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Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part I

Research Article

Spectrum Sensing for Weak Signals Based on Satellite Formation

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  • @INPROCEEDINGS{10.1007/978-3-030-69069-4_38,
        author={Yu Zhang and Xiaojin Ding and Chaoran Sun and Jian Zhu and Gengxin Zhang},
        title={Spectrum Sensing for Weak Signals Based on Satellite Formation},
        proceedings={Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part I},
        proceedings_a={WISATS},
        year={2021},
        month={2},
        keywords={Spectrum sensing Multi-satellite collaboration Beamforming Satellite formation},
        doi={10.1007/978-3-030-69069-4_38}
    }
    
  • Yu Zhang
    Xiaojin Ding
    Chaoran Sun
    Jian Zhu
    Gengxin Zhang
    Year: 2021
    Spectrum Sensing for Weak Signals Based on Satellite Formation
    WISATS
    Springer
    DOI: 10.1007/978-3-030-69069-4_38
Yu Zhang1, Xiaojin Ding2,*, Chaoran Sun1, Jian Zhu1, Gengxin Zhang1
  • 1: College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications
  • 2: Telecommunication and Network National Engineering Research Center, Nanjing University of Posts and Communications
*Contact email: dxj@njupt.edu.cn

Abstract

In this paper, we investigate the spectrum sensing of a weak signal based on multiple low earth orbit (LEO) satellites in the presence of a spectrum-sharing node, which can generate the interference imposed on the sensing LEO satellites. In order to improve the sensing ability of the weak signal, a cooperative spectrum sensing method relying on satellite formation is proposed. Specifically, firstly, some satellites will be chosen from multiple LEO satellites for formation purposes, where the specific number of satellites chosen can be adjusted by evaluating the probability of detection weak signal, as detailed later. Then, considering the object that both restraining the interference and magnifying the weak signal, the weighted value of each satellite for beamforming may be optimized with the aid of genetic algorithm, and the receive gains of the weak signal and the interference can be achieved. Finally, the probability of detecting the weak signal can be evaluated by calculating the signal to interference plus noise ratio (SINR), and the number of the chosen satellites can be decided accordingly. Simulation results show that the proposed method not only can suppress the interference imposed on the sensing satellites, but also can increase SINR of sensing satellites for the weak signal, resulting in improving the probability of detection.

Keywords
Spectrum sensing Multi-satellite collaboration Beamforming Satellite formation
Published
2021-02-28
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-69069-4_38
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