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Fast multilevel quantization for distributed detection based on Gaussian approximation

 
: Gül, Gökhan; Baßler, Michael

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Fulltext (PDF; )

Heusdens, Richard (Hrsg.) ; European Association for Signal Processing -EURASIP-:
28th European Signal Processing Conference, EUSIPCO 2020. Proceedings : 24-28 August 2020, Amsterdam, the Netherlands
Amsterdam: EURASIP, 2020
ISBN: 978-9-0827-9705-3
ISBN: 978-9-08279-704-6
ISBN: 978-1-7281-5001-7
pp.2433-2437
European Signal Processing Conference (EUSIPCO) <28, 2020, Amsterdam/cancelled>
European Signal Processing Conference (EUSIPCO) <28, 2021, Online>
English
Conference Paper, Electronic Publication
Fraunhofer IMM ()
detector; Detektor; distributed detection; quantization; multisensor systems; cognitive Radio; wireless sensor networks; signal detection; Multisensorsystem; Multisensor; Sensor

Abstract
An iterative algorithm is derived for multilevel quantization of sensor observations in distributed sensor networks, where each sensor transmits a summary of its observation to the fusion center and the fusion center makes the final decision. The proposed scheme is composed of a person-by-person optimum quantization at each sensor and a Gaussian approximation to the distribution of the test statistic at the fusion center. The complexity of the algorithm is linear both for identically and nonidentically distributed independent sensors. Experimental results indicate that the proposed scheme is promising in comparison to the current state-of-the-art.

: http://publica.fraunhofer.de/documents/N-615662.html