Information Combining Schemes for Cooperative Spectrum Sensing: A Survey and Comparative Performance Analysis

Abstract

Spectrum scarcity has evolved as�a challenging problem in the field of wireless communication. Cognitive radio (CR) has emerged as a solution to this problem which uses available spectrum efficiently in an opportunistic way. Spectrum sensing unit as part of a�CR deals with the reliable detection of primary user�s signal. However individual CRs do not able to detect the primary user due to factors such as noise uncertainty, multipath fading, shadowing etc. This paper presents a survey on state of the art information combining schemes for cooperative spectrum sensing. Different algorithms are employed for optimizing the probability of detection at a specified probability of false alarm. The performance of the state of the art techniques are compared with that achieved using evolutionary algorithm (EA). The simulation results show that the EAs perform better than the statistical techniques and reduce the computational complexity and time by a high margin. Different statistical tests are carried out to assess the stability of the simulation results offered by the heuristic EAs. In addition, the sensitivity analysis of different parameters is performed to demonstrate their impact on the overall performance of the system. � 2016, Springer Science+Business Media New York.