Effect of Primary User Traffic on the Performance of Robust and Conventional Goodness of Fit (GOF) Test based Spectrum Sensing Methods in Cognitive Radio
In cognitive radio, users of the spectrum are grouped as primary and secondary users. Primary users are license holders and a certain interval of band is assigned to them. On the other hand, secondary users determine the idle frequency intervals which are not used by primary users. To determine whether a spectrum band is idle or in use, various spectrum sensing techniques have been proposed in the literature. In the studies on goodness of fit (GOF) tests, it is assumed that primary user does not change its status during spectrum analysis. However, when the duration of analysis is long, the status of primary user may change. In this study, effect of the primary user traffic on the sensing performance of GOF test based spectrum sensing methods is investigated. According to simulation results, it has been observed that changes in the primary user status adversely affect the sensing performance.
Arshad, K., & Moessner, K. (2013). Robust spectrum sensing based on statistical tests. IET Comm., 7 (9), 808- 817. doi: 10.1049/iet-com.2012.0499
Beaulieu N. C., & Chen Y. (2010). Improved energy detectors for cognitive radios with randomly arriving or departing primary users. IEEE Signal Processing Letters, 17 (10), 867-870. doi: 10.1109/LSP.2010.2064768
Düzenli, T., & Akay, O. (2013). Bilişsel radyolar için birincil kullanıcı trafiği içeren kanallarda dinamik programlama ve ortalama kümülatif toplama dayalı yeni bir test istatistiğinin önerilmesi. V. İletişim Teknolojileri Ulusal Sempozyumu, İzmir, Turkey, 1-10.
Düzenli, T., & Akay, O. (2016). A new spectrum sensing strategy for dynamic primary users in cognitive radio. IEEE Communications Letters, 20 (4), 752-755. doi: 10.1109/LCOMM.2016.2527640
Glen, A. G., Leemis, L. M., & Barr, D. R. (2001). Order statistics in goodness-of-fit testing. IEEE Transactions on Reliability, 50 (2), 209-213. doi: 10.1109/24.963129
Lei, S., Wang, H., & Shen, L. (2011). Spectrum sensing based on goodness of fit tests. International Conf. on Electr., Comm. and Cont. (ICECC), Ningbo, China, 485 – 489. doi: 10.1109/ICECC.2011.6067691
N.-Thanh, N., K.-Xuan, T., & Koo, I. (2012). Comments on “Spectrum sensing in cognitive radio using goodness-of-fit testing”. IEEE Trans. on Wireless Comm., 11 (10), 3409 – 341. doi: 10.1109/TWC.2012.081312.110951
Rostami, S., Arshad, K., & Moessner, K. (2012). Order-statistic based spectrum sensing for cognitive radio. IEEE Comm. Lett., 16 (5), 592 -595. doi: 10.1109/LCOMM.2012.030512.111887
Stephens, M. A. (1974). EDF statistics for goodness of fit and some comparisons. Journal of the American Statistical Association, 69 (347), 730-737.
Wang, H., Yang, E., Zhao, Z., & Zhang, W. (2009). Spectrum sensing in cognitive radio using goodness of fit testing. IEEE Trans. on Wireless Comm., 8 (11), 5427 – 5430. doi: 10.1109/TWC.2009.081586
Yücek, T., & Arslan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Survey & Tutorials, 11 (1), 116-130. doi: 10.1109/HMI.2016.7449196
Zhang, J. (2002). Powerful goodness-of-fit tests based on the likelihood ratio. J. R. Statist. Soc. B Part (2), 64, 281- 294. doi: 10.1111/1467-9868.00337
Arshad, K., & Moessner, K. (2013). Robust spectrum sensing based on statistical tests. IET Comm., 7 (9), 808- 817. doi: 10.1049/iet-com.2012.0499
Beaulieu N. C., & Chen Y. (2010). Improved energy detectors for cognitive radios with randomly arriving or departing primary users. IEEE Signal Processing Letters, 17 (10), 867-870. doi: 10.1109/LSP.2010.2064768
Düzenli, T., & Akay, O. (2013). Bilişsel radyolar için birincil kullanıcı trafiği içeren kanallarda dinamik programlama ve ortalama kümülatif toplama dayalı yeni bir test istatistiğinin önerilmesi. V. İletişim Teknolojileri Ulusal Sempozyumu, İzmir, Turkey, 1-10.
Düzenli, T., & Akay, O. (2016). A new spectrum sensing strategy for dynamic primary users in cognitive radio. IEEE Communications Letters, 20 (4), 752-755. doi: 10.1109/LCOMM.2016.2527640
Glen, A. G., Leemis, L. M., & Barr, D. R. (2001). Order statistics in goodness-of-fit testing. IEEE Transactions on Reliability, 50 (2), 209-213. doi: 10.1109/24.963129
Lei, S., Wang, H., & Shen, L. (2011). Spectrum sensing based on goodness of fit tests. International Conf. on Electr., Comm. and Cont. (ICECC), Ningbo, China, 485 – 489. doi: 10.1109/ICECC.2011.6067691
N.-Thanh, N., K.-Xuan, T., & Koo, I. (2012). Comments on “Spectrum sensing in cognitive radio using goodness-of-fit testing”. IEEE Trans. on Wireless Comm., 11 (10), 3409 – 341. doi: 10.1109/TWC.2012.081312.110951
Rostami, S., Arshad, K., & Moessner, K. (2012). Order-statistic based spectrum sensing for cognitive radio. IEEE Comm. Lett., 16 (5), 592 -595. doi: 10.1109/LCOMM.2012.030512.111887
Stephens, M. A. (1974). EDF statistics for goodness of fit and some comparisons. Journal of the American Statistical Association, 69 (347), 730-737.
Wang, H., Yang, E., Zhao, Z., & Zhang, W. (2009). Spectrum sensing in cognitive radio using goodness of fit testing. IEEE Trans. on Wireless Comm., 8 (11), 5427 – 5430. doi: 10.1109/TWC.2009.081586
Yücek, T., & Arslan, H. (2009). A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Survey & Tutorials, 11 (1), 116-130. doi: 10.1109/HMI.2016.7449196
Zhang, J. (2002). Powerful goodness-of-fit tests based on the likelihood ratio. J. R. Statist. Soc. B Part (2), 64, 281- 294. doi: 10.1111/1467-9868.00337
Düzenli, T., & Akay, O. (2017). Effect of Primary User Traffic on the Performance of Robust and Conventional Goodness of Fit (GOF) Test based Spectrum Sensing Methods in Cognitive Radio. International Journal of Engineering Research and Development, 9(3), 90-99. https://doi.org/10.29137/umagd.352935