Deep-Learning Aided Channel Training and Precoding in FDD Massive MIMO with Channel Statistics Knowledge

We propose a method for channel training and precoding in FDD massive MIMO based on deep neural networks (DNNs), exploiting Downlink (DL) channel covariance knowledge. The DNN is optimized to maximize the DL multi-user sum-rate, by producing a pre-beamforming matrix based on user channel covariances...

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Bibliographic Details

Published in:	IEEE International Conference on Communications (2003) pp. 2791 - 2797
Main Authors:	Song, Yi, Yang, Tianyu, Khalilsarai, Mahdi Barzegar, Caire, Giuseppe
Format:	Conference Proceeding
Language:	English
Published:	IEEE 28.05.2023
Subjects:	analog feedback Artificial neural networks Channel estimation channel statistics knowledge DNN-based training and precoding FDD massive MIMO Knowledge engineering Microprocessors Precoding Scattering Training
ISSN:	1938-1883
Online Access:	Get full text
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