Today, communication systems face major shortages in availability of free spectrum. Cognitive radio has evolved as the most feasible technology which can empower us to effectively utilize the available spectrum. A vital component of a Cognitive Radio Network is spectrum sensing, Le. its ability to detect the presence of a primary user. This paper employs an adaptive threshold detection algorithm based on an image binarization technique. A novel approach is proposed to fix the standard deviation threshold whereby the system dynamically trains itself based on previously iterated decision statistics. Such data is computed on the basis of calculated probability of detection, probability of false alarm, standard deviation coefficient and ratio of occupied bandwidth to the total bandwidth. Simulation results show the vastly improved performance compared to the conventional energy detector. At low Sound to Noise Ratio the performance improvement index shows an increase of 30 per cent in comparison to the conventional energy detector.
cited By 0; Conference of International Conference on Control, Instrumentation, Communication and Computational Technologies, ICCICCT 2015 ; Conference Date: 18 December 2015 Through 19 December 2015; Conference Code:121754
A. Muralidharan, Venkateswaran, P., Ajay, S. G., D. Prakash, A., Arora, M., and Dr. Kirthiga S., “An adaptive threshold method for energy based spectrum sensing in cognitive radio networks: A practical implementation using a blind spectrum sensing method”, in 2015 International Conference on Control Instrumentation Communication and Computational Technologies, ICCICCT 2015, 2015, pp. 8-11.