and thereby enhance KGR. Methods This paper first derives the degradation effect of channel cascading on the key generation rate through entropy theory and validates it via theoretical simulations. Next, a PLKG scheme designed for RIS-assisted communication scenarios is proposed, with improvements in both channel probing and preprocessing. In the channel probing phase, a two-stage channel estimation approach is designed. In the first stage, the PARAllel FACtor (PARAFAC) channel estimation method is employed, utilizing the inherent multidimensional information structure in Multiple Input Multiple Output (MIMO) communication systems to construct a tensor, which is then used to estimate the baseline unfolded channel via the Alternating Least Squares (ALS) algorithm. In the second stage, the RIS phase shift matrix is randomized, and the Least Squares (LS) method is used to estimate the cascaded channel, thereby introducing an additional source of randomness for key generation. In the channel preprocessing phase, the baseline unfolded channel obtained from the two-stage channel estimation is used to separate the cascaded channel into the unfolded channel and the RIS phase shift matrix. Conventional methods such as PCA, DCT, and Wavelet Transform (WT) are then applied to remove noise and redundancy from the obtained data. By utilizing both the unfolded channel and the RIS phase shift matrix as joint key sources, the proposed scheme mitigates the KGR degradation caused by channel cascading, thereby improving KGR while ensuring a low KDR. Results and Discussions A Rayleigh channel MIMO communication system model is established for experimentation. The proposed two-stage channel estimation method is used to separate the cascaded channel into the unfolded channel and the RIS phase shift matrix. Subsequently, three preprocessing methods—PCA, DCT, and WT—are applied to the cascaded channel, unfolded channel, and RIS phase shift matrix for noise reduction and decorrelation. The extracted channel features are then quantized, followed by information reconciliation and privacy amplification. The experiment compares two key generation approaches: one using the cascaded channel as the key source and the other using the unfolded channel and RIS phase shift matrix as joint key sources. Simulation results shows that the proposed scheme achieved a 72% KGR improvement at 2 dB Signal to Noise Ratio (SNR) (Fig.8). Among the preprocessing methods, DCT demonstrates the highest KGR and the lowest KDR (Fig.9, Fig.10). Additionally, experiments on the number of RIS configuration matrices indicates that increasing the number beyond eight yielded diminishing returns in KGR improvement. Therefore, an optimal range of 8–10 configuration matrices is recommended. Furthermore, the computational complexity of the PARAFAC channel estimation method is analyzed. The feasibility of real-time key generation is validated by considering channel coherence time, algorithm complexity, and communication protocol frame intervals. Conclusions This paper proposes a PLKG scheme that employs the PARAFAC channel estimation method to estimate the unfolded channel and the LS method to estimate the cascaded channel. Based on these estimations, the cascaded channel is decomposed into the unfolded channel and the RIS phase shift matrix during preprocessing. By using the unfolded channel and the RIS phase shift matrix as joint key sources, the proposed method mitigates the degradation of KGR caused by channel cascading. Compared with conventional PLKG schemes that use the cascaded channel as the key source, the proposed method achieves a 72% KGR improvement at a 2dB SNR while maintaining a low KDR. However, despite its ability to enhance KGR, the proposed scheme still faces challenges such as excessive pilot overhead and computational limitations. Future work should focus on optimizing overhead reduction to further enhance its practicality.
- Physical Layer Key Generation (PLKG) /
- Reconfigurable Intellectual Surface (RIS) /
- Unfolded channel

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图 1 系统模型

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图 2 方案流程框图

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图 3 1个相干时间内进行的2阶段信道估计的时间轴

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图 4 基于PARAFAC分解的信道估计方法在1个相干时间内的时间块划分

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图 5 第1阶段信道估计的时间轴

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图 6 由P轮信道估计所得接收信号经过导频逆运算构建的3维张量Z

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图 7 展开信道与级联信道密钥容量对比

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图 8 不同方案的密钥生成率对比图

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图 9 以DCT去冗余时两种方案密钥不一致率对比

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图 10 本文方案在3种去冗余方法下的密钥不一致率

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图 11 密钥生成率随RIS配置矩阵数量的变化图

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