Special Issue "Communication Theory"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".

Deadline for manuscript submissions: closed (20 November 2015)

Special Issue Editors

Guest Editor
Prof. Dr. Mikael Skoglund

Communication Theory Department, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden
Website | E-Mail
Interests: information theory; communication theory; wireless communications
Guest Editor
Prof. Dr. Lars K. Rasmussen

School of Electrical Engineering, KTH Royal Institute of Technology, Sweden
Website | E-Mail
Interests: transmission strategies; wireless communications; delay-constrained applications; ad hoc wireless networks; cooperative communications; communications and control; communications and positioning; vehicular communication systems
Guest Editor
Prof. Dr. Tobias Oechtering

School of Electrical Engineering, KTH Royal Institute of Technology, Sweden
Website | E-Mail
Interests: (multi-terminal) information theory; physical layer security; (wireless) communications; statistical inference; signal processing and algorithms; networked control

Special Issue Information

Dear Colleagues,

This Special Issues focuses on theory and methods for information transmission, storage, and processing. Traditionally, the topic has concerned digital communication between one or several transmitters and receivers, and a particular focus has been placed on wireless systems. More recently, methods and tools from communication theory are also becoming crucial in trusted communication over general networks, and with modern applications to sensor and actuator networks, vehicular communications, industrial communications, and data analytics.

Prospective contributions should consider theory and methods motivated by the wide area of theory for communication and network engineering.

Interested authors are encouraged to submit previously unpublished contributions in all areas of communication theory. Topics of interest include, but are not restricted to, the following:

* Coding theory and techniques

* Interactive communication

* Communication theory for networks

* Privacy and security

* Communication for storage, computation, and analytics

* Optical communication

* Communication for networked control

* Foundations of wireless systems

* New directions in communication theory

* Communication complexity

Prof. Dr. Mikael Skoglund
Prof. Dr. Lars K. Rasmussen
Prof. Dr. Tobias Oechtering
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


Keywords

  • coding
  • networks
  • detection
  • estimation
  • capacity

Published Papers (4 papers)

