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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Maya, J.A. Rey Vega, L. Galarza, C.G. Altieri, A. |
| Copyright Year | 2014 |
| Description | Author affiliation: Univ. of Buenos Aires, Buenos Aires, Argentina (Maya, J.A.; Rey Vega, L.; Galarza, C.G.; Altieri, A.) |
| Abstract | We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN). Using Large Deviation Theory (LDT), we compute the probability error exponents of a distributed scheme for detecting a correlated circularly-symmetric complex Gaussian process under the Neyman-Pearson framework. Using an analog scheme, the sensors transmit scaled versions of their measurements several times through a multiple access channel (MAC) to reach the fusion center (FC), whose task is to decide whether the process is present or not. In the analysis, we consider the energy constraint on each node transmission. We show that the proposed distributed scheme requires relatively few MAC channel uses to achieve the centralized error exponents when detecting correlated Gaussian processes. |
| Starting Page | 133 |
| Ending Page | 136 |
| File Size | 245168 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781479914814 |
| ISSN | 2151870X |
| DOI | 10.1109/SAM.2014.6882358 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-22 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Detectors Bandwidth Wireless sensor networks Covariance matrices Gaussian processes Vectors Communication channels |
| Content Type | Text |
| Resource Type | Article |
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