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Sadeghi, M. & Larsson, E. G. (2018). Adversarial Attacks on Deep-Learning Based Radio Signal Classification. IEEE Wireless Communications Letters
Open this publication in new window or tab >>Adversarial Attacks on Deep-Learning Based Radio Signal Classification
2018 (English)In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345Article in journal (Refereed) Epub ahead of print
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), 2018
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)2-s2.0-85052663750 (Scopus ID)
Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-09-12Bibliographically 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: 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
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 1558-2248Article in journal (Refereed) Epub ahead of print
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)2-s2.0-85050020525 (Scopus ID)
Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-09-12Bibliographically 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
Larsson, E. G. & Van der Perre, L. (2018). Out-of-Band Radiation From Antenna Arrays Clarified. IEEE Wireless Communications Letters, 7(4), 610-613
Open this publication in new window or tab >>Out-of-Band Radiation From Antenna Arrays Clarified
2018 (English)In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, no 4, p. 610-613Article in journal (Refereed) Published
Abstract [en]

Non-linearities in radio-frequency transceiver hardware, particularly in power amplifiers, cause distortion in-band and out-of-band. Contrary to claims made in recent literature, in a multiple-antenna system this distortion is correlated across the antennas in the array. A significant implication of this fact is that out-of-band emissions caused by non-linearities are beamformed, in some cases into the same direction as the useful signal.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Antenna arrays; power amplifier; nonlinearity; hardware distortion; MIMO; beamforming; millimeter wave; 5G
National Category
Signal Processing
Identifiers
urn:nbn:se:liu:diva-151208 (URN)10.1109/LWC.2018.2802519 (DOI)000442368700031 ()
Note

Funding Agencies|Swedish Research Council (VR); ELLIIT

Available from: 2018-09-13 Created: 2018-09-13 Last updated: 2018-10-05
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
Interdonato, G., Frenger, P. & Larsson, E. G. (2018). Utility-based Downlink Pilot Assignment in Cell-Free Massive MIMO. 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 >>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
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-7599-4367

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