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Publications (10 of 471) Show all publications
Rodríguez Gálvez, B., Thobaben, R. & Skoglund, M. (2020). The Convex Information Bottleneck Lagrangian. Entropy, 22(1), Article ID 98.
Open this publication in new window or tab >>The Convex Information Bottleneck Lagrangian
2020 (English)In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 22, no 1, article id 98Article in journal (Refereed) Published
Abstract [en]

The information bottleneck (IB) problem tackles the issue of obtaining relevant compressedrepresentations T of some random variable X for the task of predicting Y. It is defined as a constrainedoptimization problem that maximizes the information the representation has about the task, I(T;Y) ,while ensuring that a certain level of compression r is achieved (i.e., I(X;T) ≤ r). For practical reasons,the problem is usually solved by maximizing the IB Lagrangian for many values of the Lagrange multiplier. Then, the curve of maximal I(T;Y) for a givenI(X;T) is drawn anda representation with the desired predictability and compression is selected. It is known when Yis a deterministic function of X, the IB curve cannot be explored and another Lagrangian has beenproposed to tackle this problem: the squared IB Lagrangian. In this paper, we (i) present a general family of Lagrangians which allow for the exploration of the IBcurve in all scenarios; (ii) provide the exact one-to-one mapping between the Lagrange multiplierand the desired compression rate r for known IB curve shapes; and (iii) show we can approximatelyobtain a specific compression level with the convex IB Lagrangian for both known and unknown IBcurve shapes. This eliminates the burden of solving the optimization problem for many values of theLagrange multiplier. That is, we prove that we can solve the original constrained problem with asingle optimization.

Place, publisher, year, edition, pages
MDPI, 2020
Keywords
information bottleneck; representation learning; mutual information; optimization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-266691 (URN)10.3390/e22010098 (DOI)2-s2.0-85078523691 (Scopus ID)
Note

QC 20200120

Available from: 2020-01-16 Created: 2020-01-16 Last updated: 2020-02-04Bibliographically approved
Ghauch, H., Kim, T., Fischione, C. & Skoglund, M. (2019). Compressive Sensing with Applications to Millimeter-wave Architectures. In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 12-17, 2019, Brighton, ENGLAND (pp. 7834-7838). IEEE
Open this publication in new window or tab >>Compressive Sensing with Applications to Millimeter-wave Architectures
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2019, p. 7834-7838Conference paper, Published paper (Refereed)
Abstract [en]

To make the system available at low-cost, millimeter-ave (mmWave) multiple-input multiple-output (MIMO) architectures employ analog arrays, which are driven by a limited number of radio frequency (RF) chains. One primary challenge of using large hybrid analog-digital arrays is that the digital baseband cannot directly access the signal to/from each antenna. To address this limitation, recent research has focused on retransmissions, iterative precoding, and subspace decomposition methods. Unlike these approaches that exploited the channel's low-rank, in this work we exploit the sparsity of the received signal at both the transmit/receive antennas. While the signal itself is de facto dense, it is well-known that most signals are sparse under an appropriate choice of basis. By delving into the structured compressive sensing (CS) framework and adapting them to variants of the mmWave hybrid architectures, we provide methodologies to recover the analog signal at each antenna from the (low-dimensional) digital signal. Moreover, we characterizes the minimal numbers of measurement and RF chains to provide this recovery, with high probability. We discuss their applications to common variants of the hybrid architecture. By leveraging the inherent sparsity of the received signal, our analysis reveals that a hybrid MIMO system can be " turned into" a fully digital one: the number of needed RF chains increases logarithmically with the number of antennas.

