@inproceedings{17998023a8b2431eba7d14ec0cf1ed65,
title = "Deep Learning Approach for Improving Spectral Efficiency in mmWave Hybrid Beamforming Systems",
abstract = "Hybrid beamformer design plays an important role in millimeter wave multiple input multiple output systems. In this paper, we propose a deep learning (DL) neural network for hybrid precoders and combiners to improve spectral efficiency. With the received signal and channel matrix as the input, the proposed DL network estimates the beamformer matrix as output. The proposed DL approach does not require prior knowledge such as angle features and channel information. Thus, it provides improved spectral efficiency compared to non-DL approaches.",
keywords = "deep learning, Hybrid beamforming, millimeter wave",
author = "Woosung Son and Han, {Dong Seog}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 27th Asia-Pacific Conference on Communications, APCC 2022 ; Conference date: 19-10-2022 Through 21-10-2022",
year = "2022",
doi = "10.1109/APCC55198.2022.9943726",
language = "English",
series = "APCC 2022 - 27th Asia-Pacific Conference on Communications: Creating Innovative Communication Technologies for Post-Pandemic Era",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "66--69",
booktitle = "APCC 2022 - 27th Asia-Pacific Conference on Communications",
address = "United States",
}