Spectrum Sensing for Cognitive Radio Using Binary Particle Swarm Optimization

作     者：Taha, Mohamed A. al Nadi, Dia I. Abu 

作者机构：Princess Sumaya Univ Technol Dept Commun Engn Amman Jordan Univ Jordan Dept Elect Engn Amman Jordan 

出 版 物：《WIRELESS PERSONAL COMMUNICATIONS》 (无线个人通信)

年 卷 期：2013年第72卷第4期

页      面：2143-2153页

核心收录：

学科分类：0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：Cognitive radio Spectrum sensing Maximum likelihood estimation Binary particle swarm optimization 

摘      要：Spectrum sensing techniques in cognitive radio are the most important issue to exploit the spectrum efficiently. Several techniques have been proposed recently to estimate the dimension of the received signal from which the vacant frequencies can be determined and made available to the secondary users. These techniques have difficulties in low signal to noise ratio and limited sensing interval cases. It is known that the Maximum Likelihood Estimation (MLE) has an outstanding performance in most practical scenarios. In this paper, we present a Maximum Likelihood Estimate (MLE) to detect the number of vacant channels in the spectrum. The resulting MLE estimate posses several minima and maxima, therefore it needs exhaustive search to be determined accurately. To solve the problem, an evolutionary algorithm called Binary Particle Swarm Optimization (BPSO) is proposed. Simulation results have shown significant improvement of the MLE-BPSO estimate over the conventional techniques by 3-5 dB.