Proposed Technique for Cooperative Spectrum Sensing Optimization through Maximizing the Network Utility and Minimizing the Error Probability

Abstract

Spectrum Sensing is an emerging technology in the field of wireless communication. It is an essential functionality of Cognitive Radio (CR) where it is used to detect whether there are primary users currently using the spectrum. Energy Detection technique is the most commonly used method for spectrum sensing. Non-cooperative spectrum sensing i.e. signal detection by single user suffers from several drawbacks. These drawbacks include shadowing/fading and noise uncertainty of wireless channels. Hence, to overcome these disadvantages, a new methodology called Cooperative Spectrum Sensing (CSS) has been suggested in the literature.This thesis deals with the comparison of conventional spectrum sensing techniques. Here, we consider the optimization of conventional energy detection based CSS. In CSS, hard combining technique has gained importance due to its simplicity and it deals with three decision rules which are ‘AND rule’, ‘OR rule’ and ‘MAJORITY rule’.For optimization, we have considered the network utility function and error probability. The aim of the thesis is to maximize the network utility and minimize the error probability. In order to achieve the goal we have proposed that the optimum voting rule is half voting rule also known as majority rule in ‘n out of K’ rules and obtained optimal number of cognitive radios by applying the hard decision rules. A method of obtaining the optimal detection threshold, numerically, has been presented. The optimal conditions have been verified through simulation results over an AWGN channel and it is concluded that, in proposed optimization scheme ‘MAJORITY rule (half voting rule)’ outperforms the ‘AND rule’ and ‘OR rule’. It has been found that the suitable selection of CR can achieve better utility function with minimum error probability for any wireless environment.