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Decentralized Massive MIMO Systems : Is There Anything to be Discussed?

Sanchez, Jesus Rodriguez LU ; Vidal Alegria, Juan LU and Rusek, Fredrik LU (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).

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Please use this url to cite or link to this publication:
author
organization
publishing date
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
Institute of Electrical and Electronics Engineers Inc.
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
2019-10-29 05:57:58
@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},
  language     = {eng},
  pages        = {787--791},
  publisher    = {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},
}