403 Downloads (Pure)


Cellular communication is constantly evolving; currently 5G systems are being deployed and research towards 6G is ongoing. Three use cases have been discussed as enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low-latency communication (URLLC). To fulfill the requirements of these use cases, new technologies are needed and one enabler is massive multiple-input multiple-output (MIMO). By increasing the number of antennas at the base station side, data rates can be increased, more users can be served simultaneously, and there is a potential to improve reliability. In addition, it is possible to achieve better coverage, improved energy efficiency, and low-complex user devices. The performance of any wireless system is limited by the underlying channels. Massive MIMO channels have shown several beneficial properties: the array gain stemming from the combining of the signals from the many antennas, improved user separation due to favourable propagation -- where the user channels become pair-wise orthogonal -- and the channel hardening effect, where the variations of channel gain decreases as the number of antennas increases. Previous theoretical works have commonly assumed independent and identically distributed (i.i.d.) complex Gaussian channels. However, in the first studies on massive MIMO channels, it was shown that common outdoor and indoor environments are not that rich in scattering, but that the channels are rather spatially correlated. To enable the above use cases, investigations are needed for the targeted environments. This thesis focuses on the benefits of deploying massive MIMO systems to achieve dependable communication in a number of scenarios related to the use cases. The first main area is the study of an industrial environment and aims at characterizing and modeling massive MIMO channels to assess the possibility of achieving the requirements of URLLC in a factory context. For example, a unique fully distributed array is deployed with the aim to further exploit spatial diversity. The other main area concerns massive MIMO at sub-GHz, a previously unexplored area. The channel characteristics when deploying a physically very large array for IoT networks are explored. To conclude, massive MIMO can indeed bring great advantages when trying to achieve dependable communication. Although channels in regular indoor environments are not i.i.d. complex Gaussian, the model can be justified in rich scattering industrial environments. Due to massive MIMO, the small-scale fading effects are reduced and when deploying a distributed array also the large-scale fading effects are reduced. In the Internet-of-Things (IoT) scenario, the channel is not as rich scattering. In this use case one can benefit from the array gain to extend coverage and improved energy efficiency, and diversity is gained due to the physically large array.
Translated title of the contributionMassive MIMO för tillförlitlig kommunikation
Original languageEnglish
Awarding Institution
  • Faculty of Engineering, LTH
  • Catholic University of Leuven
  • Tufvesson, Fredrik, Supervisor
  • van Der Perre, Liesbet, Supervisor
Thesis sponsors
Award date2022 Dec 9
Place of PublicationLund
ISBN (Print)978-91-8039-459-8
ISBN (electronic) 978-91-8039-460-4
Publication statusPublished - 2022 Nov 14

Bibliographical note

Defence details
Date: 2022-12-09
Time: 09:15
Place: Lecture Hall E:1406, building E, Ole Römers väg 3, Faculty of Engineering LTH, Lund University, Lund. The dissertation is to be live streamed, but part of the premises will be excluded from the live stream.
External reviewer(s)
Name: Linnartz, Jean-Paul
Title: Prof.
Affiliation: Signify and Eindhoven University of Technology, The Netherlands.

Subject classification (UKÄ)

  • Communication Systems

Free keywords

  • Channel characterisation
  • Channel measurements
  • Channel modeling
  • Industrial automation
  • Industry 4.0
  • Internet-of-Things
  • Massive MIMO
  • mMTC
  • Reliability


Dive into the research topics of 'Massive MIMO for Dependable Communication'. Together they form a unique fingerprint.

Cite this