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Publications (10 of 437) Show all publications
Schiessl, S., Al-Zubaidy, H., Skoglund, M. & Gross, J. (2018). Delay Performance of Wireless Communications With Imperfect CSI and Finite-Length Coding. IEEE Transactions on Communications, 66(12), 6527-6541
Open this publication in new window or tab >>Delay Performance of Wireless Communications With Imperfect CSI and Finite-Length Coding
2018 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 66, no 12, p. 6527-6541Article in journal (Refereed) Published
Abstract [en]

With the rise of critical machine-to-machine applications, next generation wireless communication systems must meet challenging requirements with respect to latency and reliability. A key question in this context relates to channel state estimation, which allows the transmitter to adapt the code rate to the channel state. In this paper, we characterize the tradeoff between the training sequence length and data codeword length: shorter channel estimation leaves more time for the payload transmission but reduces the estimation accuracy and causes more decoding errors. Using lower coding rates can mitigate this effect, but may result in a higher backlog of data at the transmitter. In order to optimize the training sequence length and the rate adaptation scheme with respect to the delay performance, we employ queuing analysis on top of accurate models of the physical layer. We obtain an analytically tractable solution to the problem by deriving a closed-form approximation for the decoding error probability due to imperfect channel knowledge and finite-blocklength channel coding. The optimized training sequence length and rate adaptation strategy can reduce the delay violation probability by an order of magnitude, compared with suboptimal strategies that do not consider the delay constraints.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Finite blocklength regime, imperfect CSI, rate adaptation, quasi-static fading, queuing analysis
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-241008 (URN)10.1109/TCOMM.2018.2860000 (DOI)000454112200051 ()2-s2.0-85050718946 (Scopus ID)
Note

QC 20190109

Available from: 2019-01-09 Created: 2019-01-09 Last updated: 2019-01-09Bibliographically approved
Liang, X., Javid, A. M., Skoglund, M. & Chatterjee, S. (2018). DISTRIBUTED LARGE NEURAL NETWORK WITH CENTRALIZED EQUIVALENCE. In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (pp. 2976-2980). IEEE
Open this publication in new window or tab >>DISTRIBUTED LARGE NEURAL NETWORK WITH CENTRALIZED EQUIVALENCE
2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 2976-2980Conference paper, Published paper (Refereed)
Abstract [en]

In this article, we develop a distributed algorithm for learning a large neural network that is deep and wide. We consider a scenario where the training dataset is not available in a single processing node, but distributed among several nodes. We show that a recently proposed large neural network architecture called progressive learning network (PLN) can be trained in a distributed setup with centralized equivalence. That means we would get the same result if the data be available in a single node. Using a distributed convex optimization method called alternating-direction-method-of-multipliers (ADMM), we perform training of PLN in the distributed setup.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Distributed learning, neural networks, data parallelism, convex optimization
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-237152 (URN)10.1109/ICASSP.2018.8462179 (DOI)000446384603029 ()2-s2.0-85054237028 (Scopus ID)
Conference
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Note

QC 20181025

Available from: 2018-10-25 Created: 2018-10-25 Last updated: 2018-10-25Bibliographically approved
Vu, M. T., Oechtering, T. J. & Skoglund, M. (2018). Gaussian hierarchical identification with pre-processing. In: Data Compression Conference Proceedings: . Paper presented at 2018 Data Compression Conference, DCC 2018, 27 March 2018 through 30 March 2018 (pp. 277-286). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Gaussian hierarchical identification with pre-processing
2018 (English)In: Data Compression Conference Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 277-286Conference paper, Published paper (Refereed)
Abstract [en]

In this work we consider a two-stage identification problem with pre-processing where the users' data and observation are Gaussian distributed. In the first stage the processing unit returns a list of compatible users using the information from the first storage layer and the pre-processed observation. Then, the refined search is performed in the second stage where the processing unit returns the exact user's identity and a corresponding reconstruction sequence. We provide a complete rate-distortion trade-off for the Gaussian setting.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2018
Keywords
Compression, Identification system, Compaction, Digital storage, Economic and social effects, Electric distortion, Gaussian distribution, Image coding, Signal distortion, Gaussian distributed, Gaussian setting, Hierarchical identification, Pre-processing, Processing units, Rate distortion trade-off, Storage layers, Two-stage identification, Data compression
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-238076 (URN)10.1109/DCC.2018.00036 (DOI)2-s2.0-85050965248 (Scopus ID)9781538648834 (ISBN)
Conference
2018 Data Compression Conference, DCC 2018, 27 March 2018 through 30 March 2018
Note

