Clustering-Based Activity Detection Algorithms for Grant-Free Random Access in Cell-Free Massive MIMO
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
2021-12-062021-12-062022-06-25Bibliographically approved