DocumentCode :
674921
Title :
Primary receiver localization using sparsity and interference tweets
Author :
Dall´Anese, Emiliano ; Marques, Antonio G. ; Giannakis, Georgios
Author_Institution :
Dept. of ECE, Univ. of Minnesota, Minneapolis, MN, USA
fYear :
2013
fDate :
15-18 Dec. 2013
Firstpage :
452
Lastpage :
455
Abstract :
A hierarchical access setup is considered, where secondary users can (re-)use frequency bands allocated to licensed systems, provided ongoing primary communications are not overly disrupted. Since conventional spectrum sensing schemes can detect and localize “active” sources but not “passive” users, the number of primary receivers and their locations are generally unknown. Supposing a minimal coordination between primary and secondary systems, a novel method for unveiling areas where primary receivers are located is proposed in this paper. The primary system broadcasts short messages - here refereed to as “interference tweets” - indicating the number of receivers that are interfered. Using these tweets, together with a grid-based discretization of the primary coverage region, the locations where receivers are likely to reside are obtained by solving a sparse linear regression problem. Subsequently, the estimated locations are used to optimize resource allocation of the secondary network operation under interference constraints.
Keywords :
channel allocation; interference (signal); radio receivers; radio spectrum management; regression analysis; signal detection; grid-based discretization; hierarchical access setup; interference tweets; primary coverage region; primary receiver localization; resource allocation; secondary network operation; short message; sparse linear regression problem; sparsity tweets; spectrum sensing scheme; Bayes methods; Indexes; Interference; Receivers; Resource management; Sensors; Vectors; Cognitive radios; receiver localization; sparsity; underlay access;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013 IEEE 5th International Workshop on
Conference_Location :
St. Martin
Print_ISBN :
978-1-4673-3144-9
Type :
conf
DOI :
10.1109/CAMSAP.2013.6714105
Filename :
6714105
Link To Document :
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