Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
L. Ribeiro, S. Schwarz, A. Almeida, M. Haardt:
"Low-Complexity Massive MIMO Tensor Precoding";
Vortrag: Asilomar Conference on Signals, Systems, and Computers,
Pacific Grove, CA;
01.11.2020
- 05.11.2020; in: "Proc. Asilomar Conference on Signals, Systems, and Computers",
(2020),
ISBN: 978-0-7381-3126-9;
S. 1
- 8.
Kurzfassung englisch:
We present a novel and low-complexity massive multiple-input multiple-output precoding strategy based on novel findings concerning the subspace separability of Rician fading channels. Considering a uniform planar array at the base station, we show that the subspaces spanned by the channel vectors can be factorized as a tensor product between two low-dimensional subspaces. Based on this result, we formulate tensor maximum
ratio transmit and zero-forcing precoders. We show that the
proposed tensor precoders exhibit lower computational complexity
and require less instantaneous channel state information than their linear counterparts. Finally, we present computer simulations that demonstrate the applicability of the proposed
tensor precoders in practical communication scenarios.
Schlagworte:
Massive MIMO, tensors, precoding
"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/IEEECONF51394.2020.9443492
Elektronische Version der Publikation:
https://publik.tuwien.ac.at/files/publik_290030.pdf
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.