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Performance Analysis of Multi-Antenna Hybrid Detectors and Optimization with Noise Variance Estimation

Authors:
Daniel Riviello
Pawan Dhakal
Roberto Garello

Keywords: hybrid detector; largest eigenvector; noise estimation; spectrum sensing; cognitive radio.

Abstract:
In this paper, a performance analysis of multi-antenna spectrum sensing techniques is carried out. Both well known algorithms, such as Energy Detector (ED) and eigenvalue based detectors, and an eigenvector based algorithm, are considered. With the idea of auxiliary noise variance estimation, the performance analysis is extended to the hybrid approaches of the considered detectors. Moreover, optimization for Hybrid ED under constant estimation plus detection time is performed. Performance results are evaluated in terms of Receiver Operating Characteristic (ROC) curves and performance curves, i.e., detection probability as a function of the Signal-to-Noise Ratio (SNR). It is concluded that the eigenvector based detector and its hybrid approach are able to approach the optimal Neyman-Pearson performance.

Pages: 14 to 19

Copyright: Copyright (c) IARIA, 2015

Publication date: April 19, 2015

Published in: conference

ISSN: 2308-4251

ISBN: 978-1-61208-403-9

Location: Barcelona, Spain

Dates: from April 19, 2015 to April 24, 2015