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Sadeghi, M. & Larsson, E. G. (2019). Adversarial Attacks on Deep-Learning Based Radio Signal Classification. IEEE Wireless Communications Letters, 8(1), 213-216
Open this publication in new window or tab >>Adversarial Attacks on Deep-Learning Based Radio Signal Classification
2019 (English)In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 8, no 1, p. 213-216Article in journal (Refereed) Published
Abstract [en]

Deep learning (DL), despite its enormous success in many computer vision and language processing applications, is exceedingly vulnerable to adversarial attacks. We consider the use of DL for radio signal (modulation) classification tasks, and present practical methods for the crafting of white-box and universal black-box adversarial attacks in that application. We show that these attacks can considerably reduce the classification performance, with extremely small perturbations of the input. In particular, these attacks are significantly more powerful than classical jamming attacks, which raises significant security and robustness concerns in the use of DL-based algorithms for the wireless physical layer.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
Adversarial attacks, Deep learning, Wireless security, Modulation classification, Neural networks.
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-150945 (URN)10.1109/LWC.2018.2867459 (DOI)000459510200053 ()2-s2.0-85052663750 (Scopus ID)
Note

Funding agencies: ELLIIT, Security-Link; SURPRISE project - Swedish Foundation for Strategic Research (SSF)

Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2019-03-08Bibliographically approved
Özdogan, Ö., Björnson, E. & Larsson, E. G. (2019). Massive MIMO With Spatially Correlated Rician Fading Channels. Paper presented at 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE Transactions on Communications, 67(5), 3234-3250
Open this publication in new window or tab >>Massive MIMO With Spatially Correlated Rician Fading Channels
2019 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 5, p. 3234-3250Article in journal (Refereed) Published
Abstract [en]

This paper considers multi-cell massive multiple-input multiple-output systems, where the channels are spatially correlated Rician fading. The channel model is composed of a deterministic line-of-sight path and a stochastic non-line-of-sight component describing a practical spatially correlated multipath environment. We derive the statistical properties of the minimum mean squared error (MMSE), element-wise MMSE, and least-square channel estimates for this model. Using these estimates for maximum ratio combining and precoding, rigorous closed-form uplink (UL) and downlink (DL) achievable spectral efficiency (SE) expressions are derived and analyzed. The asymptotic SE behavior, when using the different channel estimators, are also analyzed. The numerical results show that the SE is higher when using the MMSE estimator than that of the other estimators, and the performance gap increases with the number of antennas.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
Massive MIMO; spatially correlated Rician fading; channel estimation; spectral efficiency
National Category
Signal Processing
Identifiers
urn:nbn:se:liu:diva-158364 (URN)10.1109/TCOMM.2019.2893221 (DOI)000468228900011 ()2-s2.0-85059952523 (Scopus ID)
Conference
19th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Note

Funding Agencies|ELLIIT; Swedish Research Council

Available from: 2019-07-02 Created: 2019-07-02 Last updated: 2019-08-09Bibliographically approved
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: 2019-06-28
Interdonato, G., Karlsson, M., Björnson, E. & Larsson, E. G. (2018). Downlink Spectral Efficiency of Cell-Free Massive MIMO with Full-Pilot Zero-Forcing. In: 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP): . Paper presented at 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Anaheim, CA, USA (pp. 1003-1007).
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
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: 2019-06-28Bibliographically 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: 2019-06-28Bibliographically 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
Show others...
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: 2019-06-28Bibliographically approved
Senel, K. & Larsson, E. G. (2018). Joint User Activity and Non-Coherent Data Detection in mMTC-Enabled Massive MIMO Using Machine Learning Algorithms. In: Proceedings of International ITG Workshop on Smart Antennas (WSA): . Paper presented at 22nd International ITG workshop on smart antennas (WSA), 2018. Berlin, Germany
Open this publication in new window or tab >>Joint User Activity and Non-Coherent Data Detection in mMTC-Enabled Massive MIMO Using Machine Learning Algorithms
2018 (English)In: Proceedings of International ITG Workshop on Smart Antennas (WSA), Berlin, Germany, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Machine-type communication (MTC) services are expected to be an integral part of the future cellular systems. A key challenge of MTC, especially for the massive MTC (mMTC), is the detection of active devices among a large number of devices. The sparse characteristics of mMTC makes compressed sensing (CS) approaches a promising solution to the device detection problem. CS-based techniques are shown to outperform conventional device detection approaches. However, utilizing CS-based approaches for device detection along with channel estimation and using the acquired estimates for coherent data transmission may not be the optimal approach, especially for the cases where the goal is to convey only a few bits of data. In this work, we propose a non-coherent transmission technique for the mMTC uplink and compare its performance with coherent transmission. Furthermore, we demonstrate that it is possible to obtain more accurate channel state information by combining the conventional estimators with CS-based techniques.

