Efficient Autoprecoder-based deep learning for massive MU-MIMO Downlink under PA Non-Linearities

Autor: Xinying Cheng, Rafik Zayani, Marin Ferecatu, Nicolas Audebert

Publikováno v: IEEE Wireless Communications and Networking Conference
IEEE Wireless Communications and Networking Conference, Apr 2022, Austin, United States
2022 IEEE Wireless Communications and Networking Conference (WCNC)
2022 IEEE Wireless Communications and Networking Conference (WCNC), Apr 2022, Austin, United States. pp.1039-1044, ⟨10.1109/WCNC51071.2022.9771695⟩

International audience; This paper introduces a new efficient autoprecoder (AP) based deep learning approach for massive multiple-input multiple-output (mMIMO) downlink systems in which the base station is equipped with a large number of antennas wit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db8a6688174f703baa3af49c38423410

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PAPR-Aware Massive MIMO-OFDM Downlink

Autor: Rafik Zayani, Hmaied Shaiek, Daniel Roviras

Publikováno v: IEEE Access
IEEE Access, Vol 7, Pp 25474-25484 (2019)
IEEE Access, IEEE, 2019, 7, pp.25474-25484. ⟨10.1109/ACCESS.2019.2900128⟩

International audience; We investigate the peak-to-average power ratio (PAPR) reduction problem in orthogonal frequency-division multiplexing (OFDM) based massive multiuser (MU) multiple-input multiple-output (MIMO) downlink systems. In this paper, w

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9203f1c93dd1be30721abba5e3862ba6