Conference code: 138136; Export Date: 30 October 2018; Conference Paper; CODEN: DDCCF

QC 20190114

Available from: 2019-01-14 Created: 2019-01-14 Last updated: 2019-01-14Bibliographically approved
Wang, Q. & Skoglund, M. (2018). Linear symmetric private information retrieval for MDS coded distributed storage with colluding servers. In: 2017 IEEE Information Theory Workshop (ITW): . Paper presented at 2017 IEEE Information Theory Workshop, ITW 2017, 6 November 2017 through 10 November 2017 (pp. 71-75). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Linear symmetric private information retrieval for MDS coded distributed storage with colluding servers
2018 (English)In: 2017 IEEE Information Theory Workshop (ITW), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 71-75Conference paper, Published paper (Refereed)
Abstract [en]

The problem of symmetric private information retrieval (SPIR) from a coded database which is distributively stored among colluding servers is studied. Specifically, the database comprises K files, which are stored among N servers using an (N, M)-MDS storage code. A user wants to retrieve one file from the database by communicating with the N servers, without revealing the identity of the desired file to any server. Furthermore, the user shall learn nothing about the other K - 1 files in the database. In the T-colluding SPIR problem (hence called TSPIR), any T out of N servers may collude, that is, they may communicate their interactions with the user to guess the identity of the requested file. We show that for linear schemes, the information-theoretic capacity of the MDS-TSPIR problem, defined as the maximum number of information bits of the desired file retrieved per downloaded bit, equals 1 - M+T-1/N, if the servers share common randomness (unavailable at the user) with amount at least M+T-1/N-M-T+1 times the file size. Otherwise, the capacity equals zero.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
EEE International Symposium on Information Theory - Proceedings, ISSN 215-78095
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-238280 (URN)10.1109/ITW.2017.8277997 (DOI)2-s2.0-85046363054 (Scopus ID)9781509030972 (ISBN)
Conference
2017 IEEE Information Theory Workshop, ITW 2017, 6 November 2017 through 10 November 2017
Note

QC 20181121

Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2018-11-21Bibliographically approved
Bassi, G., Skoglund, M. & Piantanida, P. (2018). Lossy Communication Subject to Statistical Parameter Privacy. In: 2018 IEEE International Symposium on Information Theory (ISIT) - Proceedings: . Paper presented at 2018 IEEE International Symposium on Information Theory (ISIT) (pp. 1031-1035). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8437690.
Open this publication in new window or tab >>Lossy Communication Subject to Statistical Parameter Privacy
2018 (English)In: 2018 IEEE International Symposium on Information Theory (ISIT) - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1031-1035, article id 8437690Conference paper, Published paper (Refereed)
Abstract [en]

We investigate the problem of sharing (communi-cating) the outcomes of a memoryless source when some of its statistical parameters must be kept private. Privacy is measured in terms of the Bayesian statistical risk according to a desired loss function while the quality of the reconstruction is measured by the average per-letter distortion. We first bound -uniformly over all possible estimators- the expected risk from below. This information-theoretic bound depends on the mutual information between the parameters and the disclosed (noisy) samples. We then present an achievable scheme that guarantees an upper bound on the average distortion while keeping the risk above a desired threshold, even when the length of the sample increases.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE International Symposium on Information Theory - Proceedings, ISSN 2157-8095
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-234483 (URN)10.1109/ISIT.2018.8437690 (DOI)2-s2.0-85052431255 (Scopus ID)9781538647806 (ISBN)
Conference
2018 IEEE International Symposium on Information Theory (ISIT)
Note

