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Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment

We investigate a distributed-satellite-clusters (DSC)-system-based spectrum sensing, to enhance the ability for sensing weak signals. However, the spectrum-sensing performance may be significantly decreased by the phase deviations among different satellite clusters, where the deviations may be cause...

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Detalles Bibliográficos
Autores principales: Wang, Yunfeng, Ding, Xiaojin, Hong, Tao, Zhang, Gengxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9183005/
https://www.ncbi.nlm.nih.gov/pubmed/35684604
http://dx.doi.org/10.3390/s22113983
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author Wang, Yunfeng
Ding, Xiaojin
Hong, Tao
Zhang, Gengxin
author_facet Wang, Yunfeng
Ding, Xiaojin
Hong, Tao
Zhang, Gengxin
author_sort Wang, Yunfeng
collection PubMed
description We investigate a distributed-satellite-clusters (DSC)-system-based spectrum sensing, to enhance the ability for sensing weak signals. However, the spectrum-sensing performance may be significantly decreased by the phase deviations among different satellite clusters, where the deviations may be caused by the movement and the perturbation of satellites. To eliminate such a decrement, we propose a cooperative spectrum-sensing scheme in the presence of phase deviations, where the deviations are alleviated by a special two-stage phase synchronization. Specifically, the phase compensation is first performed relying on broadcasting reference signals and the ephemeris, to address the challenges of the deviations caused by the movement. Then, a two-bit feedback algorithm, having a dynamic disturbance step size, is further adopted for controlling and mitigating the deviations caused by the perturbation. Additionally, we provide the closed-form expression of the correct detection probability of the proposed spectrum-sensing scheme, using the specially derived probability density function of the sum of the shadowed-Rician random variables with independently identical distribution. Simulation results show that the proposed scheme can achieve the best spectrum-sensing performance, comparing with the traditional energy detection, eigenvalue ratio test and the generalized likelihood ratio test.
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spelling pubmed-91830052022-06-10 Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment Wang, Yunfeng Ding, Xiaojin Hong, Tao Zhang, Gengxin Sensors (Basel) Article We investigate a distributed-satellite-clusters (DSC)-system-based spectrum sensing, to enhance the ability for sensing weak signals. However, the spectrum-sensing performance may be significantly decreased by the phase deviations among different satellite clusters, where the deviations may be caused by the movement and the perturbation of satellites. To eliminate such a decrement, we propose a cooperative spectrum-sensing scheme in the presence of phase deviations, where the deviations are alleviated by a special two-stage phase synchronization. Specifically, the phase compensation is first performed relying on broadcasting reference signals and the ephemeris, to address the challenges of the deviations caused by the movement. Then, a two-bit feedback algorithm, having a dynamic disturbance step size, is further adopted for controlling and mitigating the deviations caused by the perturbation. Additionally, we provide the closed-form expression of the correct detection probability of the proposed spectrum-sensing scheme, using the specially derived probability density function of the sum of the shadowed-Rician random variables with independently identical distribution. Simulation results show that the proposed scheme can achieve the best spectrum-sensing performance, comparing with the traditional energy detection, eigenvalue ratio test and the generalized likelihood ratio test. MDPI 2022-05-24 /pmc/articles/PMC9183005/ /pubmed/35684604 http://dx.doi.org/10.3390/s22113983 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Yunfeng
Ding, Xiaojin
Hong, Tao
Zhang, Gengxin
Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment
title Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment
title_full Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment
title_fullStr Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment
title_full_unstemmed Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment
title_short Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment
title_sort distributed-satellite-clusters-based spectrum sensing with two-stage phase alignment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9183005/
https://www.ncbi.nlm.nih.gov/pubmed/35684604
http://dx.doi.org/10.3390/s22113983
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