MIMO Channel Prediction Using Recurrent Neural Networks
ITC/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, California === Adaptive modulation is a communication technique capable of maximizing throu...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Language: | en_US |
| Published: |
International Foundation for Telemetering
2008
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10150/606193 http://arizona.openrepository.com/arizona/handle/10150/606193 |
| Summary: | ITC/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, California === 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. |
|---|