认知无线电背景下基于复发定量分析的非合作频谱感知策略

Signals Pub Date : 2024-07-01 DOI:10.3390/signals5030022
J.-M. Kadjo, Koffi-Clément Yao, A. Mansour, Denis Le Jeune
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引用次数: 0

摘要

本文探讨了在极低信噪比(SNR)条件下的非合作频谱感知问题。在我们的方法中,检测未占用带宽包括检测该带宽上是否存在通信信号。数字通信信号可能包含隐藏的周期性,因此我们使用递推定量分析(RQA)来揭示隐藏的周期性。RQA 非常灵敏,能可靠地估计相空间维度 m 或时间延迟 τ。鉴于文献中提出的算法的局限性,我们提出了一种新算法,可同时估计 m 和 τ 的最佳值。这种距离矩阵具有特殊属性,我们利用这些属性提出了基于递推分析的探测器(RAD)。RAD 可以在信噪比极低的条件下检测通信信号。我们的实验结果利用接收器工作特性曲线证实,与广泛使用的经典算法相比,我们提出的算法具有很强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Noncooperative Spectrum Sensing Strategy Based on Recurrence Quantification Analysis in the Context of the Cognitive Radio
This paper addresses the problem of noncooperative spectrum sensing in very low signal-to-noise ratio (SNR) conditions. In our approach, detecting an unoccupied bandwidth consists of detecting the presence or absence of a communication signal on this bandwidth. Digital communication signals may contain hidden periodicities, so we use Recurrence Quantification Analysis (RQA) to reveal the hidden periodicities. RQA is very sensitive and offers reliable estimation of the phase space dimension m or the time delay τ. In view of the limitations of the algorithms proposed in the literature, we have proposed a new algorithm to simultaneously estimate the optimal values of m and τ. The new proposed optimal values allow the state reconstruction of the observed signal and then the estimation of the distance matrix. This distance matrix has particular properties that we have exploited to propose a Recurrence-Analysis-based Detector (RAD). The RAD can detect a communication signal in a very low SNR condition. Using Receiver Operating Characteristic curves, our experimental results corroborate the robustness of our proposed algorithm compared with classic widely used algorithms.
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来源期刊
CiteScore
3.20
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0.00%
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审稿时长
11 weeks
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