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Björnson, Emil
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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
Keyword
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
Keyword
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
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
Keyword
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
Keyword
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., Sanguinetti, L. & Kountouris, M. (2016). Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO. IEEE Journal on Selected Areas in Communications, 34(4), 832-847
Open this publication in new window or tab >>Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO
2016 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 34, no 4, p. 832-847Article in journal (Refereed) Published
Abstract [en]

What would a cellular network designed for maximal energy efficiency look like? To answer this fundamental question, tools from stochastic geometry are used in this paper to model future cellular networks and obtain a new lower bound on the average uplink spectral efficiency. This enables us to formulate a tractable uplink energy efficiency (EE) maximization problem and solve it analytically with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor. The closed-form expressions obtained from this general EE maximization framework provide valuable insights on the interplay between the optimization variables, hardware characteristics, and propagation environment. Small cells are proved to give high EE, but the EE improvement saturates quickly with the BS density. Interestingly, the maximal EE is achieved by also equipping the BSs with multiple antennas and operate in a "massive MIMO" fashion, where the array gain from coherent detection mitigates interference and the multiplexing of many users reduces the energy cost per user.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2016
Keyword
Energy efficiency; massive MIMO; small cells; stochastic geometry
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-130309 (URN)10.1109/JSAC.2016.2544498 (DOI)000377928500012 ()
Note

Funding Agencies|ELLIIT; Swedish Foundation for Strategic Research; People Programme (Marie Curie Actions) FP7 [PIEF-GA-2012-330731 Dense4Green]; ERC [305123 MORE]

Available from: 2016-07-31 Created: 2016-07-28 Last updated: 2017-11-28
Van Chien, T., Björnson, E. & Larsson, E. G. (2016). Downlink Power Control for Massive MIMO Cellular Systems with Optimal User Association. In: IEEE International Conference on Communications, Malaysia, May 23-27, 2016: proceedings. Paper presented at IEEE International Conference on Communications, Malaysia, May 23-27. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Downlink Power Control for Massive MIMO Cellular Systems with Optimal User Association
2016 (English)In: IEEE International Conference on Communications, Malaysia, May 23-27, 2016: proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper aims to minimize the total transmit power consumption for Massive MIMO (multiple-input multiple-output) downlink cellular systems when each user is served by the optimized subset of the base stations (BSs). We derive a lower bound on the ergodic spectral efficiency (SE) for Rayleigh fading channels and maximum ratio transmission (MRT) when the BSs cooperate using non-coherent joint transmission. We solve the joint user association and downlink transmit power minimization problem optimally under fixed SE constraints. Furthermore, we solve a max-min fairness problem with user specific weights that maximizes the worst SE among the users. The optimal BS-user association rule is derived, which is different from maximum signal-to-noise-ratio (max-SNR) association. Simulation results manifest that the proposed methods can provide good SE for the users using less transmit power than in small-scale systems and that the optimal user association can effectively balance the load between BSs when needed.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Series
IEEE International Conference on Communications, ISSN 1550-3607
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-130168 (URN)10.1109/ICC.2016.7510950 (DOI)000390993201146 ()978-1-5090-0448-5 (ISBN)
Conference
IEEE International Conference on Communications, Malaysia, May 23-27
Available from: 2016-07-13 Created: 2016-07-13 Last updated: 2017-01-29Bibliographically approved
Verenzuela, D., Björnson, E. & Matthaiou, M. (2016). Hardware Design and Optimal ADC Resolution for Uplink Massive MIMO Systems. In: IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Rio de Janeiro, Brazil, July 2016.: . Paper presented at IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) 2016. (pp. 1-5).
Open this publication in new window or tab >>Hardware Design and Optimal ADC Resolution for Uplink Massive MIMO Systems
2016 (English)In: IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Rio de Janeiro, Brazil, July 2016., 2016, p. 1-5Conference paper, Published paper (Refereed)
Abstract [en]

This work focuses on the hardware design for the efficient operation of Massive multiple-input multiple-output (MIMO) systems. A closed-form uplink achievable data rate expression is derived considering imperfect channel state information (CSI) and hardware impairments. We formulate an optimization problem to maximize the sum data rate subject to a constraint on the total power consumption. A general power consumption model accounting for the level of hardware impairments is utilized. The optimization variables are the number of base station (BS) antennas and the level of impairments per BS antenna. The resolution of the analog-to-digital converter (ADC) is a primary source of such impairments. The results show the trade-off between the number of BS antennas and the level of hardware impairments, which is important for practical hardware design. Moreover, the maximum power consumption can be tuned to achieve maximum energy efficiency (EE). Numerical results suggest that the optimal level of hardware impairments yields ADCs of 4 to 5 quantization bits.

