Analytical optimization for collaborative double threshold energy detection in cognitive radio network

作     者：Zhu, Jun Bai, Yun 

作者机构：Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Electronic Information Engineering Anhui University Hefei 230601 China 

出 版 物：《Journal of Information and Computational Science》 (J. Inf. Comput. Sci.)

年 卷 期：2012年第9卷第13期

页      面：3875-3882页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0835[工学-软件工程] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Data fusion 

摘      要：The conventional OR fusion rule is frequently applied in two pre-determined limits energy detection networks but its overall performance of the false alarm and miss detection probability is generally. The new method to optimize the total error probability in three combination schemes is proposed and the presented approach focuses on combining the k-out-of-N decision fusion with data fusion. General expressions for these probabilities are derived and an analytical solution for the optimal value of k is found minimizing the overall error probability. It provides performance analysis and comparison due to the different parameters such as SNR, the threshold coefficient, for the Additive White Gaussian Noise (AWGN) channel. Numerical experiment results show there are superior performances of above fusion strategies as opposed to traditional hard rule, by selecting the right system parameters. 1548-7741/Copyright © 2012 Binary Information Press.