Special Issue "Information Theoretic Methods for Future Communication Systems"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: 16 October 2022 | Viewed by 1731

Special Issue Editors

Dr. Onur Günlü
E-Mail Website
Guest Editor
Chair of Communications Engineering and Security, University of Siegen, 57076 Siegen, Germany
Interests: information theoretic privacy and security; coding theory; private learning; secure function computation; physical layer security
Prof. Dr. Rafael F. Schaefer
E-Mail Website
Guest Editor
Chair of Communications Engineering and Security, University of Siegen, 57076 Siegen, Germany
Interests: information theory; communications; physical layer security
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Holger Boche
E-Mail Website
Guest Editor
Institute of Theoretical Information Technology, Technical University of Munich, 80333 Munich, Germany
Interests: information theory; signal processing; communication theory
Prof. Dr. H. Vincent Poor
E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA
Interests: information theory; statistical signal processing; stochastic analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is anticipated that future communication systems will involve new technologies that will require high-speed computations using large amounts of data in order to take advantage of data-driven methods for improving services and providing reliability and other benefits. In many cases, information theory can provide a fundamental understanding of the limits on reliability, robustness, secrecy, privacy, resiliency, and latency of such systems. The aim of this Special Issue is to develop a collection of top information and coding theoretic results that provide such insights for future communication systems. Topics of interest include, but are not limited to, information and coding theory for:

  • Semantic and goal-oriented communications;
  • Joint communication and sensing;
  • Provable security and privacy;
  • Machine learning for communications;
  • Distributed function computation;
  • Feedback communication systems;
  • Intelligent communication environments;
  • THz communications;
  • Identification via channels.

Reviews for this Special Issue will be handled by Entropy, but the Special Issue Editors can be contacted for questions and requests before, during, and after paper submission.

Dr. Onur Günlü
Prof. Dr. Rafael F. Schaefer
Prof. Dr. Holger Boche
Prof. Dr. H. Vincent Poor
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 submissions that pass pre-check are 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. Entropy is an international peer-reviewed open access monthly 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 1800 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

  • Shannon theory
  • future communication systems
  • optimal code constructions
  • B5G & 6G
  • IoT & IoV

Published Papers (2 papers)

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Research

Article
Reliable Semantic Communication System Enabled by Knowledge Graph
Entropy 2022, 24(6), 846; https://doi.org/10.3390/e24060846 - 20 Jun 2022
Viewed by 344
Abstract
Semantic communication is a promising technology used to overcome the challenges of large bandwidth and power requirements caused by the data explosion. Semantic representation is an important issue in semantic communication. The knowledge graph, powered by deep learning, can improve the accuracy of [...] Read more.
Semantic communication is a promising technology used to overcome the challenges of large bandwidth and power requirements caused by the data explosion. Semantic representation is an important issue in semantic communication. The knowledge graph, powered by deep learning, can improve the accuracy of semantic representation while removing semantic ambiguity. Therefore, we propose a semantic communication system based on the knowledge graph. Specifically, in our system, the transmitted sentences are converted into triplets by using the knowledge graph. Triplets can be viewed as basic semantic symbols for semantic extraction and restoration and can be sorted based on semantic importance. Moreover, the proposed communication system adaptively adjusts the transmitted contents according to channel quality and allocates more transmission resources to important triplets to enhance communication reliability. Simulation results show that the proposed system significantly enhances the reliability of the communication in the low signal-to-noise regime compared to the traditional schemes. Full article
(This article belongs to the Special Issue Information Theoretic Methods for Future Communication Systems)
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Article
Low-Resolution Precoding for Multi-Antenna Downlink Channels and OFDM
Entropy 2022, 24(4), 504; https://doi.org/10.3390/e24040504 - 04 Apr 2022
Viewed by 627
Abstract
Downlink precoding is considered for multi-path multi-input single-output channels where the base station uses orthogonal frequency-division multiplexing and low-resolution signaling. A quantized coordinate minimization (QCM) algorithm is proposed and its performance is compared to other precoding algorithms including squared infinity-norm relaxation (SQUID), multi-antenna [...] Read more.
Downlink precoding is considered for multi-path multi-input single-output channels where the base station uses orthogonal frequency-division multiplexing and low-resolution signaling. A quantized coordinate minimization (QCM) algorithm is proposed and its performance is compared to other precoding algorithms including squared infinity-norm relaxation (SQUID), multi-antenna greedy iterative quantization (MAGIQ), and maximum safety margin precoding. MAGIQ and QCM achieve the highest information rates and QCM has the lowest complexity measured in the number of multiplications. The information rates are computed for pilot-aided channel estimation and a blind detector that performs joint data and channel estimation. Bit error rates for a 5G low-density parity-check code confirm the information-theoretic calculations. Simulations with imperfect channel knowledge at the transmitter show that the performance of QCM and SQUID degrades in a similar fashion as zero-forcing precoding with high resolution quantizers. Full article
(This article belongs to the Special Issue Information Theoretic Methods for Future Communication Systems)
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