Performance Analysis of Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach
Anastasios Papazafeiropoulos, Pandelis Kourtessis, Marco Di Renzo,, Symeon Chatzinotas, and John M. Senior

TL;DR
This paper uses stochastic geometry to analyze the performance of cell-free massive MIMO systems, deriving coverage probability and achievable rate, and compares their performance to small-cell networks.
Contribution
It provides the first analysis of coverage probability for CF massive MIMO using a Poisson point process model, highlighting performance advantages over small-cell networks.
Findings
CF massive MIMO achieves higher coverage and rate than small cells.
Increasing AP density improves coverage up to a saturation point.
Higher path-loss exponent reduces achievable rate.
Abstract
Cell-free (CF) massive multiple-input-multiple-output (MIMO) has emerged as an alternative deployment for conventional cellular massive MIMO networks. Prior works relied on the strong assumption (quite idealized) that the APs are uniformly distributed, and actually, this randomness was considered during the simulation and not in the analysis. However, in practice, ongoing and future networks become denser and increasingly irregular. Having this in mind, we consider that the AP locations are modeled by means of a Poisson point process (PPP) which is a more realistic model for the spatial randomness than a grid or uniform deployment. In particular, by virtue of stochastic geometry tools, we derive both the downlink coverage probability and achievable rate. Notably, this is the only work providing the coverage probability and shedding light on this aspect of CF massive MIMO systems.…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Millimeter-Wave Propagation and Modeling · Advanced Wireless Communication Technologies
