Web: http://arxiv.org/abs/2201.06778

Jan. 20, 2022, 2:11 a.m. | Zhen Gao, Minghui Wu, Chun Hu, Feifei Gao, Guanghui Wen, Dezhi Zheng, Jun Zhang

cs.LG updates on arXiv.org arxiv.org

In an aerial hybrid massive multiple-input multiple-output (MIMO) and
orthogonal frequency division multiplexing (OFDM) system, how to design a
spectral-efficient broadband multi-user hybrid beamforming with a limited pilot
and feedback overhead is challenging. To this end, by modeling the key
transmission modules as an end-to-end (E2E) neural network, this paper proposes
a data-driven deep learning (DL)-based unified hybrid beamforming framework for
both the time division duplex (TDD) and frequency division duplex (FDD) systems
with implicit channel state information (CSI). For …

arxiv cross data data-driven deep deep learning hybrid learning systems

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