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Research

Open AccessArticle Minimax Duality for MIMO Interference Networks
Information 2016, 7(2), 19; doi:10.3390/info7020019
Received: 1 November 2015 / Revised: 25 January 2016 / Accepted: 6 February 2016 / Published: 23 March 2016
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Abstract
A minimax duality for a Gaussian mutual information expression was introduced by Yu. An interesting observation is the relationship between cost constraints on the transmit covariances and noise covariances in the dual problem via Lagrangian multipliers. We introduce a minimax duality for general
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A minimax duality for a Gaussian mutual information expression was introduced by Yu. An interesting observation is the relationship between cost constraints on the transmit covariances and noise covariances in the dual problem via Lagrangian multipliers. We introduce a minimax duality for general MIMO interference networks, where noise and transmit covariances are optimized subject to linear conic constraints. We observe a fully symmetric relationship between the solutions of both networks, where the roles of the optimization variables and Lagrangian multipliers are inverted. The least favorable noise covariance itself provides a Lagrangian multiplier for the linear conic constraint on the transmit covariance in the dual network, while the transmit covariance provides a Lagrangian multiplier for the constraint on the interference plus noise covariance in the dual network. The degrees of freedom available for optimization are constituted by linear subspaces, where the orthogonal subspaces induce the constraints in the dual network. For the proof of our duality we make use of the existing polite water-filling network duality and as a by-product we are able to show that maximization problems in MIMO interference networks have a zero-duality gap for a special formulation of the dual function. Our minimax duality unifies and extends several results, including the original minimax duality and other known network dualities. New results and applications are MIMO transmission strategies that manage and handle uncertainty due to unknown inter-cell interference and information theoretic proofs concerning cooperation in networks and optimality of proper signaling. Full article
(This article belongs to the Special Issue Communication Theory)
Open AccessArticle Communication-Theoretic Model of Power Talk for a Single-Bus DC Microgrid
Information 2016, 7(1), 18; doi:10.3390/info7010018
Received: 20 November 2015 / Revised: 17 February 2016 / Accepted: 25 February 2016 / Published: 21 March 2016
Cited by 2 | PDF Full-text (868 KB) | HTML Full-text | XML Full-text
Abstract
Power talk is a method for communication among voltage control sources (VSCs) in DC microgrids (MGs), achieved through variations of the supplied power that is incurred by modulation of the parameters of the primary control. The physical medium upon which the communication channel
[...] Read more.
Power talk is a method for communication among voltage control sources (VSCs) in DC microgrids (MGs), achieved through variations of the supplied power that is incurred by modulation of the parameters of the primary control. The physical medium upon which the communication channel is established is the voltage supply level of the common MG bus. In this paper, we show how to create power talk channels in all-to-all communication scenarios and implement the signaling and detection techniques, focusing on the construction and use of the constellations or arbitrary order. The main challenge to the proposed communication method stems from random shifts of the loci of the constellation symbols, which are due to random load variations in the MG. We investigate the impact that solutions that combat the effects of random load variations by re-establishing the detection regions have on the power talk rate. Full article
(This article belongs to the Special Issue Communication Theory)
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Open AccessArticle Information Extraction Under Privacy Constraints
Information 2016, 7(1), 15; doi:10.3390/info7010015
Received: 1 November 2015 / Revised: 24 February 2016 / Accepted: 3 March 2016 / Published: 10 March 2016
Cited by 2 | PDF Full-text (457 KB) | HTML Full-text | XML Full-text
Abstract
A privacy-constrained information extraction problem is considered where for a pair of correlated discrete random variables (X,Y) governed by a given joint distribution, an agent observes Y and wants to convey to a potentially public user as much information about Y as possible
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A privacy-constrained information extraction problem is considered where for a pair of correlated discrete random variables (X,Y) governed by a given joint distribution, an agent observes Y and wants to convey to a potentially public user as much information about Y as possible while limiting the amount of information revealed about X. To this end, the so-called rate-privacy function is investigated to quantify the maximal amount of information (measured in terms of mutual information) that can be extracted from Y under a privacy constraint between X and the extracted information, where privacy is measured using either mutual information or maximal correlation. Properties of the rate-privacy function are analyzed and its information-theoretic and estimation-theoretic interpretations are presented for both the mutual information and maximal correlation privacy measures. It is also shown that the rate-privacy function admits a closed-form expression for a large family of joint distributions of (X,Y). Finally, the rate-privacy function under the mutual information privacy measure is considered for the case where (X,Y) has a joint probability density function by studying the problem where the extracted information is a uniform quantization of Y corrupted by additive Gaussian noise. The asymptotic behavior of the rate-privacy function is studied as the quantization resolution grows without bound and it is observed that not all of the properties of the rate-privacy function carry over from the discrete to the continuous case. Full article
(This article belongs to the Special Issue Communication Theory)
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Open AccessArticle Ultra-Reliable Link Adaptation for Downlink MISO Transmission in 5G Cellular Networks
Information 2016, 7(1), 14; doi:10.3390/info7010014
Received: 20 November 2015 / Revised: 23 February 2016 / Accepted: 25 February 2016 / Published: 4 March 2016
Cited by 3 | PDF Full-text (548 KB) | HTML Full-text | XML Full-text
Abstract
This paper discusses robust link adaptation for a downlink precoded multiple input single output system, for guaranteeing ultra-reliable (99.999%) transmissions to mobile users (e.g., slowly moving machines in a factory) served by a small cell network. The proposed technique compensates the effect of
[...] Read more.
This paper discusses robust link adaptation for a downlink precoded multiple input single output system, for guaranteeing ultra-reliable (99.999%) transmissions to mobile users (e.g., slowly moving machines in a factory) served by a small cell network. The proposed technique compensates the effect of inaccurate channel state information (CSI) caused by user mobility, as well as the variation of precoders in the interfering cells. Both of these impairments translate into instability of the received signal-to-noise plus interference ratios (SINRs), and may lead to CSI mispredictions and potentially erroneous transmissions. We show that, by knowing the statistics of the propagation channels and the precoders variations, it is possible to compute a backoff that guarantees robust link adaptation. The backoff value is based on the statistics of realized SINR, and is consequently used to adapt the transmissions according to current channel state. Theoretical analysis accompanied by simulation results show that the proposed approach is suitable for attaining 5G ultra-reliability targets in realistic settings. Full article
(This article belongs to the Special Issue Communication Theory)
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