Decentralized Random-Field Estimation for Sensor Networks Using Quantized Spatially Correlated Data and Fusion-Center Feedback
dc.contributor.author | Dogandžić, Aleksandar | |
dc.contributor.author | Qiu, Kun | |
dc.contributor.department | Department of Electrical and Computer Engineering | |
dc.date | 2018-02-14T00:56:18.000 | |
dc.date.accessioned | 2020-06-30T02:03:27Z | |
dc.date.available | 2020-06-30T02:03:27Z | |
dc.date.copyright | Tue Jan 01 00:00:00 UTC 2008 | |
dc.date.embargo | 2014-04-30 | |
dc.date.issued | 2008-12-01 | |
dc.description.abstract | <p>In large-scale wireless sensor networks, sensor-processor elements (nodes) are densely deployed to monitor the environment; consequently, their observations form a random field that is highly correlated in space. We consider a fusion sensor-network architecture where, due to the bandwidth and energy constraints, the nodes transmit quantized data to a fusion center. The fusion center provides feedback by broadcasting summary information to the nodes. In addition to saving energy, this feedback ensures reliability and robustness to node and fusion-center failures. We assume that the sensor observations follow a linear-regression model with known spatial covariances between any two locations within a region of interest. We propose a Bayesian framework for adaptive quantization, fusion-center feedback, and estimation of the random field and its parameters. We also derive a simple suboptimal scheme for estimating the unknown parameters, apply our estimation approach to the no-feedback scenario, discuss field prediction at arbitrary locations within the region of interest, and present numerical examples demonstrating the performance of the proposed methods.</p> | |
dc.description.comments | <p>This is a post-print of an article from <em>IEEE Transactions on Signal Processing</em> 56 (2008): 6069–6085, doi:<a href="http://dx.doi.org/10.1109/TSP.2008.2005753" target="_blank">10.1109/TSP.2008.2005753</a>. Posted with permission.</p> | |
dc.format.mimetype | application/pdf | |
dc.identifier | archive/lib.dr.iastate.edu/ece_pubs/6/ | |
dc.identifier.articleid | 1008 | |
dc.identifier.contextkey | 5540323 | |
dc.identifier.s3bucket | isulib-bepress-aws-west | |
dc.identifier.submissionpath | ece_pubs/6 | |
dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/21119 | |
dc.language.iso | en | |
dc.source.bitstream | archive/lib.dr.iastate.edu/ece_pubs/6/2008_DogandzicA_DecentralizedRandomfieldEstimation.pdf|||Sat Jan 15 01:05:42 UTC 2022 | |
dc.source.uri | 10.1109/TSP.2008.2005753 | |
dc.subject.disciplines | Signal Processing | |
dc.subject.keywords | Parameter estimation | |
dc.subject.keywords | Random processes | |
dc.subject.keywords | Wireless sensor networks | |
dc.title | Decentralized Random-Field Estimation for Sensor Networks Using Quantized Spatially Correlated Data and Fusion-Center Feedback | |
dc.type | article | |
dc.type.genre | article | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | c910f7d3-c386-4c37-8143-4e653a539aa9 | |
relation.isOrgUnitOfPublication | a75a044c-d11e-44cd-af4f-dab1d83339ff |
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