Place, publisher, year, edition, pages
IEEE, 2019
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-261067 (URN)10.1109/ICASSP.2019.8683604 (DOI)000482554008014 ()2-s2.0-85069003459 (Scopus ID)978-1-4799-8131-1 (ISBN)
Conference
44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 12-17, 2019, Brighton, ENGLAND
Note

QC 20191001

Available from: 2019-10-01 Created: 2019-10-01 Last updated: 2019-10-01Bibliographically approved
Schiessl, S., Gross, J., Skoglund, M. & Caire, G. (2019). Delay Performance of the Multiuser MISO Downlink Under Imperfect CSI and Finite-Length Coding. IEEE Journal on Selected Areas in Communications, 37(4), 765-779
Open this publication in new window or tab >>Delay Performance of the Multiuser MISO Downlink Under Imperfect CSI and Finite-Length Coding
2019 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 37, no 4, p. 765-779Article in journal (Refereed) Published
Abstract [en]

We use stochastic network calculus to investigate the delay performance of a multiuser MISO system with zero-forcing beamforming. First, we consider ideal assumptions with long codewords and perfect CSI at the transmitter, where we observe a strong channel hardening effect that results in very high reliability with respect to the maximum delay of the application. We then study the system under more realistic assumptions with imperfect CSI and finite blocklength channel coding. These effects lead to interference and to transmission errors, and we derive closed-form approximations for the resulting error probability. Compared to the ideal case, imperfect CSI and finite length coding cause massive degradations in the average transmission rate. Surprisingly, the system nevertheless maintains the same qualitative behavior as in the ideal case: as long as the average transmission rate is higher than the arrival rate, the system can still achieve very high reliability with respect to the maximum delay.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Multiple-input multiple-output (MIMO), multiuser diversity, zero-forcing beamforming (ZFBF), stochastic network calculus, imperfect CSI, finite blocklength regime
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Telecommunications
Identifiers
urn:nbn:se:kth:diva-248322 (URN)10.1109/JSAC.2019.2898759 (DOI)000461853500006 ()2-s2.0-85063288812 (Scopus ID)
Note

QC 20190409

Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-05-17Bibliographically approved
Tolli, A., Ghauch, H., Kaleva, J., Komulainen, P., Bengtsson, M., Skoglund, M., . . . Pajukoski, K. (2019). Distributed Coordinated Transmission with Forward-Backward Training for 5G Radio Access. IEEE Communications Magazine, 57(1), 58-64
Open this publication in new window or tab >>Distributed Coordinated Transmission with Forward-Backward Training for 5G Radio Access
Show others...
2019 (English)In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 57, no 1, p. 58-64Article in journal (Refereed) Published
Abstract [en]

CoMP transmission and reception have been considered in cellular networks for enabling larger coverage, improved rates, and interference mitigation. To harness the gains of coordinated beamforming, fast information exchange over a backhaul connecting the cooperating BSs is required. In practice, the bandwidth and delay limitations of the backhaul may not be able to meet such stringent demands. These impairments motivate the study of cooperative approaches based only on local CSI that require minimal or no information exchange between the BSs. To this end, several distributed approaches are introduced for CB-CoMP. The proposed methods rely on the channel reciprocity and iterative spatially precoded over-the-air pilot signaling. We elaborate how F-B training facilitates distributed CB by allowing BSs and UEs to iteratively optimize their respective transmitters/receivers based on only locally measured CSI. The trade-off due to the overhead from the F-B iterations is discussed. We also consider the challenge of dynamic TDD where the UE-UE channel knowledge cannot be acquired at the BSs by exploiting channel reciprocity. Finally, standardization activities and practical requirements for enabling the proposed F-B training schemes in 5G radio access are discussed.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-244555 (URN)10.1109/MCOM.2018.1700199 (DOI)000457640200011 ()2-s2.0-85060522227 (Scopus ID)
Note

QC 20190313

Available from: 2019-03-13 Created: 2019-03-13 Last updated: 2019-03-13Bibliographically approved
Mylonakis, M., Stavrou, P. A. & Skoglund, M. (2019). Empirical Coordination with Multiple Descriptions. In: 2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019: . Paper presented at 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019; Allerton House, Monticello; United States; 24 September 2019 through 27 September 2019 (pp. 1074-1081). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8919668.
Open this publication in new window or tab >>Empirical Coordination with Multiple Descriptions
2019 (English)In: 2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 1074-1081, article id 8919668Conference paper, Published paper (Refereed)
Abstract [en]

We extend the framework of empirical coordination to a distributed setup where for a given action by nature, multiple descriptions of the action of the decoder are available. We adopt the coding strategy applied by El Gamal and Cover in [1] to get a lower bound of the coordination region. Then, we improve this region by applying the coding scheme applied by Zhang and Berger in [2].

