Nurellari, E, McLernon, D, Ghogho, M et al. (1 more author) (2014) Optimal quantization and power allocation for energy-based distributed sensor detection. In: 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO). European Signal Processing Conference, 01-05 Sep 2014, Lisbon. Institute of Electrical and Electronics Engineers , 141 - 145. ISBN 9780992862619
Abstract
We consider the decentralized detection of an unknown deterministic signal in a spatially uncorrelated distributed wireless sensor network. N samples from the signal of interest are gathered by each of the M spatially distributed sensors, and the energy is estimated by each sensor. The sensors send their quantized information over orthogonal channels to the fusion center (FC) which linearly combines them and makes a final decision. We show how by maximizing the modified deflection coefficient we can calculate the optimal transmit power allocation for each sensor and the optimal number of quantization bits to match the channel capacity.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2014, Institute of Electrical and Electronics Engineers. This is an author produced version of a paper published in 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO. Uploaded in accordance with the publisher's self-archiving policy |
Keywords: | Distributed detection; soft decision; wireless sensor networks |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Apr 2015 15:37 |
Last Modified: | 19 Jan 2018 19:49 |
Published Version: | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?... |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:84147 |