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Björnson, Emil
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Publications (10 of 56) Show all publications
Van Chien, T., Björnson, E., Larsson, E. G. & Le, T. A. (2018). Distributed Power Control in Downlink Cellular Massive MIMO Systems. In: WSA 2018: 22nd International ITG Workshop on Smart Antennas. Paper presented at IEEE 22nd International ITG Workshop on Smart Antennas (WSA2018) (pp. 1-7). VDE Verlag GmbH
Open this publication in new window or tab >>Distributed Power Control in Downlink Cellular Massive MIMO Systems
2018 (English)In: WSA 2018: 22nd International ITG Workshop on Smart Antennas, VDE Verlag GmbH, 2018, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

This paper compares centralized and distributed methods to solve the power minimization problem with quality-of-service (QoS) constraints in the downlink (DL) of multi-cell Massive multiple-input multiple-output (MIMO) systems. In particular, we study the computational complexity, number of parameters that need to be exchanged between base stations (BSs), and the convergence of iterative implementations. Although a distributed implementation based on dual decomposition (which only requires statistical channel knowledge at each BS) typically converges to the global optimum after a few iterations, many parameters need to be exchanged to reach convergence.

Place, publisher, year, edition, pages
VDE Verlag GmbH, 2018
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-148936 (URN)978-3-8007-4541-8 (ISBN)
Conference
IEEE 22nd International ITG Workshop on Smart Antennas (WSA2018)
Projects
5GwirelessELLIITCENIIT
Available from: 2018-06-22 Created: 2018-06-22 Last updated: 2018-06-26
Do, T. T., Björnson, E., Larsson, E. G. & Mohammad Razavizadeh, S. (2018). Jamming-Resistant Receivers for the Massive MIMO Uplink. Paper presented at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE Transactions on Information Forensics and Security, 13(1), 210-223
Open this publication in new window or tab >>Jamming-Resistant Receivers for the Massive MIMO Uplink
2018 (English)In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 13, no 1, p. 210-223Article in journal (Refereed) Published
Abstract [en]

We design a jamming-resistant receiver scheme to enhance the robustness of a massive MIMO uplink system against jamming. We assume that a jammer attacks the system both in the pilot and data transmission phases. The key feature of the proposed scheme is that, in the pilot phase, the base station estimates not only the legitimate channel, but also the jamming channel by exploiting a purposely unused pilot sequence. The jamming channel estimate is used to construct linear receiver filters that reject the impact of the jamming signal. The performance of the proposed scheme is analytically evaluated using the asymptotic properties of massive MIMO. The best regularized zero-forcing receiver and the optimal power allocations for the legitimate system and the jammer are also studied. Numerical results are provided to verify our analysis and show that the proposed scheme greatly improves the achievable rates, as compared with conventional receivers. Interestingly, the proposed scheme works particularly well under strong jamming attacks, since the improved estimate of the jamming channel outweighs the extra jamming power.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Massive MIMO; jamming attack; receiver filter; optimal power allocation
National Category
Signal Processing
Identifiers
urn:nbn:se:liu:diva-143986 (URN)10.1109/TIFS.2017.2746007 (DOI)000417725500016 ()2-s2.0-85028560448 (Scopus ID)
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Note

Funding Agencies|ELLIIT; CENIIT

Available from: 2018-01-02 Created: 2018-01-02 Last updated: 2018-01-12Bibliographically approved
Van Chien, T., Björnson, E. & Larsson, E. G. (2018). Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems. IEEE Transactions on Wireless Communications, 17(3), 2000-2015
Open this publication in new window or tab >>Joint Pilot Design and Uplink Power Allocation in Multi-Cell Massive MIMO Systems
2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 3, p. 2000-2015Article in journal (Refereed) Published
Abstract [en]

This paper considers pilot design to mitigate pilot contamination and provide good service for everyone in multi-cell Massive multiple input multiple output (MIMO) systems. Instead of modeling the pilot design as a combinatorial assignment problem, as in prior works, we express the pilot signals using a pilot basis and treat the associated power coefficients as continuous optimization variables. We compute a lower bound on the uplink capacity for Rayleigh fading channels with maximum ratio detection that applies with arbitrary pilot signals. We further formulate the max-min fairness problem under power budget constraints, with the pilot signals and data powers as optimization variables. Because this optimization problem is non-deterministic polynomial-time hard due to signomial constraints, we then propose an algorithm to obtain a local optimum with polynomial complexity. Our framework serves as a benchmark for pilot design in scenarios with either ideal or non-ideal hardware. Numerical results manifest that the proposed optimization algorithms are close to the optimal solution obtained by exhaustive search for different pilot assignments and the new pilot structure and optimization bring large gains over the state-of-the-art suboptimal pilot design.

