Spectrum Sensing Algorithm Based on Joint Detection of Skewness and Kurtosis

doi:10.13438/j.cnki.jdzk.2023.06.003

Abstract

Abstract: By normalizing the sample skewness and kurtosis of the received signal,a spectrum sensing algorithm based on joint detection of skewness and kurtosis (joint detection) is proposed.Utilizing the probability density function of the chi-square distribution,the theoretical false alarm performance of the algorithm is analyzed under non-asymptotic conditions,and the corresponding theoretical decision threshold is derived.In the simulation experiments,joint detection can still guarantee reliable detection results with small number of samples,and shows better detection performance than the classical Jarque-Bera (JB) spectrum sensing algorithm.

Key words: cognitive radio, spectrum sensing, sample skewness, sample kurtosis, joint detection

TAN Zhewen, LEI Kejun, YANG Xi, WANG Xuming, TAN Yuhao. Spectrum Sensing Algorithm Based on Joint Detection of Skewness and Kurtosis[J]. Journal of Jishou University(Natural Sciences Edition), 2023, 44(6): 14-19.

References

[1] ALI ABDELMOHSEN,HAMOUDA WALAA.Advances on Spectrum Sensing for Cognitive Radio Networks:Theory and Applications[J].IEEE Communications Surveys & Tutorials,2016,19(2):1277-1304.
[2] NASSER ABBASS,AL HAJ HASSAN HUSSEIN,JAD ABOU CHAAYA,et al.Spectrum Sensing for Cognitive Radio:Recent Advances and Future Challenge[J].Sensors,2021,21(7):2408.DOI:10.3390/s21072408.
[3] DANNANA SURESH,BABJI PRASAD CHAPA,GOTTAPUSASIBHUSHANA RAO.Intelligent Engineering Informatics[M].Singapore:Springer,2018:497-503.
[4] YANG Mingchuan,LI Yuan,LIU Xiaofeng,et al.Cyclostationary Feature Detection Based Spectrum Sensing Algorithm Under Complicated Electromagnetic Environment in Cognitive Radio Networks[J].China Communications,2015,12(9):35-44.
[5] SUBEKTI AGUS,SYAMBAS NANA RACHMANA,SUKSMONO ANDRIYAN.A Jarque-Bera Test Based Spectrum Sensing for Cognitive Radio[C]∥ International Conference on Telecommunication Systems Services and Applications (TSSA).Kuta,Indonesia:IEEE Press,2014:1-4.
[6] DENKOVSKI DANIEL,ATANASOVSKI VLADIMIR,GAVRILOVSKA LILJANA.HOS Based Goodness-of-Fit Testing Signal Detection[J].IEEE Communications Letters,2012,16(3):310-313.
[7] CARVALHO FABRCIO B S,LOPES WASLON T A,ALENCAR MARCELO S.A Modified Jarque-Bera Test for Spectrum Sensing in Cognitive Networks Subject to Rayleigh Fading[C]∥ IEEE International Conference on Vehicular Technology Conference (VTC-Fall).Montréal:IEEE Press,2016:1-5.
[8] JING Yuan,MA Li,LI Peng,et al.Robust Spectrum Sensing for Small-Scale Primary Users Under Low Signal-to-Noise Ratio[C]∥ IEEE International Conference on High Performance Computing and Communications & IEEE International Conference on Embedded and Ubiquitous Computing (HPCC & EUC).Zhangjiajie:IEEE Press,2013:1566-1570.
[9] 盛骤,谢式千,潘承毅.概率论与数理统计[M].北京:高等教育出版社,2008:206-208.