Foundations of User-Centric Cell-Free Massive MIMO
TL;DR: In this article, the fundamental tradeoffs between communication performance, computational complexity, and fronthaul signaling requirements are thoroughly analyzed, while open problems related to these and other resource allocation problems are reviewed.
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Abstract: Imagine a coverage area where each mobile device is communicating with a preferred set of wireless access points (among many) that are selected based on its needs and cooperate to jointly serve it, instead of creating autonomous cells. This effectively leads to a user-centric post-cellular network architecture, which can resolve many of the interference issues and service-quality variations that appear in cellular networks. This concept is called User-centric Cell-free Massive MIMO (multiple-input multiple-output) and has its roots in the intersection between three technology components: Massive MIMO, coordinated multipoint processing, and ultra-dense networks. The main challenge is to achieve the benefits of cell-free operation in a practically feasible way, with computational complexity and fronthaul requirements that are scalable to enable massively large networks with many mobile devices. This monograph covers the foundations of User-centric Cell-free Massive MIMO, starting from the motivation and mathematical definition. It continues by describing the state-of-the-art signal processing algorithms for channel estimation, uplink data reception, and downlink data transmission with either centralized or distributed implementation. The achievable spectral efficiency is mathematically derived and evaluated numerically using a running example that exposes the impact of various system parameters and algorithmic choices. The fundamental tradeoffs between communication performance, computational complexity, and fronthaul signaling requirements are thoroughly analyzed. Finally, the basic algorithms for pilot assignment, dynamic cooperation cluster formation, and power optimization are provided, while open problems related to these and other resource allocation problems are reviewed. All the numerical examples can be reproduced using the accompanying Matlab code.
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Citations
Unlocking the Potential of Local CSI in Cell-Free Networks with Channel Aging and Fronthaul Delays
Lorenzo Miretti,Sławomir Stańczak +1 more
- 09 Jun 2024
Cell-Free Massive MIMO
Giovanni Interdonato,Stefano Buzzi +1 more
TL;DR: Cell-free massive MIMO is a distributed MIMO system that combines network ultra-densification and joint coherent signal processing to provide unprecedented practical gains.
Spectral Efficiency of Cell-Free Massive MIMO with Superimposed Pilots Over Spatially Correlated Rician Fading Channels
Jinjin Zhu,Mingfeng Xie +1 more
- 20 Oct 2023
TL;DR: Spectral efficiency of cell-free massive MIMO with superimposed pilots over spatially correlated Rician fading channels is investigated. Superimposed pilots significantly reduce pilot contamination and enhance spectral efficiency compared to regular pilots.
Joint data power control and LSFD design in distributed cell-free massive MIMO under non-ideal UE hardware
Ning Li,Pingzhi Fan +1 more
TL;DR: Numerical results indicate that the recommended joint data power control and LSFD design algorithm provides higher SE for the weakest UE, thus significantly enhancing the total SE of the network.
Large-scale Fading Decoding aided User-centric Cell-free Massive MIMO: Uplink Error Probability Analysis and Detector Design
Yu Zhang,Yuxiang Peng,Xiaohu Tang,Lixia Xiao,Tao Jiang +4 more
TL;DR: This paper analyzes the uplink error probability of user-centric cell-free massive MIMO systems, deriving an SER upper bound and designing low-complexity detectors that balance error probability and fusion complexity, outperforming existing detectors in scenarios with pilot contamination.
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