Place, publisher, year, edition, pages
IEEE Communications Society, 2018
Keywords
Massive MIMO, Pilot Design, Signomial Programming, Geometric Programming, Hardware Impairments.
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-145713 (URN)10.1109/TWC.2017.2787702 (DOI)000427226500042 ()2-s2.0-85040035548 (Scopus ID)
Projects
CENIIT
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsEU, Horizon 2020, 641985
Note

Funding agencies:This work was supported in part by the European Union's Horizon 2020 Research and Innovation Programme under Grant 641985 (5Gwireless), in part by ELLIIT, and in part by CENIIT. This paper was presented at the IEEE ICC 2017. The associate editor coordinating the review of this paper and approving it for publication was T. Lok.

Available from: 2018-03-19 Created: 2018-03-19 Last updated: 2018-04-12Bibliographically approved
Sadeghi, M., Björnson, E., Larsson, E. G., Yuen, C. & Marzetta, T. L. (2018). Joint Unicast and Multi-group Multicast Transmission in Massive MIMO Systems. IEEE Transactions on Wireless Communications, 17(10), 6375-6388
Open this publication in new window or tab >>Joint Unicast and Multi-group Multicast Transmission in Massive MIMO Systems
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2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 10, p. 6375-6388Article in journal (Refereed) Published
Abstract [en]

We study the joint unicast and multi-group multicast transmission in massive multiple-input-multiple-output (MIMO) systems. We consider a system model that accounts for channel estimation and pilot contamination, and derive achievable spectral efficiencies (SEs) for unicast and multicast user terminals (UTs), under maximum ratio transmission and zero-forcing precoding. For unicast transmission, our objective is to maximize the weighted sum SE of the unicast UTs, and for the multicast transmission, our objective is to maximize the minimum SE of the multicast UTs. These two objectives are coupled in a conflicting manner, due to their shared power resource. Therefore, we formulate a multiobjective optimization problem (MOOP) for the two conflicting objectives. We derive the Pareto boundary of the MOOP analytically. As each Pareto optimal point describes a particular efficient trade-off between the two objectives of the system, we determine the values of the system parameters (uplink training powers, downlink transmission powers, etc.) to achieve any desired Pareto optimal point. Moreover, we prove that the Pareto region is convex, hence the system should serve the unicast and multicast UTs at the same time-frequency resource. Finally, we validate our results using numerical simulations.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-150940 (URN)10.1109/TWC.2018.2854554 (DOI)000447047200001 ()2-s2.0-85050020525 (Scopus ID)
Note

Funding agencies: Swedish Research Council (VR); Swedish Foundation for Strategic Research (SSF); ELLIIT; Singapore University of Technology and Design; A*Star SERC Project [142-02-00043]; National Science Foundation of China [61750110529]

Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-10-30Bibliographically approved
Ghazanfar, A., Björnson, E. & Larsson, E. G. (2018). Power Control for D2D Underlay in Multi-cell Massive MIMO Networks. In: : . Paper presented at The 22nd International ITG Workshop on Smart Antennas (WSA 2018), March 14-16, Bochum, Germany.
Open this publication in new window or tab >>Power Control for D2D Underlay in Multi-cell Massive MIMO Networks
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a new power control and pilot allocation scheme for device-to-device (D2D) communication underlaying a multi-cell massive MIMO system. In this scheme, the cellular users in each cell get orthogonal pilots which are reused with reuse factor one across cells, while the D2D pairs share another set of orthogonal pilots. We derive a closed-form capacity lower bound for the cellular users with different receive processing schemes. In addition, we derive a capacity lower bound for the D2D receivers and a closed-form approximation of it. Then we provide a power control algorithm that maximizes the minimum spectral efficiency (SE) of the users in the network. Finally, we provide a numerical evaluation where we compare our proposed power control algorithm with the maximum transmit power case and the case of conventional multi-cell massive MIMO without D2D communication. Based on the provided results, we conclude that our proposed scheme increases the sum spectral efficiency of multi-cell massive MIMO networks.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-149566 (URN)978-3-8007-4541-8 (ISBN)
Conference
The 22nd International ITG Workshop on Smart Antennas (WSA 2018), March 14-16, Bochum, Germany
Projects
5Gwireless
Available from: 2018-07-06 Created: 2018-07-06 Last updated: 2018-07-06
Do, T. T., Björnson, E. & Larsson, E. G. (2017). JAMMING RESISTANT RECEIVERS FOR MASSIVE MIMO. In: 2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at The 42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2017), New Orleans, USA, March 5-9, 2017 (pp. 3619-3623). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>JAMMING RESISTANT RECEIVERS FOR MASSIVE MIMO
2017 (English)In: 2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 3619-3623Conference paper, Published paper (Refereed)
Abstract [en]

