DocumentCode :
1890425
Title :
Measurement clustering criteria for localization of multiple transmitters
Author :
Nasif, Ahmed O. ; Mark, Brian L.
Author_Institution :
Dept. of Electr. & Comput. Eng., George Mason Univ., Fairfax, VA
fYear :
2009
fDate :
18-20 March 2009
Firstpage :
341
Lastpage :
345
Abstract :
We consider the problem of localizing multiple cochannel transmitters belonging to a licensed or primary network using signal strength measurements taken by a group of unlicensed or secondary nodes. Traditional localization techniques can be applied to multiple transmitter localization, provided that: (1) the total number of cochannel transmitters in the system is known, and (2) an appropriate set of clustered measurements is available. In this paper, we present two criteria to determine the total number of cochannel transmitters in the primary system. The first criterion is called the net MMSE criterion, which uses the Cramer-Rao lower bound on localization accuracy. The second criterion is the information theoretic criterion, minimum description length. Both of these criteria lead to measurement clustering algorithms in a natural way. Although we consider only signal strength measurements, the approach can be generalized to include other types of observations (e.g., time and angle information) with independent measurements in additive noise. Our numerical results demonstrate the effectiveness of the proposed approach to measurement clustering.
Keywords :
cognitive radio; least mean squares methods; pattern clustering; radio transmitters; Cramer-Rao lower bound; MMSE criterion; clustering criteria measurement; cognitive radios; least mean squares methods; minimum description length; multiple cochannel transmitters; multiple transmitters localization; opportunistic spectrum access schemes; signal strength measurements; Clustering algorithms; Cognitive radio; Computer networks; Drives; Electric variables measurement; Frequency; Interchannel interference; Noise measurement; Radio transmitters; Time measurement; Cramér-Rao bound; Localization; clustering; minimum description length;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Sciences and Systems, 2009. CISS 2009. 43rd Annual Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-2733-8
Electronic_ISBN :
978-1-4244-2734-5
Type :
conf
DOI :
10.1109/CISS.2009.5054742
Filename :
5054742
Link To Document :
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