RIS輔助通信場景中一種基于展開信道的物理層密鑰生成方法

楊立君; 陳子碩; 陸海濤; 郭林

doi:10.11999/JEIT240988

RIS輔助通信場景中一種基于展開信道的物理層密鑰生成方法

doi: 10.11999/JEIT240988 cstr: 32379.14.JEIT240988

楊立君¹,
陳子碩¹,
陸海濤^{2, 3},
郭林^4, ,

1.
南京郵電大學(xué)物聯(lián)網(wǎng)學(xué)院南京 210003
2.
中興通訊股份有限公司深圳 518057
3.
深圳市5G接入網(wǎng)安全技術(shù)研究及應(yīng)用重點(diǎn)實(shí)驗(yàn)室深圳 518055
4.
南京郵電大學(xué)現(xiàn)代郵政學(xué)院南京 210003

基金項(xiàng)目: 國家自然科學(xué)基金( 62372244, 62172235)，中興通訊產(chǎn)學(xué)研(2023ZTE08-02)，國家重點(diǎn)研發(fā)計(jì)劃(2021YFB3101100)，江蘇省重點(diǎn)研發(fā)計(jì)劃重點(diǎn)項(xiàng)目(BE2023025)，南京郵電大學(xué)校級自然科學(xué)基金(NY222132)，江蘇省研究生科研與實(shí)踐創(chuàng)新計(jì)劃項(xiàng)目(KYCX23_1057)

詳細(xì)信息

作者簡介:
楊立君：女，副教授，研究方向?yàn)闊o線網(wǎng)絡(luò)與信息安全

陳子碩：男，碩士生，研究方向?yàn)槲锢韺用荑€生成

陸海濤：男，高級工程師，研究方向?yàn)?5G/B5G/6G 通信安全技術(shù)

郭林：男，講師，研究方向?yàn)镸IMO天線系統(tǒng)及安全技術(shù)

通訊作者:
郭林　guolin@njupt.edu.cn

中圖分類號: TN92
計(jì)量
- 文章訪問數(shù): 212
- HTML全文瀏覽量: 119
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2024-11-05
- 修回日期: 2025-02-20
- 網(wǎng)絡(luò)出版日期: 2025-02-24
- 刊出日期: 2025-02-28

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: 在可重構(gòu)智能超表面(RIS)輔助的通信場景中，基站(BS)與RIS的位置通常保持相對靜止，而終端(UE)則處于移動狀態(tài)。兩段時(shí)變性不一致的信道級聯(lián)會引起信道信息熵的損失，從而造成物理層密鑰容量的劣化。針對該問題，該文首先從理論上分析了信道級聯(lián)對密鑰容量造成的劣化效應(yīng)；為了緩解這一效應(yīng)，該文提出一種基于展開信道的密鑰生成方法，通過展開信道估計(jì)和相移矩陣的分離，充分利用了展開信道的信息熵；最后對級聯(lián)信道劣化效應(yīng)進(jìn)行了仿真驗(yàn)證，并對所提出的方案進(jìn)行了性能評估。仿真結(jié)果顯示，與直接采用級聯(lián)信道作為密鑰源相比，該文所提方案在2 dB信噪比條件下，使密鑰生成率提升了72%。這一結(jié)果表明，該文方案能有效改善信道劣化效應(yīng)，顯著提高密鑰生成效率。
- 物理層密鑰生成 /
- 智能超表面 /
- 展開信道
Abstract: Objective Physical Layer Key Generation (PLKG) is an emerging technique that leverages the reciprocity, time variability, and spatial decorrelation properties of wireless channels to enable real-time key generation. This method offers potential for one-time-pad encryption and resilience against quantum attacks. PLKG typically includes four key steps: channel probing, preprocessing and quantization, information reconciliation, and privacy amplification. Proper preprocessing can improve channel reciprocity, eliminate redundancy, increase the Key Generation Rate (KGR), and reduce the Key Disagreement Rate (KDR). Reconfigurable Intelligent Surfaces (RIS) present advantages such as low cost, low power consumption, and ease of deployment. By manipulating incident signals in terms of amplitude, phase, and polarization, RIS enables the creation of intelligent communication environments, offering a novel approach to mitigating channel limitations in key generation. However, current preprocessing methods like Principal Component Analysis (PCA), Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), and nonlinear processing typically treat channel data as a whole for noise reduction and redundancy removal. These methods overlook the key capacity loss induced by channel cascading in RIS-assisted systems, limiting KGR. To address this challenge, this paper proposes a novel PLKG protocol based on unfolded channels, aimed at mitigating key capacity loss due to channel cascading, thereby enhancing KGR. Methods This paper first derives the degradation effect of channel cascading on the KGR using entropy theory and validates it through theoretical simulations. A PLKG scheme tailored for RIS-assisted communication scenarios is then proposed, with enhancements in both channel probing and preprocessing. In the channel probing phase, a two-stage channel estimation approach is introduced. The first stage employs the PARAllel FACtor (PARAFAC) method for channel estimation, utilizing the multidimensional information structure inherent in Multiple Input Multiple Output (MIMO) communication systems to construct a tensor. This tensor is 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 applied to estimate the cascaded channel, introducing an additional source of randomness for key generation. In the channel preprocessing phase, the baseline unfolded channel derived from the two-stage 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 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, enhancing KGR while maintaining 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. Three preprocessing methods—PCA, DCT, and WT—are then applied to the cascaded channel, unfolded channel, and RIS phase shift matrix for noise reduction and decorrelation. The extracted channel features are 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 show that the proposed scheme achieves a 72% improvement in KGR at a 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, Fig. 11, Fig. 11). Additionally, experiments on the number of RIS configuration matrices indicate that increasing the number beyond eight yields diminishing returns in KGR improvement. Thus, an optimal range of 8–10 configuration matrices is recommended. Furthermore, the computational complexity of the PARAFAC channel estimation method is analyzed, and 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 utilizes the PARAFAC channel estimation method to estimate the unfolded channel and the LS method to estimate the cascaded channel. During preprocessing, the cascaded channel is decomposed into the unfolded channel and the RIS phase shift matrix. By using both 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% improvement in KGR at a 2 dB SNR, while maintaining a low KDR. However, despite enhancing KGR, the proposed scheme still faces challenges such as excessive pilot overhead and computational limitations. Future work should focus on optimizing overhead reduction to improve its practicality.
- Physical Layer Key Generation (PLKG) /
- Reconfigurable Intellectual Surface (RIS) /
- Unfolded channel

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圖 1 系統(tǒng)模型

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圖 2 方案流程框圖

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圖 3 1個(gè)相干時(shí)間內(nèi)進(jìn)行的2階段信道估計(jì)的時(shí)間軸

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圖 4 基于PARAFAC分解的信道估計(jì)方法在1個(gè)相干時(shí)間內(nèi)的時(shí)間塊劃分

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圖 5 第1階段信道估計(jì)的時(shí)間軸

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圖 6 由P輪信道估計(jì)所得接收信號經(jīng)過導(dǎo)頻逆運(yùn)算構(gòu)建的3維張量Z

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圖 7 展開信道與級聯(lián)信道密鑰容量對比

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圖 8 不同方案的密鑰生成率對比圖

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圖 9 以DCT去冗余時(shí)兩種方案密鑰不一致率對比

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圖 10 本文方案在3種去冗余方法下的密鑰不一致率

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圖 11 密鑰生成率隨RIS配置矩陣數(shù)量的變化圖

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