We design jamming resistant receivers to enhance the robustness of a massive MIMO uplink channel against jamming. In the pilot phase, we estimate not only the desired channel, but also the jamming channel by exploiting purposely unused pilot sequences. The jamming channel estimate is used to construct the linear receive filter to reduce impact that jamming has on the achievable rates. The performance of the proposed scheme is analytically and numerically evaluated. These results show that the proposed scheme greatly improves the rates, as compared to conventional receivers. Moreover, the proposed schemes still work well with stronger jamming power.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keywords
Massive MIMO; jamming attack; receive filter
National Category
Signal Processing
Identifiers
urn:nbn:se:liu:diva-144281 (URN)10.1109/ICASSP.2017.7952831 (DOI)000414286203156 ()2-s2.0-85023753985 (Scopus ID)978-1-5090-4117-6 (ISBN)
Conference
The 42nd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2017), New Orleans, USA, March 5-9, 2017
Available from: 2018-01-12 Created: 2018-01-12 Last updated: 2018-01-19Bibliographically approved
Verenzuela, D., Björnson, E. & Sanguinetti, L. (2017). Joint UL and DL Spectral Efficiency Optimization of Superimposed Pilots in Massive MIMO. In: Proceedings of 2017 IEEE Globecom Workshops (GC Wkshps): . Paper presented at 4-8 Dec 2017 Globecom Workshops (GC Wkshps), Singapore, Singapore (pp. 1-7). IEEE
Open this publication in new window or tab >>Joint UL and DL Spectral Efficiency Optimization of Superimposed Pilots in Massive MIMO
2017 (English)In: Proceedings of 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, 2017, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

The reuse of pilot sequences in a Massive MIMO system leads to pilot contamination, which reduces the channel estimation quality and adds coherent interference in the data transmission. A standard method to reduce pilot contamination, known as regular pilots (RPs), is to increase the pilot overhead and reuse pilots more sparsely in the network. Another approach, denoted as superimposed pilots (SPs), is to send a superposition of pilot and data symbols which allows the system to reuse pilots far more sparsely. This work performs a comparative analysis of RPs and SPs in Massive MIMO considering the joint spectral efficiency (SE) of the uplink (UL) and downlink (DL) communications. A rigorous DL lower bound on the capacity with SPs is derived and multiobjective optimization theory is used to compare the UL and DL SE between RPs and SPs. Numerical results indicate that RPs and SPs give comparable SE when both methods are optimized.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE Globecom Workshops
Keywords
MIMO communication, channel estimation, data communication, optimisation, DL spectral efficiency optimization, SP, channel estimation quality, data symbols, data transmission, joint spectral efficiency, massive MIMO system, pilot contamination, pilot overhead, pilot sequences, superimposed pilots, Antennas, Contamination, Interference, Optimization, Uplink
National Category
Telecommunications
Identifiers
urn:nbn:se:liu:diva-145678 (URN)10.1109/GLOCOMW.2017.8269159 (DOI)000426984700128 ()9781538639207 (ISBN)9781538639214 (ISBN)
Conference
4-8 Dec 2017 Globecom Workshops (GC Wkshps), Singapore, Singapore
Note

Funding agencies: Swedish Foundation for Strategic Research (SSF); ERC Starting MORE [305123]; Swedish Research Council; ELLIIT

Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2018-04-12Bibliographically approved
Björnson, E., Hoydis, J. & Sanguinetti, L. (2017). Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency. Boston - Delft: Now Publishers Inc.
Open this publication in new window or tab >>Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency
2017 (English)Book (Refereed)
Abstract [en]

Massive multiple-input multiple-output (Massive MIMO) is the latest technology that will improve the speed and throughput of wireless communication systems for years to come. Whilst there may be some debate over the origins of the term Massive MIMO and what it precisely means, this monograph describes in detail how the research conducted in the past decades lead to a scalable multiantenna technology that offers great throughput and energy efficiency under practical conditions. Written for students, practicing engineers and researchers who want to learn the conceptual and analytical foundations of Massive MIMO, in terms of spectral, energy, and/or hardware efficiency, as well as channel estimation and practical considerations, it provides a clear and tutorial like exposition of all the major topics. It also connects the dots of the research literature covering numerous topics not easily found therein. Massive MIMO Networks is the first monograph on the subject to cover the spatial chan el correlation and consider rigorous signal processing design essential for the complete understanding by its target audience.

