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Clustering-Based Activity Detection Algorithms for Grant-Free Random Access in Cell-Free Massive MIMO

Information Theory 2021-12-01 v1 Signal Processing math.IT

Abstract

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.

Keywords

Cite

@article{arxiv.2111.15378,
  title  = {Clustering-Based Activity Detection Algorithms for Grant-Free Random Access in Cell-Free Massive MIMO},
  author = {Unnikrishnan Kunnath Ganesan and Emil Björnson and Erik G. Larsson},
  journal= {arXiv preprint arXiv:2111.15378},
  year   = {2021}
}

Comments

12 pages, 9 figures. Published in IEEE Transactions on Communications, Vol. 69, No. 11, pp. 7520 - 7530, November 2021

R2 v1 2026-06-24T07:57:42.613Z