Decentralized Massive MIMO Systems: Is There Anything to be Discussed?
Sanchez, Jesus Rodriguez LU ; Vidal Alegria, Juan LU
and Rusek, Fredrik
LU
(2019)
2019 IEEE International Symposium on Information Theory, ISIT 2019
2019-July.
p.787-791
- Abstract
Algorithms for Massive MIMO uplink detection are typically based on a centralized approach, by which baseband data from all antenna modules need to be routed to a central node for further processing. In the case of Massive MIMO, where hundreds or thousands of antennas are expected in the base-station, such architecture requires high interconnection bandwidth between antennas and the central node. Recently, decentralized architectures have been proposed to maintain low interconnection bandwidth, where channel-state-information (CSI) is obtained locally in each antenna node and not shared. Further, Massive MIMO performance is sensitive to CSI quality. However, in the literature, ideal CSI is typically assumed in decentralized systems,... (More)
Algorithms for Massive MIMO uplink detection are typically based on a centralized approach, by which baseband data from all antenna modules need to be routed to a central node for further processing. In the case of Massive MIMO, where hundreds or thousands of antennas are expected in the base-station, such architecture requires high interconnection bandwidth between antennas and the central node. Recently, decentralized architectures have been proposed to maintain low interconnection bandwidth, where channel-state-information (CSI) is obtained locally in each antenna node and not shared. Further, Massive MIMO performance is sensitive to CSI quality. However, in the literature, ideal CSI is typically assumed in decentralized systems, which is not only far from reality but also limits the generality of the analysis.This paper proposes a decentralized (a term that will be defined in the main body of the paper) architecture with the following main features: (i) the channel matrix is not made available at any single node, (ii) there is no inter-communication among antennas, (iii) the architecture used during the payload data phase, is reused to provide a certain statistic to a processing node, (iv) A non-standard channel estimation problem based on said statistic arises, (v) a matrix inversion is needed (in case of zero-forcing) at said processing node.A hefty share of the paper is devoted to (iv).
(Less)
- author
- Sanchez, Jesus Rodriguez
LU
; Vidal Alegria, Juan
LU
and Rusek, Fredrik
LU
- organization
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- decentralized, detection, MAP, Massive MIMO, ML, MMSE, wishart, zero-forcing
- host publication
- 2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
- volume
- 2019-July
- article number
- 8849465
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2019 IEEE International Symposium on Information Theory, ISIT 2019
- conference location
- Paris, France
- conference dates
- 2019-07-07 - 2019-07-12
- external identifiers
-
- scopus:85073149812
- ISBN
- 9781538692912
- DOI
- 10.1109/ISIT.2019.8849465
- language
- English
- LU publication?
- yes
- id
- e1ca883c-f64f-46bb-b68f-9e8dc38f1589
- date added to LUP
- 2019-10-23 13:49:49
- date last changed
- 2022-09-29 14:40:53
@inproceedings{e1ca883c-f64f-46bb-b68f-9e8dc38f1589,
abstract = {{<p>Algorithms for Massive MIMO uplink detection are typically based on a centralized approach, by which baseband data from all antenna modules need to be routed to a central node for further processing. In the case of Massive MIMO, where hundreds or thousands of antennas are expected in the base-station, such architecture requires high interconnection bandwidth between antennas and the central node. Recently, decentralized architectures have been proposed to maintain low interconnection bandwidth, where channel-state-information (CSI) is obtained locally in each antenna node and not shared. Further, Massive MIMO performance is sensitive to CSI quality. However, in the literature, ideal CSI is typically assumed in decentralized systems, which is not only far from reality but also limits the generality of the analysis.This paper proposes a decentralized (a term that will be defined in the main body of the paper) architecture with the following main features: (i) the channel matrix is not made available at any single node, (ii) there is no inter-communication among antennas, (iii) the architecture used during the payload data phase, is reused to provide a certain statistic to a processing node, (iv) A non-standard channel estimation problem based on said statistic arises, (v) a matrix inversion is needed (in case of zero-forcing) at said processing node.A hefty share of the paper is devoted to (iv).</p>}},
author = {{Sanchez, Jesus Rodriguez and Vidal Alegria, Juan and Rusek, Fredrik}},
booktitle = {{2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings}},
isbn = {{9781538692912}},
keywords = {{decentralized; detection; MAP; Massive MIMO; ML; MMSE; wishart; zero-forcing}},
language = {{eng}},
pages = {{787--791}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Decentralized Massive MIMO Systems: Is There Anything to be Discussed?}},
url = {{http://dx.doi.org/10.1109/ISIT.2019.8849465}},
doi = {{10.1109/ISIT.2019.8849465}},
volume = {{2019-July}},
year = {{2019}},
}