Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity

Marx M.M. Freitas; Daynara D. Souza; A. L.P. Fernandes; Daniel B. Da Costa; André Mendes Cavalcante; Luca Valcarenghi; João C.Weyl Albuquerque Costa

doi:10.1109/ICC45041.2023.10279694

Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity

Marx M.M. Freitas^*, Daynara D. Souza^*, A. L.P. Fernandes^*, Daniel B. Da Costa, André Mendes Cavalcante, Luca Valcarenghi, João C.Weyl Albuquerque Costa

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

This paper investigates the performance of scalable user-centric (UC) distributed massive multiple-input multiple-output (D-mMIMO) systems, widely known in the literature as cell-free mMIMO, with limited processing capacity. Specifically, it is assumed that the computational complexity (CC) of performing channel estimation and precoding signals does not increase with the number of access points (APs). In this regard, it is considered that each user equipment (UE) can only be associated with a finite number of APs. Moreover, a method is proposed for adjusting the AP clusters according to the network implementation, i.e., centralized or distributed. We compare the proposed approaches with a scalable UC system that does not perform AP cluster adjustment and does not prevent the processing demands from growing with the number of APs. Simulation results reveal that UC systems can keep the spectral efficiency (SE) under minor degradation even if the processing capacity is limited, reducing the CC by up to 96%. Besides, the proposed method for adjusting the AP cluster leads to further reductions in CC.

Original language	English
Title of host publication	ICC 2023 - IEEE International Conference on Communications
Subtitle of host publication	Sustainable Communications for Renaissance
Editors	Michele Zorzi, Meixia Tao, Walid Saad
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4298-4304
Number of pages	7
ISBN (Electronic)	9781538674628
DOIs	https://doi.org/10.1109/ICC45041.2023.10279694
State	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Communications, ICC 2023 - Rome, Italy Duration: 28 May 2023 → 1 Jun 2023

Publication series

Name	IEEE International Conference on Communications
Volume	2023-May
ISSN (Print)	1550-3607

Conference

Conference	2023 IEEE International Conference on Communications, ICC 2023
Country/Territory	Italy
City	Rome
Period	28/05/23 → 1/06/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

AP selection
cell-free networks
computational complexity
distributed massive MIMO
user-centric approach

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering

Access to Document

10.1109/ICC45041.2023.10279694

Cite this

Freitas, M. M. M., Souza, D. D., Fernandes, A. L. P., Da Costa, D. B., Cavalcante, A. M., Valcarenghi, L., & Costa, J. C. W. A. (2023). Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity. In M. Zorzi, M. Tao, & W. Saad (Eds.), ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance (pp. 4298-4304). (IEEE International Conference on Communications; Vol. 2023-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC45041.2023.10279694

Freitas, Marx M.M. ; Souza, Daynara D. ; Fernandes, A. L.P. et al. / Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity. ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. editor / Michele Zorzi ; Meixia Tao ; Walid Saad. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 4298-4304 (IEEE International Conference on Communications).

@inproceedings{0810edbcd41148129a8acf2d71ad34e9,

title = "Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity",

abstract = "This paper investigates the performance of scalable user-centric (UC) distributed massive multiple-input multiple-output (D-mMIMO) systems, widely known in the literature as cell-free mMIMO, with limited processing capacity. Specifically, it is assumed that the computational complexity (CC) of performing channel estimation and precoding signals does not increase with the number of access points (APs). In this regard, it is considered that each user equipment (UE) can only be associated with a finite number of APs. Moreover, a method is proposed for adjusting the AP clusters according to the network implementation, i.e., centralized or distributed. We compare the proposed approaches with a scalable UC system that does not perform AP cluster adjustment and does not prevent the processing demands from growing with the number of APs. Simulation results reveal that UC systems can keep the spectral efficiency (SE) under minor degradation even if the processing capacity is limited, reducing the CC by up to 96%. Besides, the proposed method for adjusting the AP cluster leads to further reductions in CC.",

keywords = "AP selection, cell-free networks, computational complexity, distributed massive MIMO, user-centric approach",

