Paper Info
Title
Eigenvalue-Based Multiple Antenna Spectrum Sensing: Higher Order Moments.
Abstract
The problem of multiple antenna spectrum sensing in cognitive radio (CR) networks is studied in this paper. We propose two new invariant constant false-alarm rate eigenvalue-based (EVB) detectors, using the higher order moments of the sample covariance matrix eigenvalues, by exploiting the separating function estimation test framework. We find closed-form expressions for the false-alarm and detection probabilities of the proposed detectors by providing moment-based approximations of their statistical distributions. The accuracy of the obtained closed-form expressions is validated by Monte Carlo simulations. In addition, we compare the performance of the proposed detectors with that of their two counterparts, i.e., John’s and the arithmetic to geometric mean (AGM) detectors, in terms of the asymptotic relative efficiency. This comparison enables us to demonstrate the superiority of our proposed detectors over those detectors within the typical range of signal-to-noise ratio in CR application. The comparative simulation results also illustrate the superiority of the proposed detectors over John’s and the AGM detectors as well as some other state-of-the-art EVB algorithms given in the literature.
Year
DOI
Venue
2017
10.1109/TWC.2016.2640299
IEEE Trans. Wireless Communications
Keywords
Field
DocType
Detectors,Eigenvalues and eigenfunctions,Covariance matrices,Cascading style sheets,Antennas,Signal to noise ratio
Mathematical optimization,Monte Carlo method,Expression (mathematics),Signal-to-noise ratio,Algorithm,Real-time computing,Probability distribution,Invariant (mathematics),Detector,Mathematics,Eigenvalues and eigenvectors,Cognitive radio
Journal
Volume
Issue
ISSN
16
2
1536-1276
Citations 
PageRank 
References 
0
0.34
28
Authors
4
Name
Order
Citations
PageRank
Saeid Sedighi1215.80
Abbas Taherpour223019.77
Saeed Gazor3195.29
Tamer Khattab416948.36