National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-137324 (URN)
Conference
IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) 2016.
Available from: 2017-05-12 Created: 2017-05-12 Last updated: 2018-03-15Bibliographically approved
Van Chien, T., Björnson, E. & Larsson, E. G. (2016). Joint Power Allocation and User Association Optimization for Massive MIMO Systems. IEEE Transactions on Wireless Communications, 15(9), 6384-6399
Open this publication in new window or tab >>Joint Power Allocation and User Association Optimization for Massive MIMO Systems
2016 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 9, p. 6384-6399Article in journal (Refereed) Published
Abstract [en]

This paper investigates the joint power allocationand user association problem in multi-cell Massive MIMO(multiple-input multiple-output) downlink (DL) systems. Thetarget is to minimize the total transmit power consumptionwhen each user is served by an optimized subset of the basestations (BSs), using non-coherent joint transmission. We firstderive a lower bound on the ergodic spectral efficiency (SE),which is applicable for any channel distribution and precodingscheme. Closed-form expressions are obtained for Rayleigh fadingchannels with either maximum ratio transmission (MRT) or zeroforcing (ZF) precoding. From these bounds, we further formulatethe DL power minimization problems with fixed SE constraintsfor the users. These problems are proved to be solvable aslinear programs, giving the optimal power allocation and BS-user association with low complexity. Furthermore, we formulatea max-min fairness problem which maximizes the worst SEamong the users, and we show that it can be solved as aquasi-linear program. Simulations manifest that the proposedmethods provide good SE for the users using less transmit powerthan in small-scale systems and the optimal user associationcan effectively balance the load between BSs when needed.Even though our framework allows the joint transmission frommultiple BSs, there is an overwhelming probability that only oneBS is associated with each user at the optimal solution.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keyword
Massive MIMO, user association, power allocation, load balancing, linear program
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-131129 (URN)10.1109/TWC.2016.2583436 (DOI)000384241400040 ()
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2016-09-11 Created: 2016-09-11 Last updated: 2018-01-11Bibliographically approved
Mueller, A., Kammoun, A., Björnson, E. & Debbah, M. (2016). Linear precoding based on polynomial expansion: reducing complexity in massive MIMO. EURASIP Journal on Wireless Communications and Networking (63)
Open this publication in new window or tab >>Linear precoding based on polynomial expansion: reducing complexity in massive MIMO
2016 (English)In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, no 63Article in journal (Refereed) Published
Abstract [en]

Massive multiple-input multiple-output (MIMO) techniques have the potential to bring tremendous improvements in spectral efficiency to future communication systems. Counterintuitively, the practical issues of having uncertain channel knowledge, high propagation losses, and implementing optimal non-linear precoding are solved more or less automatically by enlarging system dimensions. However, the computational precoding complexity grows with the system dimensions. For example, the close-to-optimal and relatively "antenna-efficient" regularized zero-forcing (RZF) precoding is very complicated to implement in practice, since it requires fast inversions of large matrices in every coherence period. Motivated by the high performance of RZF, we propose to replace the matrix inversion and multiplication by a truncated polynomial expansion (TPE), thereby obtaining the new TPE precoding scheme which is more suitable for real-time hardware implementation and significantly reduces the delay to the first transmitted symbol. The degree of the matrix polynomial can be adapted to the available hardware resources and enables smooth transition between simple maximum ratio transmission and more advanced RZF. By deriving new random matrix results, we obtain a deterministic expression for the asymptotic signal-to-interference-and-noise ratio (SINR) achieved by TPE precoding in massive MIMO systems. Furthermore, we provide a closed-form expression for the polynomial coefficients that maximizes this SINR. To maintain a fixed per-user rate loss as compared to RZF, the polynomial degree does not need to scale with the system, but it should be increased with the quality of the channel knowledge and the signal-to-noise ratio.

Place, publisher, year, edition, pages
SPRINGER INTERNATIONAL PUBLISHING AG, 2016
Keyword
Massive MIMO; Linear precoding; Multiuser systems; Polynomial expansion; Random matrix theory
National Category
Signal Processing Communication Systems
Identifiers
urn:nbn:se:liu:diva-126837 (URN)10.1186/s13638-016-0546-z (DOI)000371395700001 ()
Note

Funding Agencies|ERC [305123]; Swedish Research Council

Available from: 2016-04-05 Created: 2016-04-05 Last updated: 2017-11-30
Björnson, E., Larsson, E. G. & Debbah, M. (2016). Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?. IEEE Transactions on Wireless Communications, 15(2), 1293-1308
Open this publication in new window or tab >>Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?
2016 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 2, p. 1293-1308Article in journal (Refereed) Published
Abstract [en]

Massive MIMO is a promising technique for increasing the spectral efficiency (SE) of cellular networks, by deploying antenna arrays with hundreds or thousands of active elements at the base stations and performing coherent transceiver processing. A common rule-of-thumb is that these systems should have an order of magnitude more antennas M than scheduled users K because the users channels are likely to be near-orthogonal when M/K > 10. However, it has not been proved that this rule-of-thumb actually maximizes the SE. In this paper, we analyze how the optimal number of scheduled users K-star depends on M and other system parameters. To this end, new SE expressions are derived to enable efficient system-level analysis with power control, arbitrary pilot reuse, and random user locations. The value of K-star in the large-M regime is derived in closed form, while simulations are used to show what happens at finite M, in different interference scenarios, with different pilot reuse factors, and for different processing schemes. Up to half the coherence block should be dedicated to pilots and the optimal M/K is less than 10 in many cases of practical relevance. Interestingly, K-star depends strongly on the processing scheme and hence it is unfair to compare different schemes using the same K.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2016
Keyword
Coordinated multipoint; massive MIMO; multi-cell; pilot contamination; spectral efficiency; user scheduling
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-126261 (URN)10.1109/TWC.2015.2488634 (DOI)000370949600036 ()
Note

Funding Agencies|EU [ICT-619086]; ELLIIT; Swedish Research Council (VR); ERC [305123 MORE]

Available from: 2016-03-21 Created: 2016-03-21 Last updated: 2017-11-30
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