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An Algorithm for Grant-Free Random Access in Cell-Free Massive MIMO
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-9504-3975
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5954-434x
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
2020 (English)In: 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE, 2020, p. 1-5Conference paper, Published paper (Refereed)
Abstract [en]

Massive access is one of the main use cases of beyond 5G (B5G) wireless networks and massive MIMO is a key technology for supporting it. Prior works studied massive access in the co-located massive MIMO framework. In this paper, we investigate the activity detection in grant-free random access for massive machine type communications (mMTC) in cell-free massive MIMO network. Each active device transmits a pre-assigned non-orthogonal pilot sequence to the APs and the APs send the received signals to a central processing unit (CPU) for joint activity detection. We formulate the maximum likelihood device activity detection problem and provide an algorithm based on coordinate descent method having affordable complexity. We show that the cell-free massive MIMO network can support low-powered mMTC devices and provide a broad coverage.

Place, publisher, year, edition, pages
IEEE, 2020. p. 1-5
Series
nternational Workshop on Signal Processing Advances in Wireless Communications (SPAWC), ISSN 1948-3244, E-ISSN 1948-3252
Keywords [en]
5G mobile communication, maximum likelihood detection, MIMO communication, co-located massive MIMO framework, non-orthogonal pilot sequence, low-powered mMTC device, coordinate descent method, maximum likelihood device activity detection problem, joint activity detection, cell-free massive MIMO network, massive machine type communications, 5G wireless networks, grant-free random access, Fading channels, Complexity theory, Base stations, Signal processing algorithms, Approximation algorithms, Activity Detection, Cell-Free massive MIMO, massive machine-type communications (mMTC), Internet-of-Things (IoT)
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-170111DOI: 10.1109/SPAWC48557.2020.9154288ISI: 000620337500085ISBN: 9781728154787 (electronic)ISBN: 9781728154794 (print)OAI: oai:DiVA.org:liu-170111DiVA, id: diva2:1471671
Conference
2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), MAY 26-29, 2020
Note

This work is supported in part by ELLIIT and in part by Swedish Research Council (VR).

Available from: 2020-09-29 Created: 2020-09-29 Last updated: 2021-12-29Bibliographically approved

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Björnson, EmilLarsson, Erik G.

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Ganesan, Unnikrishnan KunnathBjörnson, EmilLarsson, Erik G.
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