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Editorial

Information Theoretic Methods for Future Communication Systems

1
Information Coding Division, Linköping University, 58183 Linköping, Sweden
2
Chair of Information Theory and Machine Learning, Technische Universität Dresden, 01062 Dresden, Germany
3
BMBF Research Hub 6G-Life, Technische Universität Dresden, 01062 Dresden, Germany
4
Lehrstuhl für Theoretische Informationstechnik, TUM School of Computation, Information and Technology, Technical University of Munich, 80333 Munich, Germany
5
CASA: Cyber Security in the Age of Large-Scale Adversaries Exzellenzcluster, Ruhr-Universität Bochum, 44780 Bochum, Germany
6
BMBF Research Hub 6G-Life, Technical University of Munich, 80333 Munich, Germany
7
Munich Center for Quantum Science and Technology (MCQST), Schellingstr. 4, 80799 Munich, Germany
8
Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA
*
Author to whom correspondence should be addressed.
Entropy 2023, 25(3), 392; https://doi.org/10.3390/e25030392
Submission received: 13 February 2023 / Accepted: 15 February 2023 / Published: 21 February 2023
(This article belongs to the Special Issue Information Theoretic Methods for Future Communication Systems)
It is anticipated that future communication systems will involve the use of new technologies, requiring 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 to the reliability, robustness, secrecy, privacy, resiliency, and latency of such systems. The aim of this Featured Special Issue has been to develop a collection of top information and coding theoretic results that provide insight into future communication and computation systems.
The top-notch quality contributions to this Featured Special Issue consist of 11 articles, one of which is a review article. The topics touched upon include a multi-layer grant-free transmission method [1], a direct transform-coding approach that maps the delay-Doppler domain to the time domain [2], degree-of-freedom bounds for multi-antenna, multi-user, and frequency-selective interference channels with an instantaneous relay with or without coordination [3], new coded caching methods to reduce latency with user cooperation and simultaneous transmission [4], and a low-resolution downlink precoding method for multi-input single-output channels with orthogonal frequency-division multiplexing [5]. Furthermore, machine learning methods are discussed in the context of knowledge graphs for semantic communications [6] and in a review of the state-of-the-art coding methods for large-scale distributed machine learning [7]. Focusing on coding theory over rings, a new weight that extends the traditional Hamming weight used for algebraic structures is proposed and its properties are analyzed in [8]. Moreover, security aspects for future communication and computation systems are considered to analyze Gaussian wiretap channels with a jammer that overhears the transmissions [9], to propose new polynomial codes that enable straggler-tolerant secure matrix multiplication [10], and to illustrate the private-key rate regimes observed when reconstructing source sequences at another node with side information under privacy and security constraints [11]. It is expected that these contributions will have a significant impact on the applications of information and coding theory to future communication and computation systems.

Acknowledgments

The Guest Editors are grateful to all authors, anonymous reviewers, and the Entropy Editors for their great contributions to this Featured Special Issue. Our work was partially supported by the German Federal Ministry of Education and Research (BMBF) within the national initiative on 6G Communication Systems through the research hub 6G-life under Grants 16KISK001K and 16KISK002, which motivated and greatly assisted the Guest Editors in putting together this Featured Special Issue. Moreover, this Featured Special Issue was also supported by the ZENITH Research and Career Development Fund, ELLIIT funding endowed by the Swedish government, and U.S. National Science Foundation (NSF) Grant with no. CCF-1908308.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Zohdy, M.; Tajer, A.; Shamai, S. Broadcast Approach to Uplink NOMA: Queuing Delay Analysis. Entropy 2022, 24, 1757. [Google Scholar] [CrossRef] [PubMed]
  2. Lampel, F.; Joudeh, H.; Alvarado, A.; Willems, F.M.J. Orthogonal Time Frequency Space Modulation Based on the Discrete Zak Transform. Entropy 2022, 24, 1704. [Google Scholar] [CrossRef] [PubMed]
  3. Abdollahi Bafghi, A.H.; Mirmohseni, M.; Nasiri-Kenari, M. Degrees of Freedom of a K-User Interference Channel in the Presence of an Instantaneous Relay. Entropy 2022, 24, 1078. [Google Scholar] [CrossRef] [PubMed]
  4. Huang, Z.; Chen, J.; You, X.; Ma, S.; Wu, Y. Coded Caching for Broadcast Networks with User Cooperation. Entropy 2022, 24, 1034. [Google Scholar] [CrossRef] [PubMed]
  5. Nedelcu, A.S.; Steiner, F.; Kramer, G. Low-Resolution Precoding for Multi-Antenna Downlink Channels and OFDM. Entropy 2022, 24, 504. [Google Scholar] [CrossRef] [PubMed]
  6. Jiang, S.; Liu, Y.; Zhang, Y.; Luo, P.; Cao, K.; Xiong, J.; Zhao, H.; Wei, J. Reliable Semantic Communication System Enabled by Knowledge Graph. Entropy 2022, 24, 846. [Google Scholar] [CrossRef] [PubMed]
  7. Xiao, M.; Skoglund, M. Coding for Large-Scale Distributed Machine Learning. Entropy 2022, 24, 1284. [Google Scholar] [CrossRef] [PubMed]
  8. Gassner, N.; Greferath, M.; Rosenthal, J.; Weger, V. Bounds for Coding Theory over Rings. Entropy 2022, 24, 1473. [Google Scholar] [CrossRef]
  9. Chou, R.A.; Yener, A. Gaussian Multiuser Wiretap Channels in the Presence of a Jammer-Aided Eavesdropper. Entropy 2022, 24, 1595. [Google Scholar] [CrossRef] [PubMed]
  10. Byrne, E.; Gnilke, O.W.; Kliewer, J. Straggler- and Adversary-Tolerant Secure Distributed Matrix Multiplication Using Polynomial Codes. Entropy 2023, 25, 266. [Google Scholar] [CrossRef]
  11. Günlü, O.; Schaefer, R.F.; Boche, H.; Poor, H.V. Private Key and Decoder Side Information for Secure and Private Source Coding. Entropy 2022, 24, 1716. [Google Scholar] [CrossRef] [PubMed]
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MDPI and ACS Style

Günlü, O.; Schaefer, R.F.; Boche, H.; Poor, H.V. Information Theoretic Methods for Future Communication Systems. Entropy 2023, 25, 392. https://doi.org/10.3390/e25030392

AMA Style

Günlü O, Schaefer RF, Boche H, Poor HV. Information Theoretic Methods for Future Communication Systems. Entropy. 2023; 25(3):392. https://doi.org/10.3390/e25030392

Chicago/Turabian Style

Günlü, Onur, Rafael F. Schaefer, Holger Boche, and H. Vincent Poor. 2023. "Information Theoretic Methods for Future Communication Systems" Entropy 25, no. 3: 392. https://doi.org/10.3390/e25030392

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