Making Cell-Free Massive MIMO Competitive With MMSE Processing and Centralized Implementation

By Emil Björnson, Luca Sanguinetti. IEEE Transactions on Wireless Communications, 2019

923 citations recorded by the source corpus.

Cell-free Massive MIMO is considered as a promising technology for satisfying the increasing number of users and high rate expectations in beyond-5G networks. The key idea is to let many distributed access points (APs) communicate with all users in the network, possibly by using joint coherent signal processing. The aim of this paper is to provide the first comprehensive analysis of this technology under different degrees of cooperation among the APs. Particularly, the uplink spectral efficiencies of four different cell-free implementations are analyzed, with spatially correlated fading and arbitrary linear processing. It turns out that it is possible to outperform conventional Cellular Massive MIMO and small cell networks by a wide margin, but only using global or local minimum mean-square error (MMSE) combining. This is in sharp contrast to the existing literature, which advocates for maximum-ratio combining. Also, we show that a centralized implementation with optimal MMSE processing not only maximizes the SE but largely reduces the fronthaul signaling compared to the standard distributed approach. This makes it the preferred way to operate Cell-free Massive MIMO networks. Non-linear decoding is also investigated and shown to bring negligible improvements.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/b6a7677b7457f46a8db6da4c83d0946b6eff1675

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Citations in the corpus

Cell-Free Massive MIMO: A New Next-Generation Paradigm (2019, background): “In this context, four different levels of cooperation was introduced in [36] for UL signal detection.”
Foundations of User-Centric Cell-Free Massive MIMO (2020, methodology): “One option is to provide the CPU with statistical CSI so that it can optimize how the uplink data estimates from the APs are combined by taking their relative accuracy into account [4], [28], [122], [130].”
User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions (2021, background): “and the DUs can be assumed quasi-synchronized within a 1 km or 5 km radius for the LTE normal and extended cyclic prefix respectively [3].”
Ubiquitous cell-free Massive MIMO communications (2018, positive): “The UL spectral efficiency of cell-free Massive MIMO under four different levels of receiver cooperation are evaluated in [23].”
Massive MIMO is a Reality - What is Next? Five Promising Research Directions for Antenna Arrays (2019, methodology): “nce since it coherently combines signals from many antennas to achieve the aforementioned divide-and-conquer gains. This has, for example, been demonstrated numerically for cell-free networks in [40]–[42]. To achieve these gains, the antennas in the ELAA need to be phase-synchronized, which is more ”
Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination (2019, background): “However, the general theory behind Massive MIMO is not limited to that case, but has recently been applied also to cellfree networks [74]–[76].”
Prospective Multiple Antenna Technologies for Beyond 5G (2019, methodology): “The highest spectral efﬁciency is achieved by cell-free massive MIMO when using L-MMSE combining The uplink spectral efﬁciency with different combining methods and power control schemes, using the simulation setup from [37]. and the optimal weights from [46].”