Towards 6G: Deep Learning in Cell-Free Massive MIMO

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Towards 6G: Deep Learning in Cell-Free Massive MIMO

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  • June 6, 2022
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Lazaros Alexios Iliadis, Zaharias D Zaharis, Sotirios P Sotiroudis, Panagiotis Sarigiannidis, George K Karagiannidis, Sotirios K Goudos: Towards 6G: Deep Learning in Cell-Free Massive MIMO. 2022 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), 2022, ISBN: 978-1-6654-9749-7.

Abstract

Massive Multiple-Input-Multiple-Output (MIMO) technology is considered a crucial part of the fifth generation (5G) telecommunications systems. However, moving towards sixth generation (6G) wireless networks, novel solutions have to be incorporated into the current telecommunications' systems. Cell-free Massive MIMO and especially the user-centric approach, seems to be the most promising idea to this direction at this moment. Nevertheless, there are many open issues to be resolved. Deep Learning has been successfully applied to a wide range of problems in many different fields, including wireless communications. In this paper, a review of the state-of-the-art Deep Learning methods applied to Cell-free Massive MIMO communications systems is provided. In addition future research directions are discussed.

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BibTeX (Download)

@conference{9858306,
title = {Towards 6G: Deep Learning in Cell-Free Massive MIMO},
author = {Lazaros Alexios Iliadis and Zaharias D Zaharis and Sotirios P Sotiroudis and Panagiotis Sarigiannidis and George K Karagiannidis and Sotirios K Goudos},
url = {https://www.researchgate.net/publication/362924666_Towards_6G_Deep_Learning_in_Cell-Free_Massive_MIMO},
doi = {10.1109/BlackSeaCom54372.2022.9858306},
isbn = {978-1-6654-9749-7},
year  = {2022},
date = {2022-06-06},
booktitle = {2022 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)},
pages = {269-273},
abstract = {Massive Multiple-Input-Multiple-Output (MIMO) technology is considered a crucial part of the fifth generation (5G) telecommunications systems. However, moving towards sixth generation (6G) wireless networks, novel solutions have to be incorporated into the current telecommunications' systems. Cell-free Massive MIMO and especially the user-centric approach, seems to be the most promising idea to this direction at this moment. Nevertheless, there are many open issues to be resolved. Deep Learning has been successfully applied to a wide range of problems in many different fields, including wireless communications. In this paper, a review of the state-of-the-art Deep Learning methods applied to Cell-free Massive MIMO communications systems is provided. In addition future research directions are discussed.},
keywords = {6G, Cell-free massive MIMO, Deep Learning, User-centric cell-free massive MIMO},
pubstate = {published},
tppubtype = {conference}
}
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