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Spectrum sensing based on angular reciprocity in cognitive satellite communication system

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Abstract

Satellite communication is attracting increasing attention owing to its freedom from geographical constraints. However, its spectrum resources are limited, and it is susceptible to interferences. Therefore, cognitive radio technology can be used to detect and prevent interferences as well as improve spectrum utilization. To improve the spectrum sensing performance, an angle reciprocity-based spectrum sensing (ARSS) scheme is proposed in this study. The scheme exploits the reciprocity between the known beam’s central angle and the unknown signal’s arrival angle, with the reciprocity controlled by the narrow characteristic of the satellite’s beam owing to long-distance propagation. In this scheme, we use the beam’s central angle instead of the signal’s actual angle to process the received signal, and then the processed data are used as the sensing statistics for spectrum sensing. The simulation results show that the proposed ARSS scheme exhibits better satellite spectral sensing performance compared with the energy detector (ED).

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References

  1. Zhang X, Wang J, Jiang C, et al. Robust beamforming for multibeam satellite communication in the face of phase perturbations. IEEE Trans Veh Technol, 2019, 68: 3043–3047

    Article  Google Scholar 

  2. Papathanassiou A, Salkintzis A K, Mathiopoulos P T. A comparison study of the uplink performance of W-CDMA and OFDM for mobile multimedia communications via LEO satellites. IEEE Pers Commun, 2001, 8: 35–43

    Article  Google Scholar 

  3. Zeng Y, Liang Y. Maximum-minimum eigenvalue detection for cognitive radio. In: Proceedings of 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, 2007. 1–5

  4. Liolis K, Schlueter G, Krause J, et al. Cognitive radio scenarios for satellite communications: the corasat approach. In: Proceedings of 2013 Future Network Mobile Summit, 2013. 1–10

  5. Chae S H, Jeong C, Lee K. Cooperative communication for cognitive satellite networks. IEEE Trans Commun, 2018, 66: 5140–5154

    Article  Google Scholar 

  6. Tarchi D, Guidotti A, Icolari V, et al. Technical challenges for cognitive radio application in satellite communications. In: Proceedings of 2014 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), 2014. 136–142

  7. Li H, Li J. Wavelet transforms detection of spectrum sensing in the space network. In: Proceedings of 2015 Science and Information Conference (SAI), 2015. 978–984

  8. Wu Z, Luo M, Yin Z, et al. Research of spectrum sensing based on ANN algorithm. In: Proceedings of the 4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, 2014. 493–496

  9. Li F, Liu X, Lam K Y, et al. Spectrum allocation with asymmetric monopoly model for multibeam-based cognitive satellite networks. IEEE Access, 2018, 6: 9713–9722

    Article  Google Scholar 

  10. Sujatmoko K, Wibisono G, Gunawan D. Notice of violation of ieee publication principles: blind spectrum sensing for cognitive radio using discriminant analysis. In: Proceedings of 2012 IEEE International Conference on Communication, Networks and Satellite (ComNetSat), 2012. 40–43

  11. Jia M, Zhang X, Gu X, et al. Interbeam interference constrained resource allocation for shared spectrum multibeam satellite communication systems. IEEE Internet Things J, 2019, 6: 6052–6059

    Article  Google Scholar 

  12. Pierucci L, Fantacci R. Mimo cooperative spectrum sensing in hybrid satellite/terrestrial scenario. In: Proceedings of 2015 IEEE International Conference on Communication Workshop (ICCW), 2015. 1617–1622

  13. Sharma S K, Chatzinotas S, Ottersten B. Spectrum sensing in dual polarized fading channels for cognitive satcoms. In: Proceedings of 2012 IEEE Global Communications Conference (GLOBECOM), 2012. 3419–3424

  14. Mahendru G, Shukla A, Banerjee P. A novel mathematical model for energy detection based spectrum sensing in cognitive radio networks. Wirel Pers Commun, 2020, 110: 1237–1249

    Article  Google Scholar 

  15. Yuan W, Yang M, Guo Q, et al. Improved cuckoo search algorithm for spectrum sensing in sparse satellite cognitive systems. In: Proceedings of 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), 2016. 1–5

  16. Wang X, Ekin S, Serpedin E. Joint spectrum sensing and resource allocation in multi-band-multi-user cognitive radio networks. IEEE Trans Commun, 2018, 66: 3281–3293

    Article  Google Scholar 

  17. Taherpour A, Nasiri-Kenari M, Gazor S. Multiple antenna spectrum sensing in cognitive radios. IEEE Trans Wirel Commun, 2010, 9: 814–823

    Article  Google Scholar 

  18. Fan J, Han L, Luo X, et al. Beamwidth design for beam scanning in millimeter-wave cellular networks. IEEE Trans Veh Technol, 2020, 69: 1111–1116

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially supported by National Natural Science Foundation of China (Grants No. 61671367), Key Research and Development Plan of Shaanxi Province (Grant No. 2018GY-003), Research Foundation of Science and Technology on Communication Networks Laboratory, Postdoctoral Science Foundation of Shanxi Province, and Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. School of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

    Jiancun Fan, Yong Ban, Jie Luo, Ying Zhang & Xinmin Luo

  2. Science and Technology on Communication Networks Laboratory, Shijiazhuang, 050081, China

    Jiancun Fan

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  1. Jiancun Fan
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  2. Yong Ban
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  3. Jie Luo
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  4. Ying Zhang
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  5. Xinmin Luo
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Correspondence to Jiancun Fan.

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Fan, J., Ban, Y., Luo, J. et al. Spectrum sensing based on angular reciprocity in cognitive satellite communication system. Sci. China Inf. Sci. 64, 182308 (2021). https://doi.org/10.1007/s11432-019-2864-5

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  • DOI: https://doi.org/10.1007/s11432-019-2864-5

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