Open AccessPerformance of Threshold Detection in Cognitive Radio with Improved Otsu’s and Recursive One-Sided Hypothesis Testing Technique
Author(s) -
Pallam Venkatapathi,
Habibulla Khan,
Suhasini Subba Rao
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i3063.0789s319
Subject(s) - cognitive radio , otsu's method , false alarm , computer science , noise (video) , energy (signal processing) , statistical power , signal (programming language) , algorithm , pattern recognition (psychology) , statistics , artificial intelligence , telecommunications , mathematics , segmentation , wireless , image (mathematics) , image segmentation , programming language
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