Sensitive white space detection with spectral covariance sensing

Authors:
Jaeweon Kim;Jeffrey G. Andrews
Affiliations:
Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX;Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX
Venue:
IEEE Transactions on Wireless Communications
Year:
2010

Citing 5
Cited 2

Digital signal processing (3rd ed.): principles, algorithms, and applications

Digital signal processing (3rd ed.): principles, algorithms, and applications
Cognitive PHY and MAC layers for dynamic spectrum access and sharing of TV bands

TAPAS '06 Proceedings of the first international workshop on Technology and policy for accessing spectrum
IEEE 802.22: the first cognitive radio wireless regional area network standard

IEEE Communications Magazine
A survey of spectrum sensing algorithms for cognitive radio applications

IEEE Communications Surveys & Tutorials
COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Spectrum Access in the Time Domain: Modeling and Exploiting White Space

IEEE Communications Magazine

A unified framework for the performance analyses of diversity energy detectors over fading channels

International Journal of Autonomous and Adaptive Communications Systems
A reconfigurable upper audio band modem for data communication between mobile devices

Analog Integrated Circuits and Signal Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

This paper proposes a novel, highly effective spectrum sensing algorithm for cognitive radio and white space applications. The proposed spectral covariance sensing (SCS) algorithm exploits the ditTerent statistical correlations of the received signal and noise in the frequency domam. Test statIstiCs are computed from the covariance matrix of a partial spectrogram and compared with a decision threshold to determine whether .a primary signal or arbitrary type is present or not. This detector Is analyzed theoretically and verified through realistic open-source simulations using actual digital television signals captured in the US. Compared to the state of the art in the literature, SCS improves sensitivity by 3 dB for the same dwell time, which is a very significant improvement for this application. Further, it is shown that SCS is highly robust to noise uncertainty, whereas many other spectrum sensors are not.