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MIMO Channel Prediction Using Recurrent Neural Networks

dc.contributor.authorPotter, Chris
dc.contributor.authorKosbar, Kurt
dc.contributor.authorPanagos, Adam
dc.date.accessioned2016-04-20T22:30:46Zen
dc.date.available2016-04-20T22:30:46Zen
dc.date.issued2008-10en
dc.identifier.issn0884-5123en
dc.identifier.issn0074-9079en
dc.identifier.urihttp://hdl.handle.net/10150/606193en
dc.descriptionITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, Californiaen_US
dc.description.abstractAdaptive modulation is a communication technique capable of maximizing throughput while guaranteeing a fixed symbol error rate (SER). However, this technique requires instantaneous channel state information at the transmitter. This can be obtained by predicting channel states at the receiver and feeding them back to the transmitter. Existing algorithms used to predict single-input single-output (SISO) channels with recurrent neural networks (RNN) are extended to multiple-input multiple-output (MIMO) channels for use with adaptive modulation and their performance is demonstrated in several examples.
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.language.isoen_USen
dc.publisherInternational Foundation for Telemeteringen
dc.relation.urlhttp://www.telemetry.org/en
dc.rightsCopyright © held by the author; distribution rights International Foundation for Telemeteringen
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectMultiple-input multiple-output (MIMO)en
dc.subjectChannel predictionen
dc.subjectRecurrent neural networksen
dc.subjectOnline trainingen
dc.subjectAdaptive modulationen
dc.subjectFlat fadingen
dc.titleMIMO Channel Prediction Using Recurrent Neural Networksen_US
dc.typetexten
dc.typeProceedingsen
dc.contributor.departmentMissouri University of Science and Technologyen
dc.contributor.departmentDynetics, Inc.en
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
refterms.dateFOA2018-09-11T09:11:05Z
html.description.abstractAdaptive modulation is a communication technique capable of maximizing throughput while guaranteeing a fixed symbol error rate (SER). However, this technique requires instantaneous channel state information at the transmitter. This can be obtained by predicting channel states at the receiver and feeding them back to the transmitter. Existing algorithms used to predict single-input single-output (SISO) channels with recurrent neural networks (RNN) are extended to multiple-input multiple-output (MIMO) channels for use with adaptive modulation and their performance is demonstrated in several examples.


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