ANTENNA SYSTEM PRECODING METHOD AND APPARATUS BASED ON TWO TIME SCALES AND DEEP LEARNING

WIPO Patent Application WO/2023/035736

A1

An antenna system precoding method and apparatus based on two time scales and deep learning. The method comprises: constructing a long-time-scale deep neural network (DNN) and a short-time-scale DNN, wherein the constructed DNNs each comprise a plurality of sub-networks corresponding to a transceiver of a large-scale millimeter wave multiple-input-multiple-output system; training the constructed DNNs by means of training data; acquiring a signal to be transmitted, performing high-dimensional pilot frequency estimation and high-dimensional channel feedback by means of a trained long-time-scale DNN, and performing low-dimensional pilot frequency estimation and low-dimensional channel feedback by means of the short-time-scale DNN; and performing analog precoding and digital precoding according to a high-dimensional original channel matrix and by means of the long-time-scale DNN, and performing digital precoding according to a low-dimensional equivalent channel matrix and by means of the short-time-scale DNN. By means of the method, the signaling overheads can be reduced, the robustness of a system can be improved, and modules in the system are jointly designed, thereby reducing the calculation complexity.

HU QIYU (CN)
CAI YUNLONG (CN)
KANG KAI (CN)
LI MIN (CN)
ZHAO MINJIAN (CN)

PCT/CN2022/102833

March 16, 2023

June 30, 2022

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UNIV ZHEJIANG (CN)

H04L5/00

WO2020092391A1	2020-05-07
WO2020188316A1	2020-09-24

CN113972939A	2022-01-25
CN107332598A	2017-11-07
CN110099016A	2019-08-06
CN113162666A	2021-07-23

TSINGYIHUA INTELLECTUAL PROPERTY LLC (CN)

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