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Performance Evaluation of Windowing Based Energy Detector in Multipath and Multi-signal Scenarios

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Cognitive Radio-Oriented Wireless Networks (CrownCom 2019)

Abstract

Connectivity in remote areas continues to be a major challenge despite of the evolution of cellular technology. 5th Generation (5G) technology can address remote connectivity if lower carrier frequencies are available, which calls for shared use of spectrum to enable cost-efficient license-free solution. Therefore, spectrum sensing has its own role in future wireless systems such as mobile 5G networks and Internet of Things (IoT) to complement database approach in dynamic spectrum utilization. In this paper, a windowing based (WIBA) blind spectrum sensing method is studied. Its performance is compared to the localization algorithm based on double-thresholding (LAD) detection method. Both the methods are based on energy detection and can be used in any frequency range as well as for detecting all kind of relatively narrowband signals. Probability of detection, relative mean square error for the bandwidth estimation, and the number of detected signals were evaluated, including multipath and multi-signal scenarios. The simulation results show that the WIBA method is very suitable for future 5G applications especially for remote area connectivity, due to its good detection performance in low signal-to-noise ratio (SNR) areas with low complexity and reasonable costs. The simulation results also show importance of the used detection window selection since too wide detection window degrades the detection performance of the WIBA method.

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References

  1. Bockelmann C., et al.: Towards massive connectivity support for scalable mMTC communications in 5G networks. In: IEEE Access, vol. 6 (2018)

    Google Scholar 

  2. Li, B., Li, S., Nallanathan, A., Zhao, C.: Deep sensing for future spectrum and location awareness 5G communications. IEEE J. Sel. Areas Commun. 33(7), 1331ā€“1344 (2015)

    Article  Google Scholar 

  3. Atat, R., Liu, L., Chen, H., Wu, J., Li, H., Yi, Y.: Enabling cyber-physical communication in 5G cellular networks: challenges, spatial spectrum sensing, and cyber-security. IET Cyber-Phys. Syst. Theory Appl. 2(1), 49ā€“54 (2017)

    Article  Google Scholar 

  4. Ejaz, W., Ibnkahla, M.: Multiband spectrum sensing and resource allocation for IoT in cognitive 5G networks. IEEE Internet Things J. 5(1), 150ā€“163 (2018)

    Article  Google Scholar 

  5. Vartiainen, J., Hoyhtya, M., Vuohtoniemi, R., Ramani, V.V.: The future of spectrum sensing. In: International Conference on Ubiquitous and Future Networks, ICUFN 2016, pp. 247ā€“252 (2016)

    Google Scholar 

  6. Akyildiz, I.F., Lo, B.F., Balakrishnan, R.: Cooperative spectrum sensing in cognitive radio networks: a survey. Phys. Commun. 4(1), 40ā€“62 (2011)

    Article  Google Scholar 

  7. Liu, X., He, D., Jia, M.: 5G-based wideband cognitive radio system design with cooperative spectrum sensing. Phys. Commun. 25(2), 539ā€“545 (2017)

    Article  Google Scholar 

  8. Saarnisaari, H., Vartiainen, J.: Spectrum window based signal detection at low SNR. In: International Conference on Military Communications and Information Systems (ICMCIS), Poland (2018)

    Google Scholar 

  9. Vartiainen, J., Lehtomaki, J.J., Saarnisaari, H.: Double-threshold based narrowband signal extraction. In: IEEE Vehicular Technology Conference (VTC), pp. 1288ā€“1292 (2005)

    Google Scholar 

  10. Vartiainen, J.: Concentrated signal extraction using consecutive mean excision algorithms. Ph.D. Dissertation, Acta Univ Oul Technica C 368. Faculty of Technology, University of Oulu, Finland (2010)

    Google Scholar 

  11. ECC: Technical and operational requirements for the possible operation of cognitive radio systems in the white spaces of the frequency band 470ā€“790 MHz. In: ECC Report 159 (2011)

    Google Scholar 

  12. FCC: Amendment of the Commissionā€™s Rules with Regard to Commercial Operations in the 3550ā€“3650 MHz Band. In: Report and Order, FNPRM, FCC-15-47 (2015)

    Google Scholar 

  13. 5G-RANGE Project. http://5g-range.eu/. Accessed 1 Mar 2019

  14. Miller, K.S.: Complex Gaussian process. SIAM Rev. 11, 544ā€“567 (1969)

    Article  MathSciNet  Google Scholar 

  15. Neeser, F.D., Massey, J.-L.: Proper complex random processes with applications to information theory. IEEE Trans. Inf. Theory 39, 1293ā€“1302 (1993)

    Article  MathSciNet  Google Scholar 

  16. Lehtomaki, J.J., Vartiainen, J., Juntti, M., Saarnisaari, H.: CFAR outlier detection with forward methods. IEEE Trans. Sig. Process. 55, 4702ā€“4706 (2003)

    Article  MathSciNet  Google Scholar 

  17. Saarnisaari H., Henttu P.: Impulse detection and rejection methods for radio systems. In: Military Communications Conference (MILCOM), pp. 1126ā€“1131 (2003)

    Google Scholar 

  18. Proakis, J.G.: Digital Communications, 3rd edn. McGraw-Hill Inc., New York (1995)

    MATH  Google Scholar 

Download references

Acknowledgment

This research has received funding from the European Union Horizon 2020 Programme (H2020/2017ā€“2019) under grant agreement N0. 777137 and from the Ministry of Science, Technology and Innovation of Brazil through Rede Nacional de Ensino e Pesquisa (RNP) under the 4th EU-BR Coordinated Call Information and Communication Technologies through 5G-RANGE project. In addition, this research has been financially supported in part by Academy of Finland 6Genesis Flagship (grant 318927) and CNPq-Brasil.

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Correspondence to Johanna Vartiainen .

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Ā© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Vartiainen, J., Karvonen, H., Matinmikko-Blue, M., Mendes, L. (2019). Performance Evaluation of Windowing Based Energy Detector in Multipath and Multi-signal Scenarios. In: Kliks, A., et al. Cognitive Radio-Oriented Wireless Networks. CrownCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 291. Springer, Cham. https://doi.org/10.1007/978-3-030-25748-4_5

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  • DOI: https://doi.org/10.1007/978-3-030-25748-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-25747-7

  • Online ISBN: 978-3-030-25748-4

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