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Signal Processing Aspects of Cell-Free Massive MIMO
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6078-835X
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The fifth generation of mobile communication systems (5G) promises unprecedented levels of connectivity and quality of service (QoS) to satisfy the incessant growth in the number of mobile smart devices and the huge increase in data demand. One of the primary ways 5G network technology will be accomplished is through network densification, namely increasing the number of antennas per site and deploying smaller and smaller cells.

Massive MIMO, where MIMO stands for multiple-input multiple-output, is widely expected to be a key enabler of 5G. This technology leverages an aggressive spatial multiplexing, from using a large number of transmitting/receiving antennas, to multiply the capacity of a wireless channel. A massive MIMO base station (BS) is equipped with a large number of antennas, much larger than the number of active users. The users are coherently served by all the antennas, in the same time-frequency resources but separated in the spatial domain by receiving very directive signals. By supporting such a highly spatially-focused transmission (precoding), massive MIMO provides higher spectral and energy efficiency, and reduces the inter-cell interference compared to existing mobile systems. The inter-cell interference is however becoming the major bottleneck as we densify the networks. It cannot be removed as long as we rely on a network-centric implementation, since the inter-cell interference concept is inherent to the cellular paradigm.

Cell-free massive MIMO refers to a massive MIMO system where the BS antennas, herein referred to as access points (APs), are geographically spread out. The APs are connected, through a fronthaul network, to a central processing unit (CPU) which is responsible for coordinating the coherent joint transmission. Such a distributed architecture provides additional macro-diversity, and the co-processing at multiple APs entirely suppresses the inter-cell interference. Each user is surrounded by serving APs and experiences no cell boundaries. This user-centric approach, combined with the system scalability that characterizes the massive MIMO design, constitutes a paradigm shift compared to the conventional centralized and distributed wireless communication systems. On the other hand, such a distributed system requires higher capacity of back/front-haul connections, and the signal co-processing increases the signaling overhead.

In this thesis, we focus on some signal processing aspects of cell-free massive MIMO. More specifically, we firstly investigate if the downlink channel estimation, via downlink pilots, brings gains to cell-free massive MIMO or the statistical channel state information (CSI) knowledge at the users is enough to reliably perform data decoding, as in conventional co-located massive MIMO. Allocating downlink pilots is costly resource-wise, thus we also propose resource saving-oriented strategies for downlink pilot assignment. Secondly, we study further fully distributed and scalable precoding schemes in order to outperform cell-free massive MIMO in its canonical form, which consists in single-antenna APs implementing conjugate beamforming (also known as maximum ratio transmission).

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. , p. 35
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1817
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-151026DOI: 10.3384/lic.diva-151026ISBN: 9789176852248 (print)OAI: oai:DiVA.org:liu-151026DiVA, id: diva2:1248585
Presentation
2018-09-21, Systemet, B-huset, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2018-09-17 Created: 2018-09-17 Last updated: 2019-10-29Bibliographically approved
List of papers
1. Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise
Open this publication in new window or tab >>Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise
2019 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 18, no 11, p. 5153-5169Article in journal (Refereed) Published
Abstract [en]

Cell-free Massive MIMO (multiple-input multipleoutput) refers to a distributed Massive MIMO system where all the access points (APs) cooperate to coherently serve all the user equipments (UEs), suppress inter-cell interference and mitigate the multiuser interference. Recent works 1, 2 demonstrated that, unlike co-located Massive MIMO, the channel hardening is, in general, less pronounced in cell-free Massive MIMO, thus there is much to benefit from estimating the downlink channel. In this study, we investigate the gain introduced by the downlink beamforming training, extending the analysis in 1 to non-orthogonal uplink and downlink pilots. Assuming singleantenna APs, conjugate beamforming and independent Rayleigh fading channel, we derive a closed-form expression for the peruser achievable downlink rate that addresses channel estimation errors and pilot contamination both at the AP and UE side. The performance evaluation includes max-min fairness power control, greedy pilot assignment methods, and a comparison between achievable rates obtained from different capacitybounding techniques. Numerical results show that downlink beamforming training, although increases pilot overhead and introduces additional pilot contamination, improves significantly the achievable downlink rate. Even for large number of APs, it is not fully efficient for the UE relying on the statistical channel state information for data decoding.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
Cell-Free Massive MIMO;downlink training;conjugate beamforming;max-min fairness power control;capacity lower bound;achievable downlink rate;channel hardening.
National Category
Telecommunications Signal Processing Communication Systems Computer Engineering
Identifiers
urn:nbn:se:liu:diva-161332 (URN)10.1109/TWC.2019.2933831 (DOI)000496947800010 ()
Note

Funding agencies: European UnionEuropean Union (EU) [641985]; Swedish Research Council (VR)Swedish Research Council; U.K. Research and Innovation Future Leaders Fellowships [MR/S017666/1]

Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2019-12-18Bibliographically approved
2. Utility-based Downlink Pilot Assignment in Cell-Free Massive MIMO
Open this publication in new window or tab >>Utility-based Downlink Pilot Assignment in Cell-Free Massive MIMO
2018 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

We propose a strategy for orthogonal downlink pilot assignment in cell-free massive MIMO (multiple-input multiple-output) that exploits knowledge of the channel state information, the channel hardening degree at each user, and the mobility conditions for the users. These elements, properly combined together, are used to define a user pilot utility metric, which measures the user's real need of a downlink pilot for efficient data decoding. The proposed strategy consists in assigning orthogonal downlink pilots only to the users having a pilot utility metric exceeding a predetermined threshold. Instead, users that are not assigned with an orthogonal downlink pilot decode the data by using the statistical channel state information. The utility-based approach guarantees higher downlink net sum throughput, better support both for high-speed users and shorter coherent intervals than prior art approaches.

National Category
Communication Systems Telecommunications Signal Processing
Identifiers
urn:nbn:se:liu:diva-146247 (URN)
Conference
The 22nd International ITG Workshop on Smart Antennas (WSA 2018), March 14-16, Bochum, Germany
Available from: 2018-04-04 Created: 2018-04-04 Last updated: 2018-09-17
3. On the Performance of Cell-Free Massive MIMO with Short-Term Power Constraints
Open this publication in new window or tab >>On the Performance of Cell-Free Massive MIMO with Short-Term Power Constraints
2016 (English)In: 2016 IEEE 21ST INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELLING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS (CAMAD), IEEE , 2016, p. 225-230Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we consider a time-division duplex cell-free massive multiple-input multiple-output (MIMO) system where many distributed access points (APs) simultaneously serve many users. A normalized conjugate beamforming scheme, which satisfies short-term average power constraints at the APs, is proposed and analyzed taking into account the effect of imperfect channel information. We derive an approximate closed-form expression for the per-user achievable downlink rate of this scheme. We also provide, analytically and numerically, a performance comparison between the normalized conjugate beamforming and the conventional conjugate beamforming scheme in [1] (which satisfies long-term average power constraints). Normalized conjugate beamforming scheme reduces the beamforming uncertainty gain, which comes from the users lack of the channel state information knowledge, and hence, it improves the achievable downlink rate compared to the conventional conjugate beamforming scheme.

Place, publisher, year, edition, pages
IEEE, 2016
National Category
Telecommunications
Identifiers
urn:nbn:se:liu:diva-134522 (URN)10.1109/CAMAD.2016.7790362 (DOI)000391562900042 ()978-1-5090-2558-9 (ISBN)
Conference
21st IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD)
Available from: 2017-02-15 Created: 2017-02-15 Last updated: 2019-03-20
4. Downlink Spectral Efficiency of Cell-Free Massive MIMO with Full-Pilot Zero-Forcing
Open this publication in new window or tab >>Downlink Spectral Efficiency of Cell-Free Massive MIMO with Full-Pilot Zero-Forcing
2018 (English)In: 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2018, p. 1003-1007Conference paper, Published paper (Refereed)
Abstract [en]

Cell-free Massive multiple-input multiple-output (MIMO) ensures ubiquitous communication at high spectral efficiency (SE) thanks to increased macro-diversity as compared cellular communications. However, system scalability and performance are limited by fronthauling traffic and interference. Unlike conventional precoding schemes that only suppress intra-cell interference, full-pilot zero-forcing (fpZF), introduced in [1], actively suppresses also inter-cell interference, without sharing channel state information (CSI) among the access points (APs). In this study, we derive a new closed-form expression for the downlink (DL) SE of a cell-free Massive MIMO system with multi-antenna APs and fpZF precoding, under imperfect CSI and pilot contamination. The analysis also includes max-min fairness DL power optimization. Numerical results show that fpZF significantly outperforms maximum ratio transmission scheme, without increasing the fronthauling overhead, as long as the system is sufficiently distributed.

Keywords
MIMO communication, Interference, Precoding, Channel estimation, Fading channels, Downlink, Signal to noise ratio, Cell-free Massive MIMO, full-pilot zero-forcing, downlink spectral efficiency, max-min fairness power control
National Category
Telecommunications
Identifiers
urn:nbn:se:liu:diva-154885 (URN)10.1109/GlobalSIP.2018.8646666 (DOI)000462968100205 ()978-1-7281-1295-4 (ISBN)978-1-7281-1294-7 (ISBN)978-1-7281-1296-1 (ISBN)
Conference
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Anaheim, CA, USA
Note

Funding agencies: European Union [641985]

Available from: 2019-03-04 Created: 2019-03-04 Last updated: 2019-06-28

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