Combined energy detection and one-order cyclostationary feature detection techniques in cognitive radio systems

• Published in: Journal of China universities of posts and telecommunications Vol. 17; no. 4; pp. 18 - 25
• Main Authors: YUE, Wen-jing, ZHENG, Bao-yu, MENG, Qing-min, YUE, Wen-jie
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2010; Institute of Signal Processing and Transmission,Nanjing University of Posts and Telecommunications,Nanjing 210003,China%Institute of Signal Processing and Transmission,Nanjing University of Posts and Telecommunications,Nanjing 210003,China; Department of Electronic Engineering,Shanghai Jiaotong University,Shanghai 200240,China%Shanxi Institute of Educational Science,Taiyuan 030009,China
• Subjects: Algorithms; cognitive radio (CR); cyclostationary feature detector; Detection; energy detector; Focusing; Hardware; Mathematical analysis; Power consumption; Radio; spectrum sensing; Time domain; 循环平稳特性; 无线电系统; 检测性能; 检测技术; 特征检测; 能量检测; 计算复杂度; energy detector; cognitive radio (CR); spectrum sensing; cyclostationary feature detector; cognitive radio(CR); energy detectur
• ISSN: 1005-8885
• DOI: 10.1016/S1005-8885(09)60482-9

One of the main requirements of cognitive radio systems is the ability to detect the presence of the primary user with fast speed and precise accuracy. To achieve that, a possible two-stage spectrum sensing scheme is suggested in this paper. More specifically, a fast spectrum sensing algorithm based on the energy detection is introduced focusing on the coarse detection. A complementary fine spectrum sensing algorithm adopts one-order cyclostationary properties of primary user＇s signals in time domain. Since the one-order feature detection is performed in time domain, the real-time operation and low-computational complexity can be achieved. Also, it drastically reduces hardware burdens and power consumption as opposed to two-order feature detection. The sensing performance of the proposed method is studied and the analytical performance results are given. The results indicate that better performance can be achieved in proposed two-stage sensing detection compared to the conventional energy detector.