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- Title
Co-variance Based Adaptive Threshold Spectrum Detection Optimized with Chameleon Swarm Optimization for Optimum Threshold Selection in Cognitive Radio Networks.
- Authors
Charan, Chhagan; Pandey, Rajoo
- Abstract
In cognitive radio networks, Spectrum sensing is most important task for avoiding the unacceptable interference to primary users. The performance of spectrum sensing is based on the threshold value used in the sensing scheme. The existing co-variance based spectrum sensing technique use a fixed threshold which does not ensure sufficient protection to Primary users. Hence, Co-variance based adaptive threshold spectrum detection optimized with Chameleon Swarm optimization for Optimum threshold selection in Cognitive Radio Networks is proposed for appropriate security to the primary user and also reduces the total error probability. In this, the threshold selection is based on constant false alarm rate (CFAR) principles and constant detection rate (CDR) principles. Besides these principles the threshold can be derived by reducing the total probability of decision error. Hence co-variance based adaptive threshold detection (CATD) process is proposed to obtain the adaptive threshold for minimizing the total error probability. But the performance of this process weakens at low Signal to Noise Ratio. To overcome these issues, the optimized selection of threshold is needed. Hence Chameleon swarm optimization algorithm (CSOA) is proposed to enhance the performance of CATD process by selecting an optimal threshold value. The simulation process is executed in the MATLAB platform. The proposed Co-variance based adaptive threshold spectrum detection optimized with Chameleon Swarm optimization (CATD-CSOA) attains low error probability 38.5%, high detection probability 98.6, and high throughput 94.35% when comparing with the existing method such as Optimum threshold selection in Spectrum sensing based Adaptive Covariance-based Detection Algorithm (ACDA) and Optimum threshold selection in Spectrum sensing based CUSUM (Cumulate Sum) Algorithm. Finally, the proposed CATD-CSOA produces high detection probability with limited number of samples as well as threshold is selected in an optimized way.
- Subjects
FALSIFICATION of data; COGNITIVE radio; RADIO networks; OPTIMIZATION algorithms; CHAMELEONS; SIGNAL-to-noise ratio; COINTEGRATION
- Publication
Wireless Personal Communications, 2023, Vol 132, Issue 2, p1025
- ISSN
0929-6212
- Publication type
Article
- DOI
10.1007/s11277-023-10647-2