QC 20180907

Available from: 2018-09-07 Created: 2018-09-07 Last updated: 2018-10-19Bibliographically approved
Ghauch, H., Kim, T., Skoglund, M. & Fischione, C. (2018). Low-overhead coordination in sub-28 millimeter-wave networks. In: IEEE International Conference on Communications: . Paper presented at 2018 IEEE International Conference on Communications, ICC 2018, 20 May 2018 through 24 May 2018. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Low-overhead coordination in sub-28 millimeter-wave networks
2018 (English)In: IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers Inc. , 2018Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present some contributions from our recent investigation. We address the open issue of interference coordination for sub-28 GHz millimeter-wave communication, by proposing fast- converging coordination algorithms, for dense multi-user multi-cell networks. We propose to optimize a lower bound on the network sum-rate, after investigating its tightness. The bound in question results in distributed optimization, requiring local information at each base station and user. We derive the optimal solution to the transmit and receive filter updates, that we dub non-homogeneous waterfilling, and show its convergence to a stationary point of the bound. We also underline a built-in mechanism to turn-off data streams with low SINR, and allocate power to high-SNR streams. This 'stream control' is a at the root of the fast-converging nature of the algorithm. Our numerical result conclude that low- overhead coordination offers large gains, for dense sub-28 GHz systems. These findings bear direct relevance to the ongoing discussions around 5G New Radio.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2018
Keywords
Difference of Log and Trace (DLT), Low-overhead coordination, Max-DLT, Nonhomogeneous Waterfilling, Sub-28 GHz Millimeter-wave, 5G mobile communication systems, Coordination algorithms, Distributed optimization, Interference co-ordination, Low overhead, Millimeter-wave communication, Multi-cell networks, Waterfilling, Millimeter waves
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-238065 (URN)10.1109/ICC.2018.8422456 (DOI)2-s2.0-85051444915 (Scopus ID)9781538631805 (ISBN)
Conference
2018 IEEE International Conference on Communications, ICC 2018, 20 May 2018 through 24 May 2018
Note

Conference code: 138282; Export Date: 30 October 2018; Conference Paper

QC 20190114

Available from: 2019-01-14 Created: 2019-01-14 Last updated: 2019-01-14Bibliographically approved
Stavrou, F., Østergaard, J. & Skoglund, M. (2018). On Zero-delay Source Coding of LTI Gauss-Markov Systems with Covariance Matrix Distortion Constraints. In: 2018 European Control Conference, ECC 2018: . Paper presented at 16th European Control Conference, ECC 2018, Limassol, Cyprus, 12 June 2018 through 15 June 2018 (pp. 3083-3088). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8550204.
Open this publication in new window or tab >>On Zero-delay Source Coding of LTI Gauss-Markov Systems with Covariance Matrix Distortion Constraints
2018 (English)In: 2018 European Control Conference, ECC 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 3083-3088, article id 8550204Conference paper, Published paper (Refereed)
Abstract [en]

We introduce a new class of zero-delay source coding problems where a vector-valued Gauss-Markov source is conveyed subject to covariance matrix distortion constraints. We address this problem by defining an information theoretic measure where we minimize mutual information subject to causality constraints and covariance matrix distortion constraints. The resulting measure serves as a lower bound to the zero-delay rate distortion function (RDF). We solve this problem by showing that it is semidefinite representable and, thus, can be computed numerically. We also show that for this new class of information measures, it is possible to have achievable rates up to a constant space-filling loss due to a vector lattice quantizer and a constant loss due to entropy coding. We corroborate our framework with illustrative simulation examples.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-241403 (URN)10.23919/ECC.2018.8550204 (DOI)2-s2.0-85059806539 (Scopus ID)9783952426982 (ISBN)
Conference
16th European Control Conference, ECC 2018, Limassol, Cyprus, 12 June 2018 through 15 June 2018
Note

QC 20190121

Available from: 2019-01-21 Created: 2019-01-21 Last updated: 2019-01-21Bibliographically approved
Cao, P., Oechtering, T. J. & Skoglund, M. (2018). Precoding Design for Massive MIMO Systems with Sub-connected Architecture and Per-antenna Power Constraints. In: : . Paper presented at The 22nd International ITG Workshop on Smart Antennas.
Open this publication in new window or tab >>Precoding Design for Massive MIMO Systems with Sub-connected Architecture and Per-antenna Power Constraints
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper provides the necessary conditions to design precoding matrices for massive MIMO systems with a sub-connected architecture, RF power constraints and per-antenna power constraints. The system is configured such that each RFchain serves a group of antennas. The necessary condition to design the digital precoder is established based on a generalized water-filling and joint sum and per-antenna optimal power allocation solution, while the analog precoder is based on a per-antenna power allocation solution only. We study the analytically most interesting case where the power constraint on the RF chain is smaller than the sum of the corresponding per-antenna power constraints. For this, the optimal power is allocated based on two properties: Each RF chain uses full power and if the optimal power allocation of the unconstraint problem violates a per-antenna power constraint then it is optimal to allocate the maximal power for that antenna.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-225420 (URN)
Conference
The 22nd International ITG Workshop on Smart Antennas
Note

