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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nasif, A.O. Mark, B.L. |
| Copyright Year | 2009 |
| Description | Author affiliation: Dept. of Electrical and Computer Engineering, George Mason University, MS 1G5, 4400 University Drive, Fairfax, VA, USA (Nasif, A.O.; Mark, B.L.) |
| 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 Cramér-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. |
| Starting Page | 341 |
| Ending Page | 345 |
| File Size | 159514 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424427338 |
| DOI | 10.1109/CISS.2009.5054742 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-03-18 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Radio transmitters Drives Time measurement Noise measurement Cognitive radio Electric variables measurement Clustering algorithms Frequency Computer networks clustering minimum description length Localization Interchannel interference Cramér-Rao bound |
| Content Type | Text |
| Resource Type | Article |
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