A cooperative wideband spectrum sensing framework in the frequency domain for resource allocation with 5G-NR. (15th March 2022)

• Record Type: Journal Article
• Authors: Zhao, Yingxin; Wang, Changfeng; Hu, Man; Wu, Hong; Lin, Fangru; Liu, Zhiyang
• Is Part Of: Measurement. Volume 191(2022)
• Publication Date: 2022-03-15
• Subjects: Cooperative spectrum sensing -- Cyclic prefix autocorrelation -- Soft-hard combined decision -- Energy detection -- Noise uncertainty -- Dual-threshold model; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.110756
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Utilize the cyclic prefix correlation of the OFDM signal for wideband spectrum sensing. The proposed algorithm can effectively deal with the noise uncertainty. Combine the multi-user cooperative model and the dual-threshold detection model to construct a framework. The performance of the proposed framework is better than the other widely used algorithms. The proposed framework can reduce the overhead of spectrum sensing system. Abstract: The development of wireless communication leads to the gradual reduction of spectrum resources. As an essential part of cognitive radio (CR) technology, wideband spectrum sensing can detect whether the current authorized spectrum is being occupied, which is the prerequisite for dynamic spectrum allocation. In this paper, by utilizing the correlation of cyclic prefixes in the frequency domain, we propose a novel spectrum sensing algorithm applied to wideband scenarios with the existence of noise uncertainty (NU). Based on the proposed algorithm, we construct the dual-threshold cooperative spectrum sensing framework by integrating the multi-user cooperative model and dual-threshold detection model to enhance the effectiveness and reliability of spectrum sensing. With the parameters of 5G New Radio (5G-NR), we consider a cooperative spectrum sensing scheme to evaluate system performance. The simulation results demonstrate that the proposed framework exhibits better wideband spectrum sensing performance than traditional algorithms and effectively reduces the overhead of system.