Performance of Threshold Detection in Cognitive Radio with Improved Otsu’s and Recursive One-Sided Hypothesis Testing Technique
P. Venkatapathi1, Habibulla Khan2, S. Srinivasa Rao3
1P. Venkatapathi, Research Scholar, Department of ECE, KLEF, Vijayawada, Andhra Pradesh, India.
2Dr. Habibulla Khan, Professor, Department of Electronics and Communication Engineering, KLEF, Andhra Pradesh, India.
3Dr. S. Srinivasa Rao, Professor & HOD, Department of Electronics and Communication Engineering, MRCET, Hyderabad, Telangana, India.
Manuscript received on 02 July 2019 | Revised Manuscript received on 16 July 2019 | Manuscript Published on 23 August 2019 | PP: 343-346 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I30630789S319/2019©BEIESP | DOI: 10.35940/ijitee.K1133.09811S19
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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: Cognitive radio (CR) is a new technology proposed to enhance spectrum efficiency by enabling unlicensed secondary users to access the licensed frequency bands without getting involved with the primary users licensed. Although considered optimal, in order to calculate the signal threshold, this approach requires prior noise statistics information. Even though considered optimal, in order to calculate the signal threshold, this approach requires prior noise statistics information. A prominent example of an Adaptive Threshold Estimation Technique (ATT) for energy detection in Cognitive Radio (CR) is the Recursive One-sided Hypothesis Testing Technique (ROHT). Accurate threshold values are known to be calculated based on the correct choice of their parameter values, which include the standard deviation coefficient and the stop criteria. In this paper, for efficient threshold estimation, the improved Otsu and ROHT are combined for estimating threshold even in the presence of noise floor without need of prior knowledge. The proposed methodology for enactment in cognitive radio sensor networks (CRSN) system based on the adaptive threshold energy detection model with noise variance estimation. The simulation is carried out with the help of Matlab 2017a with the improved Otsu and ROHT techniques. The results obtained shows that improved Otsu and ROHT techniques outperforms that of fixed threshold energy detection in terms of different probability of false alarm rates and miss detections.
Keywords: Adaptive, Cognitive Radio, Energy Detector, Recursive One‐sided Hypothesis Testing, Threshold
Scope of the Article: Cognitive Radio Networks