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-266873 (URN)10.1109/ALLERTON.2019.8919668 (DOI)2-s2.0-85077794823 (Scopus ID)9781728131511 (ISBN)
Conference
57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019; Allerton House, Monticello; United States; 24 September 2019 through 27 September 2019
Note

QC 20200124

Available from: 2020-01-24 Created: 2020-01-24 Last updated: 2020-01-24Bibliographically approved
Pitarokoilis, A. & Skoglund, M. (2019). Frequency Diversity versus Channel Training in Latency-Constrained Massive MIMO. In: 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC): . Paper presented at 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019; Cannes; France; 2 July 2019 through 5 July 2019. Institute of Electrical and Electronics Engineers (IEEE), Article ID 8815578.
Open this publication in new window or tab >>Frequency Diversity versus Channel Training in Latency-Constrained Massive MIMO
2019 (English)In: 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Institute of Electrical and Electronics Engineers (IEEE), 2019, article id 8815578Conference paper, Published paper (Refereed)
Abstract [en]

The effect of correlation between neighboring resource blocks (RBs) in the outage probability performance of OFDM-based Massive MIMO systems is investigated. An upper bound on the outage probability, which is the relevant performance metric for latency-constrained communication, of two operations that exploit this correlation structure is derived and compared with the base scenario of orthogonal communication, where the correlation is ignored. It is observed that substantial outage probability improvement can be reaped already when moderate correlation is present. Closed-form upper and lower bounds on the investigated outage probability are derived. The bounds are shown to be tight for a wide range of system parameters and can be used to draw insights on the optimal design of latency-constrained Massive MIMO systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
channel estimation, low-latency, Massive MIMO, ultra-reliable
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-262583 (URN)10.1109/SPAWC.2019.8815578 (DOI)2-s2.0-85072349037 (Scopus ID)9781538665282 (ISBN)
Conference
20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019; Cannes; France; 2 July 2019 through 5 July 2019
Note

QC 20191022

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-22Bibliographically approved
Zhou, L., Vu, M. T., Oechtering, T. J. & Skoglund, M. (2019). Fundamental Limits for Biometric Identification Systems without Privacy Leakage. In: Proceedings 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton): . Paper presented at 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 24-27 Sept. 2019. IEEE
Open this publication in new window or tab >>Fundamental Limits for Biometric Identification Systems without Privacy Leakage
2019 (English)In: Proceedings 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), IEEE, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Wewithout privacy leakage. Privacy-preserving biometric identifi- cation systems that involve helper data, secret keys and private keys are considered. The helper data are stored in a public database and can be used to support the user identification. The secret key is either stored in an encrypted database or handed to the user, which can be used for authentication. Since the helper data are public and releasing the biometric information invokes privacy issues, the public helper data can only leak a negligible amount of biometric information. To achieve this, we use private keys to mask the helper data such that the public helper data contain as little as possible information about the biometrics. Moreover, a two-stage extension is also studied, where the clustering method is used such that the search complexity in the identification phase can be reduced. identification

Place, publisher, year, edition, pages
IEEE, 2019
National Category
Telecommunications
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-271127 (URN)10.1109/ALLERTON.2019.8919895 (DOI)2-s2.0-85077789237 (Scopus ID)978-1-7281-3151-1 (ISBN)978-1-7281-3152-8 (ISBN)
Conference
2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 24-27 Sept. 2019
Funder
Swedish Research Council, 2016-03853
Note

QC 20200318

Available from: 2020-03-18 Created: 2020-03-18 Last updated: 2020-03-18Bibliographically approved
Vu, M. T., Oechtering, T. J. & Skoglund, M. (2019). Hierarchical Identification with Pre-processing. IEEE Transactions on Information Theory, 66(1), 82-113
Open this publication in new window or tab >>Hierarchical Identification with Pre-processing
2019 (English)In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 66, no 1, p. 82-113Article in journal (Refereed) Published
Abstract [en]

