CSS using Energy Detector in AWGN and Flat-Fading Channels in Cognitive Radio Networks: A Complete Analysis
Aparna Singh Kushwah1, Vineeta Saxena (Nigam)2
1Mrs. Aparna Singh Kushwah, Associate Professor in the Department of Electronics & Communication Engineering, University Institute of Technology, Rajiv Gandhi Proudyougiki Vishwavidyalaya, Bhopal, Madhya Pradesh.
2Dr. Vineeta Saxena (Nigam), Professor & Head, Department of Electronics & Communication Engineering, University Institute of Technology, Rajiv Gandhi Proudyougiki Vishwavidyalaya, Bhopal, Madhya Pradesh.
Manuscript received on February 27, 2020. | Revised Manuscript received on March 14, 2020. | Manuscript published on March 30, 2020. | PP: 5042-5046 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9593038620/2020©BEIESP | DOI: 10.35940/ijrte.F9593.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this work, various spectrum sensing methods and algorithms are analyzed and their performance is been evaluated based on the different values of probabilities as obtained through MATLAB simulations. The work is been started from the analysis of the simplest single user sensing to advanced cooperative spectrum sensing and is further extended to CSS in AWGN noise and flat-fading channels. The results indicates that advanced cooperative spectrum sensing gives much better sensing decisions as compared to the results obtained by simulating single user sensing method. Simulation results obtained shows that Pd increases with Pf and also shows good values for SNR more than 0 dB. Also the Pd increases from 0.7 to 0.84 as we go from single user detection to CSS.
Keywords: Cognitive Radio Networks (CRN), Co-operative Spectrum Sensing (CSS), Energy Detector (ED), Primary User (PU), Secondary User (SU), Signal Noise Ratio (SNR).
Scope of the Article: Cognitive Radio Networks.