标题：Optimal Linear Soft Fusion Schemes for Cooperative Sensing in Cognitive Radio Networks
作者：Shen, Bin; Kwak, Kyungsup; Bai, Zhiquan
作者机构：[Shen, Bin; Kwak, Kyungsup] Inha Univ, Grad Sch Informat Tech & Telecom, Inchon 402751, South Korea.; [Bai, Zhiquan] Shandong Univ, Sch Informat Sci 更多
会议名称：IEEE Global Telecommunications Conference (GLOBECOM 09)
会议日期：NOV 30-DEC 04, 2009
来源：GLOBECOM 2009 - 2009 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, VOLS 1-8
关键词：Energy detection; optimal fusion; cooperative spectrum sensing;; cognitive radio
摘要：In this paper, three optimal linear soft fusion schemes for cooperative sensing are proposed on the basis of corresponding optimality criteria, namely Neyman-Pearson (N-P), deflection coefficient maximization (DCM), and linear quadratic optimization (LQO). Multiple cooperative secondary users (SU) in the cognitive radio (CR) network simply serve as relays to provide space diversity for the fusion center (FC) to obtain the global test statistic. After the ideal optimal fusion weights are acquired, iterative weight setting strategies are utilized to implement them in practice. Analysis and simulation results illustrate that the proposed N-P and DCM schemes yield significant improvements on the sensing performance and the iterative weight setting algorithm can effectively approach the ideal performance of these two schemes. As for the LQO scheme which operates on the received signal covariance matrices merely, it is capable of providing satisfactory performance with sufficient cooperative SUs.