Ubiquitous cell-free Massive MIMO communications
By Giovanni Interdonato, Emil Björnson, Hien Quoc Ngo, Pål K. Frenger, Erik G. Larsson. EURASIP Journal on Wireless Communications and Networking, 2018
632 citations recorded by the source corpus.
Since the first cellular networks were trialled in the 1970s, we have witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic growth has been managed by a combination of wider bandwidths, refined radio interfaces, and network densification, namely increasing the number of antennas per site. Due its cost-efficiency, the latter has contributed the most. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatially multiplexing of users and hence increases the spectral and energy efficiency (see references herein). It constitutes a centralized solution to densify a network, and its performance is limited by the inter-cell interference inherent in its cell-centric design. Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive MIMO system implementing coherent user-centric transmission to overcome the inter-cell interference limitation in cellular networks and provide additional macro-diversity. These features, combined with the system scalability inherent in the Massive MIMO design, distinguish ubiquitous cell-free Massive MIMO from prior coordinated distributed wireless systems. In this article, we investigate the enormous potential of this promising technology while addressing practical deployment issues to deal with the increased back/front-hauling overhead deriving from the signal co-processing.
Subfields: Biomedical Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/aeafc815d581c826b2e7173c6856d51b8df15579
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Luca Sanguinetti
- Hadi Sarieddeen
- Emil Björnson
- Jakob Hoydis
- Sundeep Rangan
- Marco Mezzavilla
- Shree Krishna Sharma
- Anum Ali
In Electrical and Electronic Engineering
- Emil Björnson
- Luca Sanguinetti
- Rui Zhang
- Robert W. Heath
- Jakob Hoydis
- Qingqing Wu
- Erik G. Larsson
- M. Di Renzo
Citations in the corpus
- Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination (2019, methodology): “Although the achievable SE follows from the Massive MIMO methodology, the post-cellular perspective opens a Pandora’s box of new issues [82]: how to implement initial access, soft handover, resource allocation, adaptive modulation and coding, MMSE-like interference suppression, or synchronization in”
- Non-Stationarities in Extra-Large-Scale Massive MIMO (2019, background): “Another possible implementation of very large arrays is through radio stripes as described in [5] that can be easily attached to existing construction structures and are connected to a central unit to form a distributed cell-free system.”
- Foundations of User-Centric Cell-Free Massive MIMO (2020, background): “A cell-free network is an attempt to move beyond those limits [49], [83], [126], [208], [210].”
- What Will the Future of UAV Cellular Communications Be? A Flight From 5G to 6G (2021, background): “somewhat distributed implementations [143] while the latter, a decided shift towards the C-RAN paradigm, is where the full cell-free potential is unleashed [144]–[146].”
- A Comprehensive Survey on Millimeter Wave Communications for Fifth-Generation Wireless Networks: Feasibility and Challenges (2020, background): “…networks are suboptimal as higher spectral efficiency (bit/s/Hz/UE) can be realized by employing multiple access points per signal co-processing [312], [313], [316]. correlation [316], and therefore, proper user grouping and user scheduling algorithms are required to reduce UEs’ spatial correlation.”
- Prospective Multiple Antenna Technologies for Beyond 5G (2019, background): “Wired provision via optical fiber is cost-prohibitive except in premium venues or if serial connections can be used [34].”
- Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019, background): “The user-centric transmission not only overcomes the inter-cell interference encountered in the conventional cellular networks but also provides macro-scale diversity [219].”
- A Joint Precoding Framework for Wideband Reconfigurable Intelligent Surface-Aided Cell-Free Network (2020, methodology): “In the proposed RIS-aided cell-free network, all BSs are synchronized, which is necessary to serve all users by coherent joint transmission [8].”
- Making Cell-Free Massive MIMO Competitive With MMSE Processing and Centralized Implementation (2019, methodology): “This type of serial fronthaul is needed for Level 2 and Level 3 to make practical sense, which is why it is adopted by the radio stripes concept described in [42].”
- Channel Hardening and Favorable Propagation in Cell-Free Massive MIMO With Stochastic Geometry (2017, background): “These are important open issues that need to be treated in future work [15], but we first need to understand to what extent we can rely on channel hardening and favorable propagation to simplify these functionalities.”
- Massive MIMO is a Reality - What is Next? Five Promising Research Directions for Antenna Arrays (2019, methodology): “A synchronization algorithm based on over-the-air signaling is described in [55], indicating that this might be a solvable problem.”
- White Paper on Broadband Connectivity in 6G (2020, methodology): “Although there are concepts (e.g., radio stripes where the antennas are integrated into cables [41]) to achieve practically convenient deployment, the technology is mainly of interest for crowded areas with a huge traffic demand or robustness requirements.”
- The Road to 6G: Ten Physical Layer Challenges for Communications Engineers (2020, background): “Some heuristic power control schemes have been proposed, which, however, are developed based on a specific assumption of the propagation environment, and hence, it is hard to evaluate how well these schemes work in practice [9].”