author = "Freitas, {Marx M.M.} and Souza, {Daynara D.} and Fernandes, {A. L.P.} and {Da Costa}, {Daniel B.} and Cavalcante, {Andr{\'e} Mendes} and Luca Valcarenghi and Costa, {Jo{\~a}o C.Weyl Albuquerque}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Communications, ICC 2023 ; Conference date: 28-05-2023 Through 01-06-2023",

year = "2023",

doi = "10.1109/ICC45041.2023.10279694",

language = "English",

series = "IEEE International Conference on Communications",

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Freitas, MMM, Souza, DD, Fernandes, ALP, Da Costa, DB, Cavalcante, AM, Valcarenghi, L & Costa, JCWA 2023, Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity. in M Zorzi, M Tao & W Saad (eds), ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. IEEE International Conference on Communications, vol. 2023-May, Institute of Electrical and Electronics Engineers Inc., pp. 4298-4304, 2023 IEEE International Conference on Communications, ICC 2023, Rome, Italy, 28/05/23. https://doi.org/10.1109/ICC45041.2023.10279694

Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity. / Freitas, Marx M.M.; Souza, Daynara D.; Fernandes, A. L.P. et al.
ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. ed. / Michele Zorzi; Meixia Tao; Walid Saad. Institute of Electrical and Electronics Engineers Inc., 2023. p. 4298-4304 (IEEE International Conference on Communications; Vol. 2023-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity

AU - Freitas, Marx M.M.

AU - Souza, Daynara D.

AU - Fernandes, A. L.P.

AU - Da Costa, Daniel B.

AU - Cavalcante, André Mendes

AU - Valcarenghi, Luca

AU - Costa, João C.Weyl Albuquerque

PY - 2023

Y1 - 2023

N2 - This paper investigates the performance of scalable user-centric (UC) distributed massive multiple-input multiple-output (D-mMIMO) systems, widely known in the literature as cell-free mMIMO, with limited processing capacity. Specifically, it is assumed that the computational complexity (CC) of performing channel estimation and precoding signals does not increase with the number of access points (APs). In this regard, it is considered that each user equipment (UE) can only be associated with a finite number of APs. Moreover, a method is proposed for adjusting the AP clusters according to the network implementation, i.e., centralized or distributed. We compare the proposed approaches with a scalable UC system that does not perform AP cluster adjustment and does not prevent the processing demands from growing with the number of APs. Simulation results reveal that UC systems can keep the spectral efficiency (SE) under minor degradation even if the processing capacity is limited, reducing the CC by up to 96%. Besides, the proposed method for adjusting the AP cluster leads to further reductions in CC.

AB - This paper investigates the performance of scalable user-centric (UC) distributed massive multiple-input multiple-output (D-mMIMO) systems, widely known in the literature as cell-free mMIMO, with limited processing capacity. Specifically, it is assumed that the computational complexity (CC) of performing channel estimation and precoding signals does not increase with the number of access points (APs). In this regard, it is considered that each user equipment (UE) can only be associated with a finite number of APs. Moreover, a method is proposed for adjusting the AP clusters according to the network implementation, i.e., centralized or distributed. We compare the proposed approaches with a scalable UC system that does not perform AP cluster adjustment and does not prevent the processing demands from growing with the number of APs. Simulation results reveal that UC systems can keep the spectral efficiency (SE) under minor degradation even if the processing capacity is limited, reducing the CC by up to 96%. Besides, the proposed method for adjusting the AP cluster leads to further reductions in CC.

KW - AP selection

KW - cell-free networks

KW - computational complexity

KW - distributed massive MIMO

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M3 - Conference contribution

AN - SCOPUS:85178301795

T3 - IEEE International Conference on Communications

SP - 4298

EP - 4304

BT - ICC 2023 - IEEE International Conference on Communications

A2 - Zorzi, Michele

A2 - Tao, Meixia

A2 - Saad, Walid

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Communications, ICC 2023

Y2 - 28 May 2023 through 1 June 2023

ER -

Freitas MMM, Souza DD, Fernandes ALP, Da Costa DB, Cavalcante AM, Valcarenghi L et al. Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity. In Zorzi M, Tao M, Saad W, editors, ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. Institute of Electrical and Electronics Engineers Inc. 2023. p. 4298-4304. (IEEE International Conference on Communications). doi: 10.1109/ICC45041.2023.10279694

Scalable User-Centric Distributed Massive MIMO Systems with Limited Processing Capacity

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this