Spectrum sensing using weighted covariance matrix in Rayleigh fading channels

Authors

Ming Jin, University of WollongongFollow
Qinghua Guo, University of WollongongFollow
Jiangtao Xi, University of WollongongFollow
Youming Li, Ningbo University
Yanguang Yu, University of WollongongFollow
Defeng Huang, University of Western AustraliaFollow

RIS ID

104219

Publication Details

M. Jin, Q. Guo, J. Xi, Y. Li, Y. Yu & D. Huang, "Spectrum sensing using weighted covariance matrix in Rayleigh fading channels," IEEE Transactions on Vehicular Technology, vol. 64, (11) pp. 5137-5148, 2015.

Abstract

Covariance-based detection is a low-complexity blind spectrum sensing scheme that exploits spatial and/or temporal correlations of primary signals. However, its performance severely degrades with the decrease of signal correlations. In this work, a weighted-covariance-based detector is proposed by introducing data-aided weights to the covariance matrix. The false alarm probability, decision threshold, and detection probability are analyzed in the low signal-to-noise ratio (SNR) regime, and their approximate analytical expressions are derived based on the central limit theorem. The analyses are verified through simulations. Experiments with simulated multiple-antenna signals and field measurement digital television signals show that the proposed weighted detection can significantly outperform the original covariance-based detection.

Grant Number

ARC/DE120101266

Additional Grant Number

http://purl.org/au-research/grants/ARC/DE120101266