Decision-Making Rules in Cooperative Cognitive Radio Networks: Evaluation and Comparison

Abstract

Cognitive radio CR is a communication technology developed to solve the problem of spectrum scarcity. Energy detection based on cooperative spectrum sensing represents a solution to enhance the throughput of CR since the information about primary signal presence are collected using many sensing nodes with different channel conditions. Each node reports its own reports to the network centre to make its decision. However, the throughput cannot be maximized unless efficient decision rules are used to combine the collected information and produce right final judgment. In this paper, a centralized cooperative spectrum sensing scheme is used, and basic decision rules are presented. New decision-making rule based on statistical average of the node reports is proposed. Closed form expressions for probability of detection and false alarm probability for the different decision rules are given. Comparison on the throughput performance of each decision rule is studied simulated via a system model and MATLAB programming. Fading channel is assumed for data transmission, while the reporting channels are assumed to be free of errors.