kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Clustering-Based Activity Detection Algorithms for Grant-Free Random Access in Cell-Free Massive MIMO
Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS. Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden.ORCID iD: 0000-0002-5954-434x
Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..
2021 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 69, no 11, p. 7520-7530Article in journal (Refereed) Published
Abstract [en]

Future wireless networks need to support massive machine type communication (mMTC) where a massive number of devices accesses the network and massive MIMO is a promising enabling technology. Massive access schemes have been studied for co-located massive MIMO arrays. In this paper, we investigate the activity detection in grant-free random access for mMTC in cell-free massive MIMO networks using distributed arrays. Each active device transmits a non-orthogonal pilot sequence to the access points (APs) and the APs send the received signals to a central processing unit (CPU) for joint activity detection. The maximum likelihood device activity detection problem is formulated and algorithms for activity detection in cell-free massive MIMO are provided to solve it. The simulation results show that the macro diversity gain provided by the cell-free architecture improves the activity detection performance compared to co-located architecture when the coverage area is large.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. Vol. 69, no 11, p. 7520-7530
Keywords [en]
Massive MIMO, Signal processing algorithms, Wireless networks, Performance evaluation, Computer architecture, Central Processing Unit, Partial transmit sequences, Activity detection, grant-free random access, cell-free massive MIMO, massive machine-type communications (mMTC), Internet-of-Things (IoT)
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-305660DOI: 10.1109/TCOMM.2021.3102635ISI: 000719563500032Scopus ID: 2-s2.0-85112198086OAI: oai:DiVA.org:kth-305660DiVA, id: diva2:1617072
Note

QC 20211206

Available from: 2021-12-06 Created: 2021-12-06 Last updated: 2022-06-25Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Björnson, Emil

Search in DiVA

By author/editor
Björnson, Emil
By organisation
Communication Systems, CoS
In the same journal
IEEE Transactions on Communications
Communication Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 20 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf