Compressive SNR Estimation for Wideband Cognitive Radio under Correlated Scenarios

Sharma, Shree Krishna; Chatzinotas, Symeon; Ottersten, Björn

Reference : Compressive SNR Estimation for Wideband Cognitive Radio under Correlated Scenarios


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/18021

Title :	Compressive SNR Estimation for Wideband Cognitive Radio under Correlated Scenarios
Language :	English
Author, co-author :	Sharma, Shree Krishna [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	Apr-2014
Main document title :	Proceedings of IEEE Wireless Communications and Networking Conference
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	IEEE Wireless Communications and Networking Conference (WCNC)
Event date :	6-04-2014 to 09-04-2014
Event organizer :	IEEE
Event place (city) :	Istanbul
Event country :	Turkey
Keywords :	[en] Signal to Noise Ratio Estimation ; Random Matrix Theory ; Cognitive Radio ; Compressive Sensing
Abstract :	[en] Estimating the Signal to Noise Ratio (SNR) of the Primary Users’ (PUs) signals over a wideband spectrum accurately is crucial in order to fully exploit an under-utilized primary spectrum using underlay Cognitive Radio (CR) techniques. In this context, we study an SNR estimation problem for a wideband CR under practical correlated scenarios in compressive settings. We carry out detailed theoretical analysis for the considered scenarios and then derive the expressions for the asymptotic eigenvalue probability distribution function (aepdf) of the measured signal’s covariance matrix using asymptotic Random Matrix Theory. Subsequently, based on the derived aepdfs, we present a technique to estimate the PU SNR over a wideband spectrum with compressive measurements. The performance of the proposed technique is evaluated in terms of normalized Mean Square Error (MSE) and it is shown that the SNR of the PU signals over the wideband spectrum can be reliably estimated using the proposed technique.
Target :	Researchers ; Professionals ; Students ; Others
Permalink :	http://hdl.handle.net/10993/18021

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