Wasonga, FOlwal, TOAbu-Mahfouz, Adnan MI2019-12-182019-12-182019-11Wasonga, F., Olwal, T.O. & Abu-Mahfouz, A.M.I. 2019. Improved two-stage spectrum sensing for cognitive radio networks. Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 23, no. 6, pp. 1052-10621883-80141343-0130https://www.fujipress.jp/jaciii/jc/jacii002300061052/https://www.jstage.jst.go.jp/article/jaciii/23/6/23_1052/_article/-char/enhttp://hdl.handle.net/10204/11272Copyright: 2019 Fuji Technology Press Ltd. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 23, no. 6, pp. 1052-1062Cognitive radio employs an opportunistic spectrum access approach to ensure efficient utilization of the available spectrum by secondary users (SUs). To allow SUs to access the spectrum opportunistically, the spectrum sensing process must be fast and accurate to avoid possible interference with the primary users. Previously, two-stage spectrum sensing methods were proposed that consider the sensing time and sensing accuracy parameters independently at the cost of a non-optimal spectrum sensing performance. To resolve this non-optimality issue, we consider both parameters in the design of our spectrum sensing scheme. In our scheme, we first derive optimal thresholds using an optimization equation with an objective function of maximizing the probability of detection, subject to the minimal probability of error. We then minimize the average spectrum sensing time using signal-to-noise ratio estimation. Our simulation results show that the proposed improved two-stage spectrum sensing (ITSS) scheme provides a 4%, 7%, and 6% better probability of detection accuracy rate than two-stage combinations of energy detection (ED) and maximum eigenvalue detection, energy detection and cyclostationary feature detection (CFD), and ED and combination of maximum-minimum eigenvalue (CMME) detection, respectively. The ITSS is superior also to single-stage ED by 19% and shows an improved average spectrum sensing time.enCognitive radioProbability of errorProbability of missed detectionSignal-to-noise ratioProbability of false alarmArticleWasonga, F., Olwal, T., & Abu-Mahfouz, A. M. (2019). Improved two-stage spectrum sensing for cognitive radio networks. http://hdl.handle.net/10204/11272Wasonga, F, TO Olwal, and Adnan MI Abu-Mahfouz "Improved two-stage spectrum sensing for cognitive radio networks." (2019) http://hdl.handle.net/10204/11272Wasonga F, Olwal T, Abu-Mahfouz AM. Improved two-stage spectrum sensing for cognitive radio networks. 2019; http://hdl.handle.net/10204/11272.TY - Article AU - Wasonga, F AU - Olwal, TO AU - Abu-Mahfouz, Adnan MI AB - Cognitive radio employs an opportunistic spectrum access approach to ensure efficient utilization of the available spectrum by secondary users (SUs). To allow SUs to access the spectrum opportunistically, the spectrum sensing process must be fast and accurate to avoid possible interference with the primary users. Previously, two-stage spectrum sensing methods were proposed that consider the sensing time and sensing accuracy parameters independently at the cost of a non-optimal spectrum sensing performance. To resolve this non-optimality issue, we consider both parameters in the design of our spectrum sensing scheme. In our scheme, we first derive optimal thresholds using an optimization equation with an objective function of maximizing the probability of detection, subject to the minimal probability of error. We then minimize the average spectrum sensing time using signal-to-noise ratio estimation. Our simulation results show that the proposed improved two-stage spectrum sensing (ITSS) scheme provides a 4%, 7%, and 6% better probability of detection accuracy rate than two-stage combinations of energy detection (ED) and maximum eigenvalue detection, energy detection and cyclostationary feature detection (CFD), and ED and combination of maximum-minimum eigenvalue (CMME) detection, respectively. The ITSS is superior also to single-stage ED by 19% and shows an improved average spectrum sensing time. DA - 2019-11 DB - ResearchSpace DP - CSIR KW - Cognitive radio KW - Probability of error KW - Probability of missed detection KW - Signal-to-noise ratio KW - Probability of false alarm LK - https://researchspace.csir.co.za PY - 2019 SM - 1883-8014 SM - 1343-0130 T1 - Improved two-stage spectrum sensing for cognitive radio networks TI - Improved two-stage spectrum sensing for cognitive radio networks UR - http://hdl.handle.net/10204/11272 ER -