Place, publisher, year, edition, pages
Berlin, Germany: , 2018
Keywords
Massive MIMO, Machine Type Communications
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-149577 (URN)978-3-8007-4541-8 (ISBN)
Conference
22nd International ITG workshop on smart antennas (WSA), 2018
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Research Council
Available from: 2018-07-06 Created: 2018-07-06 Last updated: 2018-07-06
Chandhar, P., Danev, D. & Larsson, E. G. (2018). Massive MIMO for Communications With Drone Swarms. IEEE Transactions on Wireless Communications, 17(3), 1604-1629
Open this publication in new window or tab >>Massive MIMO for Communications With Drone Swarms
2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 3, p. 1604-1629Article in journal (Refereed) Published
Abstract [en]

We illustrate the potential of Massive MIMO for communication with unmanned aerial vehicles (UAVs). We consider a scenario, where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Specifically, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight conditions. We develop a realistic geometric model, which incorporates an arbitrary orientation, of the GS and UAV antenna elements to characterize the polarization mismatch loss, which occurs due to the movement and orientation of the UAVs. A closed-form expression for a lower bound on the ergodic rate for a maximum-ratio combining receiver with estimated channel state information is derived. The optimal antenna spacing that maximizes the ergodic rate achieved by an UAV is also determined for uniform linear and rectangular arrays. It is shown that when the UAVs are spherically uniformly distributed around the GS, the ergodic rate per UAV is maximized for an antenna spacing equal to an integer multiple of one-half wavelength.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Unmanned aerial vehicles; Massive MIMO; ergodic capacity
National Category
Telecommunications
Identifiers
urn:nbn:se:liu:diva-147124 (URN)10.1109/TWC.2017.2782690 (DOI)000427226500015 ()
Note

Funding Agencies|Swedish Research Council (VR); ELLIIT

Available from: 2018-04-20 Created: 2018-04-20 Last updated: 2018-06-13
Chandhar, P., Danev, D. & Larsson, E. G. (2018). On the Zero-Forcing Receiver Performance for Massive MIMO Drone Communications. In: 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC): . Paper presented at IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 25-28 June 2018, Kalamata, Greece (pp. 930-934). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>On the Zero-Forcing Receiver Performance for Massive MIMO Drone Communications
2018 (English)In: 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 930-934Conference paper, Published paper (Refereed)
Abstract [en]

We study the uplink ergodic rate performance of the zero-forcing (ZF) receiver in a Massive multiple-input and multiple-output (MIMO) enabled drone communication system. Considering a 3D geometric model for line-of-sight (LoS) propagation, approximate but accurate analyses of lower and upper bounds on the uplink ergodic rate with estimated channel state information (CSI) are provided.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
Signal Processing Advances in Wireless Communications (SPAWC), E-ISSN 1948-3252 ; 2018
Keywords
Signal to noise ratio, Drones, Receivers, MIMO communication, Interference, Antennas, Uplink
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-152454 (URN)10.1109/SPAWC.2018.8445989 (DOI)000451080200187 ()9781538635124 (ISBN)9781538635117 (ISBN)9781538635131 (ISBN)
Conference
IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 25-28 June 2018, Kalamata, Greece
Note

Funding Agencies|Swedish Research Council (VR); ELLIIT

Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2019-06-19Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-7599-4367

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