Place, publisher, year, edition, pages
Boston - Delft: Now Publishers Inc., 2017. p. 516
Series
Foundations and Trends® in Signal Processing, ISSN 1932-8346 ; 11(3-4)
National Category
Telecommunications Communication Systems Signal Processing
Identifiers
urn:nbn:se:liu:diva-148736 (URN)10.1561/2000000093 (DOI)9781680839852 (ISBN)9781680833652 (ISBN)
Available from: 2018-06-18 Created: 2018-06-18 Last updated: 2018-06-25Bibliographically approved
Sadeghi, M., Björnson, E., Larsson, E. G., Yuen, C. & Marzetta, T. L. (2017). Max–Min Fair Transmit Precoding for Multi-Group Multicasting in Massive MIMO. IEEE Transactions on Wireless Communications, 17(2), 1358-1373
Open this publication in new window or tab >>Max–Min Fair Transmit Precoding for Multi-Group Multicasting in Massive MIMO
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2017 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 2, p. 1358-1373Article in journal (Refereed) Published
Abstract [en]

This paper considers the downlink precoding for physical layer multicasting in massive multiple-input multiple-output (MIMO) systems. We study the max-min fairness (MMF) problem, where channel state information at the transmitter is used to design precoding vectors that maximize the minimum spectral efficiency (SE) of the system, given fixed power budgets for uplink training and downlink transmission. Our system model accounts for channel estimation, pilot contamination, arbitrary path-losses, and multi-group multicasting. We consider six scenarios with different transmission technologies (unicast and multicast), different pilot assignment strategies (dedicated or shared pilot assignments), and different precoding schemes (maximum ratio transmission and zero forcing), and derive achievable spectral efficiencies for all possible combinations. Then, we solve the MMF problem for each of these scenarios, and for any given pilot length, we find the SE maximizing uplink pilot and downlink data transmission policies, all in closed forms. We use these results to draw a general guideline for massive MIMO multicasting design, where for a given number of base station antennas, number of users, and coherence interval length, we determine the multicasting scheme that shall be used.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
Keywords
Multicast transmission, massive MIMO, physical layer precoding, large-scale antenna systems
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-150942 (URN)10.1109/TWC.2017.2777987 (DOI)000424945600048 ()2-s2.0-85038352945 (Scopus ID)
Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-09-12Bibliographically approved
Verenzuela, D., Björnson, E. & Matthaiou, M. (2017). Per-antenna hardware optimization and mixed resolution ADCs in uplink massive MIMO. In: 2017 51st Asilomar Conference on Signals, Systems, and Computers: . Paper presented at 2017 51st Asilomar Conference on Signals, Systems, and Computers. Pacific Grove, CA, USA. 29 Oct.-1 Nov. 2017. (pp. 27-31). IEEE conference proceedings
Open this publication in new window or tab >>Per-antenna hardware optimization and mixed resolution ADCs in uplink massive MIMO
2017 (English)In: 2017 51st Asilomar Conference on Signals, Systems, and Computers, IEEE conference proceedings, 2017, p. 27-31Conference paper, Published paper (Refereed)
Abstract [en]

Massive multiple-input multiple-output (MIMO) is a key technology for next generation wireless networks that deploys many antennas at the base stations (BSs). This requires low-complexity hardware at each antenna branch that, in turn, increases distortions. This work studies the selection of per-antenna hardware quality in terms of analog-to-digital converters (ADCs) resolution. A new achievable spectral efficiency (SE) expression is derived and majorization theory is used to analyze the order preserving properties of the SE and the power consumption with respect to the per-antenna ADC resolutions. That is, given a fixed sum of ADC resolutions across the antenna array, is it preferable to use an equal-ADC over a mixed-ADC approach? The results show that having equal-resolution ADCs across the antenna array maximizes the SE and minimizes the power consumption.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2017
Keywords
Distortion, Hardware, MIMO communication, Power demand, Antenna arrays, Complexity theory
National Category
Telecommunications Signal Processing Communication Systems
Identifiers
urn:nbn:se:liu:diva-148777 (URN)10.1109/ACSSC.2017.8335129 (DOI)000442659900005 ()978-1-5386-1823-3 (ISBN)
Conference
2017 51st Asilomar Conference on Signals, Systems, and Computers. Pacific Grove, CA, USA. 29 Oct.-1 Nov. 2017.
Note

Funding agencies: ELLIIT; Swedish Foundation for Strategic Research (SSF); EPSRC [EP/P000673/1]

Available from: 2018-06-19 Created: 2018-06-19 Last updated: 2018-09-21Bibliographically approved
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