Enabling Ultrareliable and Low-Latency Communications under Shadow Fading by Massive MU-MIMO

Zeng, J; Lv, T; Liu, RP; Su, X; Guo, YJ; Beaulieu, NC

Enabling Ultrareliable and Low-Latency Communications under Shadow Fading by Massive MU-MIMO

Zeng, J Lv, T Liu, RP Su, X Guo, YJ Beaulieu, NC

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Internet of Things Journal, 2020, 7, (1), pp. 234-246
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Zeng, J
dc.contributor.author	Lv, T
dc.contributor.author	Liu, RP
dc.contributor.author	Su, X
dc.contributor.author	Guo, YJ
dc.contributor.author	Beaulieu, NC
dc.date.accessioned	2020-12-28T00:52:30Z
dc.date.available	2020-12-28T00:52:30Z
dc.date.issued	2020-01-01
dc.identifier.citation	IEEE Internet of Things Journal, 2020, 7, (1), pp. 234-246
dc.identifier.issn	2327-4662
dc.identifier.issn	2327-4662
dc.identifier.uri	http://hdl.handle.net/10453/144968
dc.description.abstract	© 2014 IEEE. It is challenging to satisfy the critical requirements of ultrareliable and low-latency communications (URLLCs) in the Internet of Things (IoT) under severe channel fading. The emerging massive multiuser multiple-input-multiple-output (MU-MIMO) concept is applied in IoT networks under shadow fading, enabling URLLC with pilot-assisted channel estimation (PACE) and zero-forcing (ZF) detection. Assuming users are uniformly and randomly deployed under log-normal shadow fading, the probability density function (pdf) of postprocessing signal-to-noise ratios (SNRs) is derived for the uplink (UL) of massive MU-MIMO with perfect channel state information (CSI) and imperfect CSI obtained by PACE. Then, finite blocklength (FBL) information theory is utilized to derive the error probability of accessing users with a given latency, thereby evaluating the reliability of massive MU-MIMO for short-packet transmissions. Further, the length of pilots to minimize the error probability can be decided by the golden section search method (GSSM), which can converge rapidly. Numerical results verify that massive MU-MIMO can support a large number of UL URLLC users even when users are randomly deployed under shadow fading.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation	iMOVE Australia Limited
dc.relation.ispartof	IEEE Internet of Things Journal
dc.relation.isbasedon	10.1109/JIOT.2019.2945106
dc.rights	info:eu-repo/semantics/closedAccess
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.subject	0805 Distributed Computing, 1005 Communications Technologies
dc.title	Enabling Ultrareliable and Low-Latency Communications under Shadow Fading by Massive MU-MIMO
dc.type	Journal Article
utslib.citation.volume	7
utslib.for	0805 Distributed Computing
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-12-28T00:52:12Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	7
utslib.citation.issue	1

Abstract:

© 2014 IEEE. It is challenging to satisfy the critical requirements of ultrareliable and low-latency communications (URLLCs) in the Internet of Things (IoT) under severe channel fading. The emerging massive multiuser multiple-input-multiple-output (MU-MIMO) concept is applied in IoT networks under shadow fading, enabling URLLC with pilot-assisted channel estimation (PACE) and zero-forcing (ZF) detection. Assuming users are uniformly and randomly deployed under log-normal shadow fading, the probability density function (pdf) of postprocessing signal-to-noise ratios (SNRs) is derived for the uplink (UL) of massive MU-MIMO with perfect channel state information (CSI) and imperfect CSI obtained by PACE. Then, finite blocklength (FBL) information theory is utilized to derive the error probability of accessing users with a given latency, thereby evaluating the reliability of massive MU-MIMO for short-packet transmissions. Further, the length of pilots to minimize the error probability can be decided by the golden section search method (GSSM), which can converge rapidly. Numerical results verify that massive MU-MIMO can support a large number of UL URLLC users even when users are randomly deployed under shadow fading.

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http://hdl.handle.net/10453/144968