We study a two-stage identification problem with pre-processing to enable efficient data retrieval and reconstruc- tion. In the enrollment phase, users’ data are stored into the database in two layers. In the identification phase an observer obtains an observation, which originates from an unknown user in the enrolled database through a memoryless channel. The observation is sent for processing in two stages. In the first stage, the observation is pre-processed, and the result is then used in combination with the stored first layer information in the database to output a list of compatible users to the second stage. Then the second step uses the information of users contained in the list from both layers and the original observation sequence to return the exact user identity and a corresponding reconstruction sequence. The rate-distortion regions are characterized for both discrete and Gaussian scenarios. Specifically, for a fixed list size and distortion level, the compression-identification trade-off in the Gaussian scenario results in three different operating cases characterized by three auxiliary functions. While the choice of the auxiliary random variable for the first layer information is essentially unchanged when the identification rate is varied, the second one is selected based on the dominant function within those three. Due to the presence of a mixture of discrete and continuous random variables, the proof for the Gaussian case is highly non-trivial, which makes a careful measure theoretic analysis necessary. In addition, we study a connection of the previous setting to a two observer identification and a related problem with a lower bound for the list size, where the latter is motivated from privacy concerns.

Place, publisher, year, edition, pages
IEEE, 2019
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-271121 (URN)10.1109/TIT.2019.2948848 (DOI)000505566100004 ()2-s2.0-85077234904 (Scopus ID)
Funder
Swedish Research Council, 2016-03853
Note

QC 20191114. QC 20200318

Available from: 2020-03-18 Created: 2020-03-18 Last updated: 2020-03-18Bibliographically approved
Nekouei, E., Tanaka, T., Skoglund, M. & Johansson, K. H. (2019). Information-theoretic approaches to privacy in estimation and control. Annual Reviews in Control, 47, 412-422
Open this publication in new window or tab >>Information-theoretic approaches to privacy in estimation and control
2019 (English)In: Annual Reviews in Control, ISSN 1367-5788, E-ISSN 1872-9088, Vol. 47, p. 412-422Article, review/survey (Refereed) Published
Abstract [en]

Network control systems (NCSs) heavily rely on information and communication technologies for sharing information between sensors and controllers as well as controllers and actuators. When estimation, control or actuation tasks in a NCS are performed by an untrusted party, sharing information might result in the leakage of private information. The current paper reviews some of the recent results on the privacy-aware decision-making problems in NCSs. In particular, we focus on static and dynamic decision-making problems wherein privacy is measured using information-theoretic notions. We also review the applications of these problems in smart buildings and smart grids. 

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD, 2019
Keywords
Privacy, Information theory, Networked control systems
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-255503 (URN)10.1016/j.arcontrol.2019.04.006 (DOI)000474680200028 ()2-s2.0-85064542337 (Scopus ID)
Note

QC 20190926

Available from: 2019-09-26 Created: 2019-09-26 Last updated: 2019-09-26Bibliographically approved
Shokri-Ghadikolaei, H., Ghauch, H., Fischione, C. & Skoglund, M. (2019). Learning and Data Selection in Big Datasets. In: Proceedings of the 36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019.: . Paper presented at 36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019..
Open this publication in new window or tab >>Learning and Data Selection in Big Datasets
2019 (English)In: Proceedings of the 36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019., 2019Conference paper, Published paper (Refereed)
Abstract [en]

Finding a dataset of minimal cardinality to characterize the optimal parameters of a model is of paramount importance in machine learning and distributed optimization over a network. This paper investigates the compressibility of large datasets. More specifically, we propose a framework that jointly learns the input-output mapping as well as the most representative samples of the dataset (sufficient dataset). Our analytical results show that the cardinality of the sufficient dataset increases sub-linearly with respect to the original dataset size. Numerical evaluations of real datasets reveal a large compressibility, up to 95%, without a noticeable drop in the learnability performance, measured by the generalization error.

Keywords
machine learning, optimization, non-convex, data compression
National Category
Computer Sciences
Research subject
Applied and Computational Mathematics, Optimization and Systems Theory; Information and Communication Technology; Computer Science
Identifiers
urn:nbn:se:kth:diva-260389 (URN)
Conference
36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019.
Funder
Swedish Research Council
Note

QC 20191008

Available from: 2019-09-29 Created: 2019-09-29 Last updated: 2019-10-08Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-7926-5081

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