Spectrum Sensing Using Weighted Covariance Matrix in Rayleigh Fading Channels

• Published in: IEEE transactions on vehicular technology Vol. 64; no. 11; pp. 5137 - 5148
• Main Authors: Ming Jin, Qinghua Guo, Jiangtao Xi, Youming Li, Yanguang Yu, Huang, Defeng David
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-11-2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Antennas; Cognitive radio; Correlation; Covariance matrices; data-aided weighting; Detectors; Manganese; signal correlation; Signal to noise ratio; spectrum sensing; Cognitive radio; signal correlation; spectrum sensing; data-aided weighting
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2014.2379924

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.