Affiliation
Missouri University of Science and TechnologyDynetics, Inc.
Issue Date
2008-10Keywords
Multiple-input multiple-output (MIMO)Channel prediction
Recurrent neural networks
Online training
Adaptive modulation
Flat fading
Metadata
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Copyright © held by the author; distribution rights International Foundation for TelemeteringCollection Information
Proceedings 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.Abstract
Adaptive 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.Sponsors
International Foundation for TelemeteringISSN
0884-51230074-9079