A soft fusion scheme for cooperative spectrum sensing based on the log-likelihood ratio

Abstract

Cognitive spectrum sensing is a key technology to improve the spectrum utilization and meanwhile decrease the possibility of interfering the primary users(PUs). Based on the cooperation of several cognitive radio sensors(CRSs), the channel fading and hidden terminal problems are avoided. The performance of detection has great relevance with the algorithm of combining the data from different CRSs. Soft fusion scheme is proved to perform better than hard fusion scheme in many scenarios[1]. The log-likelihood ratio(LLR) based soft fusion scheme is widely studied these years, but the complex or unavailable form of the distribution of the data at fusion center(FC) largely limits the optimization of the cognitive system. This paper proposes a new soft fusion scheme based on LLR which simplifies the analysis of the data at FC, and presents the exact closed-form expressions for the distribution of the data at FC, which turn out to be the Gaussian Distribution. The closed-form expressions for the probabilities of miss detection and false alarm derived are analytically tractable, therefore they efficiently guarantee the global optimality with low computational complexity. Simulation results verify the effectiveness of the proposed data fusion scheme and the validity of the expressions.