Covariance-Based Spectrum Sensing for Noncircular Signal in Cognitive Radio Networks With Uncalibrated Multiple Antennas
An-Zhi Chen, Zhiping Shi
Abstract
In this letter, the problem of spectrum sensing is addressed for noncircular (NC) signal in cognitive radio networks with uncalibrated multiple antennas. Specifically, by taking both the standard covariance and complementary covariance information of the NC signal into account, a new robust spectrum sensing method called NC covariance (NCC) is proposed, which can fully reap the statistical property of the NC signals. Meanwhile, we derive the asymptotic distribution of the NCC statistic under the signal-absence hypothesis and obtain the theoretical decision threshold of the NCC method. Simulation results demonstrate that the proposed method is capable of outperforming state-of-the-art methods.
Topics & Concepts
Cognitive radioCovarianceSIGNAL (programming language)Computer scienceStatisticCovariance matrixAlgorithmSpectrum (functional analysis)MathematicsTelecommunicationsStatisticsWirelessPhysicsProgramming languageQuantum mechanicsCognitive Radio Networks and Spectrum SensingBlind Source Separation TechniquesDistributed Sensor Networks and Detection Algorithms