Cooperative Spectrum Sensing Algorithms Based on Correlation Matrix in Cognitive Radio Networks

• Published in: Tsinghua science and technology Vol. 16; no. 4; pp. 386 - 392
• Main Author: 王海军 粟欣 王京
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2011; Wireless and Mobile Communications R&D Center, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
• Subjects: Algorithms; Channels; cognitive radio; Correlation; covariance matrix; Detection; energy cooperative sensing; Networks; Performance enhancement; Radio; Stations; 合作计划; 感知; 无线电网络; 检测性能; 测算法; 相关矩阵; 线性模型; 频谱; energy cooperative sensing; cognitive radio; covariance matrix
• ISSN: 1007-0214; 1878-7606; 1007-0214
• DOI: 10.1016/S1007-0214(11)70056-6

Cooperative energy spectrum sensing has been widely applied in cognitive radio （CR） networks. In this paper, two cooperative sensing algorithms based on the received signals＇ correlation matrix were proposed. The first proposed algorithm made use of both diagonal elements and non-diagonal elements in the cooperative scheme. In the second algorithm, when the sensing station can obtain the information of the channel gains between the primary user and the sensing nodes, the weighted linear model can be adopted to improve the sensing performance. This paper analyzed the effectiveness of these two proposed coopera- tive algorithms and demonstrated that they can considerably improve the sensing performance compared with the traditional linear cooperative sensing algorithms. Simulation results showed that the sensing performance can be significantly enhanced by using the proposed algorithms, especially when the number of cooperative nodes is large.