Cell-Free Massive MIMO for URLLC: A Finite-Blocklength Analysis
Journal article, 2023

We present a general framework for the characterization of the packet error probability achievable in cell-free Massive multiple-input multiple output (MIMO) architectures deployed to support ultra-reliable low-latency (URLLC) traffic. The framework is general and encompasses both centralized and distributed cell-free architectures, arbitrary fading channels and channel estimation algorithms at both network and user-equipment (UE) sides, as well as arbitrary combing and precoding schemes. The framework is used to perform numerical experiments on specific scenarios, which illustrate the superiority of cell-free architectures compared to cellular architectures in supporting URLLC traffic in uplink and downlink. Also, these numerical experiments provide the following insights into the design of cell-free architectures for URLLC: i) minimum mean square error (MMSE) spatial processing must be used to achieve the URLLC targets; ii) for a given total number of antennas per coverage area, centralized cell-free solutions involving single-antenna access points (APs) offer the best performance in the uplink, thereby highlighting the importance of reducing the average distance between APs and UEs in the URLLC regime; iii) this observation applies also to the downlink, provided that the APs transmit precoded pilots to allow the UEs to estimate accurately the precoded channel.

centralized and decentralized operation

Cell-free Massive MIMO

uplink and downlink

finite-blocklength regime

ultra-reliable low-latency communications

Author

Alejandro Lancho Serrano

Massachusetts Institute of Technology (MIT)

Giuseppe Durisi

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Luca Sanguinetti

University of Pisa

IEEE Transactions on Wireless Communications

15361276 (ISSN) 15582248 (eISSN)

Vol. 22 12 8723-8735

Subject Categories

Telecommunications

Communication Systems

Signal Processing

DOI

10.1109/TWC.2023.3265303

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3/7/2024 9