Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8987
Title: Optimisation of censoring-based cooperative spectrum sensing approach with multiple antennas and imperfect reporting channel scenarios for cognitive radio network
Authors: Kumar, Alok
Pandit, Shweta
Singh, Ghanshyam
Keywords: censoring
Antenna
Radio network
Issue Date: 2020
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: In this article, we have employed an energy detector (ED)-based cooperative spectrum sensing (CSS) with multiantenna for cognitive radio network (CRN). The spectrum sensing error and energy efficiency (EE) are the key performance parameters in CRN which are affected by the threshold selection method, number of antennas employed at each cognitive user (CU), reporting error probability and cooperative fusion-rule applied at fusion center (FC). Therefore, we have derived the expression for sensing error by considering the effect of all these parameters and have optimized the cooperative fusion-rule at FC by formulating mathematical expression for optimal K in k-out-of-M rule to minimize the sensing error. Since CSS improves the sensing performance of CRN at the cost of increased overhead bits due to more CUs reporting to FC, results reduced EE. We have employed censoring approach to reduce the energy consumption and hence increase the EE of CSS technique. Further, we have illustrated the sensing error and EE improvement achieved under the censoring approach when different threshold selection approaches are employed at each CU. The percentage EE enhancement in censoring approach are 19.53% and 19.9% with constant false-alarm rate (CFAR) and minimized-error probability (MEP) approaches, respectively in comparison to that of the non-censoring approach.
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8987
Appears in Collections:Journal Articles



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.