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Achieving Distributed MIMO Performance with Repeater-Assisted Cellular Massive MIMO
Lund Univ, Sweden.
Ericsson, Japan.
Ericsson, Sweden.
Ericsson, Sweden.
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2025 (English)In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 63, no 3, p. 114-119Article in journal (Refereed) Published
Abstract [en]

In what ways could cellular massive MIMO be improved? This technology has already been shown to bring huge performance gains, however, coverage holes and difficulties to transmit multiple streams to multi-antenna users because of insufficient channel rank remain issues. Distributed MIMO, also known as cell-free massive MIMO, might be the ultimate solution. However, while being a powerful technology, it is expensive to install backhaul, and it is difficult to achieve accurate phase alignment for coherent multi-user beamforming on downlink. Another option is reflective intelligent surfaces - but they have large form factors and require a lot of training and control overhead, and probably, in practice, some form of active filtering to make them sufficiently band-selective. We propose a new approach to densification of cellular systems, envisioning repeater-assisted cellular massive MIMO, where a large number of physically small and cheap wireless repeaters are deployed. They receive and retransmit signals instantaneously, appearing as active scatterers. This means they appear as ordinary channel scatterers but with amplification. We elaborate on the requirements of such repeaters, show that the performance of these systems could potentially approach that of distributed MIMO, and outline future research directions.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2025. Vol. 63, no 3, p. 114-119
Keywords [en]
Wireless communication; Training; Filtering; Array signal processing; Massive MIMO; Performance gain; Repeaters; Downlink; Streams; Backhaul networks
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-212345DOI: 10.1109/MCOM.001.2400332ISI: 001438536600001OAI: oai:DiVA.org:liu-212345DiVA, id: diva2:1945701
Note

Funding Agencies|ELLIIT; KAW foundation; Swedish Research Council; H2020-REINDEER

Available from: 2025-03-19 Created: 2025-03-19 Last updated: 2025-04-10

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CiteExportLink to record
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Citation style
  • apa
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