Paper Info
Title
SFET-Based Multiple Antenna Spectrum Sensing Using the Second Order Moments of Eigenvalues.
Abstract
In this paper, we propose a new detector for multiantenna spectrum sensing in cognitive radios (CR) by exploiting the Separating Function Estimation Test (SFET) framework. Specifically, we consider a blind scenario for multiantenna spectrum sensing in which both the channel gains and noise variance are assumed to be unknown. For such a scenario, we find an appropriate Separating Function (SF) whose Maximum Likelihood Estimate (MLE) leads us to a SFET-based detector which uses the second order moments of the eigenvalues of the Sample Covariance Matrix (SCM). We also find closed-form expressions for the detection and false-alarm probabilities of the proposed detector. The performance of the proposed detector asymptotically tends to that of the Uniformly Most Powerful Unbiased (UMPU) detector as the number of independent and identically distributed observations increases. In addition, simulation results show that the proposed detector outperforms the state-of-art eigenvalue-based detectors because of using the second order moments of the SCM eigenvalues.
Year
DOI
Venue
2015
10.1109/GLOCOM.2015.7417100
IEEE Global Communications Conference
Field
DocType
ISSN
Mathematical optimization,Estimation of covariance matrices,Expression (mathematics),Computer science,Communication channel,Algorithm,Real-time computing,Second order moments,Independent and identically distributed random variables,Detector,Eigenvalues and eigenvectors,Cognitive radio
Conference
2334-0983
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Saeid Sedighi1215.80
Abbas Taherpour223019.77
Saeed Gazor382270.56
Tamer Khattab416948.36