QCR 20180411

Available from: 2018-04-04 Created: 2018-04-04 Last updated: 2018-04-11Bibliographically approved
Nekouei, E., Skoglund, M. & Johansson, K. H. (2018). Privacy of Information Sharing Schemes in a Cloud-based Multi-sensor Estimation Problem. In: 2018 Annual American Control Conference (ACC): . Paper presented at 2018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton ,Milwauke City Center Milwauke, United States, 27 June 2018 through 29 June 2018 (pp. 998-1002). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8431192.
Open this publication in new window or tab >>Privacy of Information Sharing Schemes in a Cloud-based Multi-sensor Estimation Problem
2018 (English)In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 998-1002, article id 8431192Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we consider a multi-sensor estimation problem wherein each sensor collects noisy information about its local process, which is only observed by that sensor, and a common process, which is simultaneously observed by all sensors. The objective is to assess the privacy level of (the local process of) each sensor while the common process is estimated using cloud computing technology. The privacy level of a sensor is defined as the conditional entropy of its local process given the shared information with the cloud. Two information sharing schemes are considered: a local scheme, and a global scheme. Under the local scheme, each sensor estimates the common process based on its measurement and transmits its estimate to a cloud. Under the global scheme, the cloud receives the sum of the sensors' measurements. It is shown that, in the local scheme, the privacy level of each sensor is always above a certain level which is characterized using Shannon's mutual information. It is also proved that this result becomes tight as the number of sensors increases. We also show that the global scheme is asymptotically private, i.e., the privacy loss of the global scheme decreases to zero at the rate of O(1/M) where M is the number of sensors.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
Proceedings of the American Control Conference, ISSN 0743-1619
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-234705 (URN)10.23919/ACC.2018.8431192 (DOI)2-s2.0-85052564006 (Scopus ID)9781538654286 (ISBN)
Conference
2018 Annual American Control Conference, ACC 2018, Wisconsin Center / Hilton ,Milwauke City Center Milwauke, United States, 27 June 2018 through 29 June 2018
Note

QC 20180910

Available from: 2018-09-10 Created: 2018-09-10 Last updated: 2018-09-10Bibliographically approved
Wang, Q. & Skoglund, M. (2018). Secure Private Information Retrieval from Colluding Databases with Eavesdroppers. In: 2018 IEEE International Symposium on Information Theory (ISIT): . Paper presented at 2018 IEEE International Symposium on Information Theory, ISIT 2018, Vail, United States, 17 June 2018 through 22 June 2018 (pp. 2456-2460). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Secure Private Information Retrieval from Colluding Databases with Eavesdroppers
2018 (English)In: 2018 IEEE International Symposium on Information Theory (ISIT), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 2456-2460Conference paper, Published paper (Refereed)
Abstract [en]

The problem of private information retrieval (PIR) is to retrieve one message out of K messages replicated at N databases, without revealing the identity of the desired message to the databases. We consider the problem of PIR with colluding databases and eavesdroppers, named ETPIR. Specifically, any T out of N databases may collude, that is, they may communicate their interactions with the user to guess the identity of the requested message. An eavesdropper is curious to know the content of the messages and can tap in on the incoming and outgoing transmissions of any E databases with the user. The databases share some common randomness unknown to the eavesdropper and the user, and use the common randomness to generate the answers, such that the eavesdropper can learn no information about the K messages. The capacity is defined as the maximum retrieval rate, i.e. the number of information bits of the desired message retrieved per downloaded bit. In our previous work [1], we found that when Egeq T, the capacity equals 1-frac E N. In this work, we focus on the case when Eleq T. We find an outer bound (converse bound) and an inner bound (achievability) on the optimal achievable rate. The gap between the derived inner and outer bounds vanishes as the number of messages K tends to infinity.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE International Symposium on Information Theory - Proceedings, ISSN 2157-8095
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-234699 (URN)10.1109/ISIT.2018.8437848 (DOI)2-s2.0-85052432049 (Scopus ID)9781538647806 (ISBN)
Conference
2018 IEEE International Symposium on Information Theory, ISIT 2018, Vail, United States, 17 June 2018 through 22 June 2018
Note

QC 20180910

Available from: 2018-09-10 Created: 2018-09-10 Last updated: 2018-09-10Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-7926-5081

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