OPTIMIZATION OF MULTIPLE-CHANNEL COOPERATIVE SPECTRUM SENSING WITH DATA FUSION RULE IN COGNITIVE RADIO NETWORKS  

作　　者：Yu Huogen Tang Wanbin Li Shaoqian 

机构地区：[1]National Key Laboratory of Science and Technology on Communications,University of Electronic Science and Technology of China

出　　处：《Journal of Electronics(China)》2012年第6期515-522,共8页电子科学学刊（英文版）

基　　金：Supported by the National Natural Science Foundation of China (No. 61271169);National Basic Research Program (973 Program) of China (No. 2009CB320405);Nation Grand Special Science and Technology Project of China under Grant (No. 2010ZX03006-002, 2010ZX03002-008-03)

摘　　要：This paper focuses on multi-channel Cooperative Spectrum Sensing (CSS) where Secondary Users (SUs) are assigned to cooperatively sense multiple channels simultaneously. A multi-channel CSS optimization problem of joint spectrum sensing and SU assignment based on data fusion rule is formulated, which maximizes the total throughput of the Cognitive Radio Network (CRN) subject to the constraints of probabilities of detection and false alarm. To address the optimization problem, a Branch and Bound (BnB) algorithm and a greedy algorithm are proposed to obtain the optimal solutions. Simulation results are presented to demonstrate the effectiveness of our proposed algorithms and show that the throughput improvement is achieved through the joint design. It is also shown that the greedy algorithm with a low complexity achieves the comparable performance to the exhaustive algorithm.This paper focuses on multi-channel Cooperative Spectrum Sensing （CSS） where Secondary Users （SUs） are assigned to cooperatively sense multiple channels simultaneously. A multi-channel CSS optimization problem of joint spectrum sensing and SU assignment based on data fusion rule is for- mulated, which maximizes the total throughput of the Cognitive Radio Network （CRN） subject to the constraints of probabilities of detection and false alarm. To address the optimization problem, a Branch and Bound （BnB） algorithm and a greedy algorithm are proposed to obtain the optimal solutions. Simulation results are presented to demonstrate the effectiveness of our proposed algorithms and show that the throughput improvement is achieved through the joint design. It is also shown that the greedy algorithm with a low complexity achieves the comparable performance to the exhaustive algorithm.

关 键 词：Cooperative Spectrum Sensing (CSS) Cognitive radio Branch and Bound (BnB) algorithm Greedy algorithm 

分 类 号：TN92[电子电信—通信与信息系统]