Adaptive Techniques to Detect White Spaces Using Spectrum Sensing In Cognitive Radio

Abstract

Spectrum sensing is one of the key technologies to realize dynamic spectrum access in cognitive radio systems. Cognitive radios have been proposed as a possible solution to improve spectrum utilization by enabling opportunistic spectrum sharing. The main requirement for allowing CR�s to use proper exploitation of white spaces in the radio spectrum requires fast, robust, and accurate methods for their detection. Spectrum sensing allows cognitive users to autonomously identify unused portions of the radio spectrum. In this work, energy detection technique is considered for spectrum sensing and uses the cost-function that depends upon a single parameter which gives the aggregate information about the present or absent of licensed users. The process of threshold selection for energy detection is addressed by the constant false alarm method and selection is carried out considering present conditions of noise levels. In this paper, simulation results shown that if we dynamically adjust the detection threshold based on noise level present during the detection process. The detection of white spaces will be higher at lower sampling time as compared with probability of detection and false alarm rate.