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  • 1.
    Interdonato, Giovanni
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Ngo, Hien Quoc
    Queen’s University Belfast, UK.
    Frenger, Pål
    Ericsson Research, Ericsson AB, Linköping, Sweden.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Downlink Training in Cell-Free Massive MIMO: A Blessing in Disguise2019In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 18, no 11, p. 5153-5169Article in journal (Refereed)
    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.

  • 2.
    Interdonato, Giovanni
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Frenger, Pål
    Ericsson Research, Ericsson AB, Linköping, Sweden.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Scalability Aspects of Cell-Free Massive MIMO2019In: 2019 IEEE International Conference on Communications (ICC), Proceedings Shanghai, China 20–24 May 2019, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Ubiquitous cell-free massive MIMO (multiple-input multiple-output) combines massive MIMO technology and user-centric transmission in a distributed architecture. All the access points (APs) in the network cooperate to jointly and coherently serve a smaller number of users in the same time-frequency resource. However, this coordination needs significant amounts of control signalling which introduces additional overhead, while data co-processing increases the back/front-haul requirements. Hence, the notion that the “whole world” could constitute one network, and that all APs would act as a single base station, is not scalable. In this study, we address some system scalability aspects of cell-free massive MIMO that have been neglected in literature until now. In particular, we propose and evaluate a solution related to data processing, network topology and power control. Results indicate that our proposed framework achieves full scalability at the cost of a modest performance loss compared to the canonical form of cell-free massive MIMO.

  • 3.
    Interdonato, Giovanni
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Quoc Ngo, Hien
    Queens Univ Belfast, North Ireland.
    Frenger, Pal
    Ericsson AB, Ericsson Res, S-58330 Linkoping, Sweden.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Ubiquitous cell-free Massive MIMO communications2019In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, article id 197Article, review/survey (Refereed)
    Abstract [en]

    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.

  • 4.
    Interdonato, Giovanni
    et al.
    Ericsson Research, Linköping, 581 12, Sweden.
    Karlsson, Marcus
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Downlink Spectral Efficiency of Cell-Free Massive MIMO with Full-Pilot Zero-Forcing2018In: 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2018, p. 1003-1007Conference 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.

  • 5.
    Interdonato, Giovanni
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Signal Processing Aspects of Cell-Free Massive MIMO2018Licentiate 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).

    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)
    Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2019-11-12Bibliographically 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
  • 6.
    Interdonato, Giovanni
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. Ericsson Research, Linköping, Sweden.
    Frenger, Pål
    Ericsson Research, Linköping, Sweden.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Utility-based Downlink Pilot Assignment in Cell-Free Massive MIMO2018Conference paper (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.

  • 7.
    Interdonato, Giovanni
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. Ericsson Research.
    Quoc Ngo, Hien
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Frenger, Pål
    Ericsson Research.
    How Much Do Downlink Pilots Improve Cell-Free Massive MIMO?2016In: 2016 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), IEEE , 2016, p. 1-7Conference paper (Refereed)
    Abstract [en]

    In this paper, we analyze the benefits of including downlink pilots in a cell-free massive MIMO system. We derive an approximate per-user achievable downlink rate for conjugate beamforming processing, which takes into account both uplink and downlink channel estimation errors, and power control. A performance comparison is carried out, in terms of per-user net throughput, considering cell-free massive MIMO operation with and without downlink training, for different network densities. We take also into account the performance improvement provided by max-min fairness power control in the downlink. Numerical results show that, exploiting downlink pilots, the performance can be considerably improved in low density networks over the conventional scheme where the users rely on statistical channel knowledge only. In high density networks, performance improvements are moderate.

  • 8.
    Interdonato, Giovanni
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. Ericsson Research.
    Ngo, Hien Quoc
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Frenger, Pål
    Ericsson Research.
    On the Performance of Cell-Free Massive MIMO with Short-Term Power Constraints2016In: 2016 IEEE 21ST INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELLING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS (CAMAD), IEEE , 2016, p. 225-230Conference 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.

1 - 8 of 8
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