Publikation: An Exponentially-Tight Approximate Fact...
Stammdaten
Titel: | An Exponentially-Tight Approximate Factorization of the Joint PDF of Statistical Dependent Measurements in Wireless Sensor Networks |
Untertitel: | |
Kurzfassung: | We consider the distributed detection problem of a temporally correlated random radio source signal using a wireless sensor network capable of measuring the energy of the received signals. It is well-known that optimal tests in the Neyman-Pearson setting are based on likelihood ratio tests (LRT), which, in this set-up, evaluate the quotient between the probability density functions (PDF) of the measurements when the source signal is present and absent. When the source is present, the computation of the joint PDF of the energy measurements at the nodes is a challenging problem. This is due to the statistical dependence introduced to the received signals by the propagation through fading channels of the radio signal emitted by the source. We deal with this problem using the characteristic function of the (intractable) joint PDF, and proposing an approximation to it. We derive bounds for the approximation error in two wireless propagation scenarios, slow and fast fading, and show that the proposed approximation is exponentially tight with the number of nodes when the time-bandwidth product is sufficiently high. The approximation is used as a substitute of the exact joint PDF for building an approximate LRT, which performs better than other well-known detectors, as verified by Monte Carlo simulations. |
Schlagworte: | Probability density function, Wireless sensor networks, Energy measurement, Fading channels, Sensors, Light rail systems, Correlation |
Publikationstyp: | Beitrag in Zeitschrift (Autorenschaft) |
Erscheinungsdatum: | 13.11.2023 (Online) |
Erschienen in: |
IEEE Open Journal of the Communications Society
IEEE Open Journal of the Communications Society
(
IEEE;
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zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Heftnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | - |
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Keine Version vorhanden |
Erscheinungsdatum: | 13.11.2023 |
ISBN (e-book): | - |
eISSN: | 2644-125X |
DOI: | http://dx.doi.org/10.1109/OJCOMS.2023.3332259 |
Homepage: | https://ieeexplore.ieee.org/document/10315166/keywords#keywords |
Open Access |
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AutorInnen
Zuordnung
Organisation | Adresse | ||||
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Fakultät für Technische Wissenschaften
Institut für Vernetzte und Eingebettete Systeme
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AT - 9020 Klagenfurt am Wörthersee |
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