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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 |
Files in This Item:
File | Description | Size | Format | |
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Optimization of censoring based cooperative spectrum sensing approach with multiple antennas and imperfect reporting channel scenarios for cognitive radio network.pdf | 1.97 MB | Adobe PDF | View/Open |
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