by Marco Di Renzo, Université Paris-Saclay, CNRS, CentraleSupélec, Laboratoire des Signaux et Systèmes, 3 Rue Joliot-Curie, 91192 Gif-sur-Yvette, France,,,,,,,,,,,,,,,,AND

Marco Donald Migliore, University of Cassino and Southern Lazio, Cassino Viale dell’Università, 03043 Cassino FR, Italy

Edited by Boya Di and Alan J Weissberger

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Introduction:

The notion of communications channel capacity* as well as the methods, algorithms, and protocols to achieve it have been fundamental questions that have driven the design of wireless communications and will continue to do so.

*  Channel capacity is the highest rate at which communications can be made with only a small number of transmission errors.

Communication and information are inherently physical phenomena.  Most of the literature, however, abstracts the physics of wave propagation, often treating the generation, transmission, and manipulation of electromagnetic waves as pure mathematical operators.

While mathematical abstractions and engineering approximations are necessary to design advanced or complex communications systems and to gain so-called “engineering insights,” much is lost in understanding the true and physically consistent fundamental limits of wireless communications.  The disciplines of information and communications theory, wave propagation, and signal processing are all inter-related and are consistent with the fundamental laws of physics and electromagnetism [1].

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Editor’s Note:  

Electromagnetic field theory provides the physics of radio communications, while information theory approaches the problem from a purely mathematical point of view. While there is a law of conservation of energy in physics, there is no such law in information theory. In information theory, when reference is made (as it frequently is) to terms like energy, power, noise, or antennas, it is by no means guaranteed that their use is consistent with the physics of the communication system.

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Emerging communication paradigms and technologies are pushing the boundaries of wave and information manipulation far beyond what was thinkable a few years ago. Among the technologies under evaluation for being integrated in future telecommunication standards, Reconfigurable Intelligent Surfaces (RIS) [2] have been under intense research during the last few years. It is interesting to note that these two technologies put forth a vision of information generation and processing that is not digital-oriented anymore but is analog-oriented and entails the processing of electromagnetic waves either through the scattering objects available in the network or at the end points of communication links.

Editor’s Note: In the past few years, various evaluation and field tests have been delivered to explore the applicability of RIS in future telecommunication standards. For example, ZTE Corporation had conducted outdoor and indoor trials that the deployment of RIS can increase the RSRP by 15 to 35 dB depending on the detail test setup in 2022. NTT Docomo has also performed communication tests based on transparent dynamic meta-surfaces in 2020.

Reconfigurable Intelligent Surfaces:

The basic premise of reconfigurable intelligent surfaces (RIS) is to be able to modify the scattering from objects coated with this technology as one desires. However, modeling such a device as a simple diagonal matrix is neither capacity achieving from a pure information-theoretic standpoint, i.e., assuming that the model being utilized is correct [4], nor strictly correct from an electromagnetic standpoint [5]. Also, the use of such devices just for channel shaping is known not to be capacity achieving [6].

The relationship between information theory and the physics of wave propagation is essential.  Understanding these relationships entails a redefinition of the Physical layer in communication systems, which goes beyond the concept of manipulation of bits. The interplay between information theory and physics of wave propagation can only be captured by embedding the wave propagation into the physical layer – a concept known as the “deep physical layer” [10], where electromagnetic field processing is performed using specialized devices.

Electromagnetic Signal and Information Theory (ESIT) Explained:

In order to extend the mathematical notions of information/communication theory and statistical signal processing to incorporate the notion of physics of wave propagation, the term electromagnetic signal and information theory (ESIT) has recently emerged.

ESIT is a broad research field that is concerned with the mathematical treatment and information processing of electromagnetic fields governing the transmission and processing of messages through communication systems. One of the main objectives of ESIT is, for example, the development of communication models that are electromagnetically consistent and that overcome current assumptions in wireless communications, including considering scalar fields, assuming far-field planar wave fronts, and ignoring electromagnetic coupling, as illustrated in the following two figures:

Fig. 1 From far-field planar-wavefronts to near-field spherical wavefronts

Fig. 2 From mutual coupling-free designs to mutual coupling-aware optimization

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ESIT makes it possible to quantify the ultimate performance limits of wireless communications, by considering realistic electromagnetic models.

Fig. 3. and Fig. 4. show the great benefits of exploiting the mutual coupling at the design stage and the increased number of communication models that can be transmitted in near-field multiple antenna communication channels.

Recent results on the impact of mutual coupling and the fundamental performance limits in the near-field communications can be found in [13] and [14], respectively.

Fig. 3 ESIT: Mutual coupling aware design [11]

Fig. 4 ESIT: Multi-mode communications in line-of-sight [4]

Editor’s Note: Modelling the influence of the near-far field and coupling effects naturally builds up a bridge between the real-world practice and theoretical analysis.

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Part II to follow: “From ESIT Theory to Standardization” by ETSI

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References:

[1] M. Franceschetti. Wave Theory of Information. Cambridge University Press, 2018.
[2] M. Di Renzo et al., “Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead,” in IEEE Journal on Selected Areas in Communications, vol. 38, no. 11, pp. 2450-2525, Nov. 2020.
[3] C. Huang et al., “Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends,” in IEEE Wireless Communications, vol. 27, no. 5, pp. 118-125, October 2020.
[4] G. Bartoli et al., “Spatial Multiplexing in Near Field MIMO Channels with Reconfigurable Intelligent Surfaces”, IET Signal Processing, 2023 (https://arxiv.org/abs/2212.11057).
[5] M. Di Renzo, F. H. Danufane and S. Tretyakov, “Communication Models for Reconfigurable Intelligent Surfaces: From Surface Electromagnetics to Wireless Networks Optimization,” in Proceedings of the IEEE, vol. 110, no. 9, pp. 1164-1209, Sept. 2022.
[6] R. Karasik et al., “Adaptive Coding and Channel Shaping Through Reconfigurable Intelligent Surfaces: An Information-Theoretic Analysis,” in IEEE Transactions on Communications, vol. 69, no. 11, pp. 7320- 7334, Nov. 2021.
[7] D. Dardari and N. Decarli, “Holographic Communication Using Intelligent Surfaces”, IEEE Commun. Mag. 59(6): 35-41 (2021).
[8] M. Di Renzo, D. Dardari, and N. Decarli, “LoS MIMO-Arrays vs. LoS MIMO-Surfaces”, IEEE EuCAP 2023 (https://arxiv.org/abs/2210.08616).
[9] M. Di Renzo, V. Galdi, and G. Castaldi, “Modeling the Mutual Coupling of Reconfigurable Metasurfaces”, IEEE EuCAP 2023 (https://arxiv.org/abs/2210.08619).
[10] M. D. Migliore, “The World Beneath the Physical Layer: An Introduction to the Deep Physical Layer”, IEEE Access 9: 77106-77126 (2021).
[11] Andrea Abrardo, Davide Dardari, Marco Di Renzo, Xuewen Qian, “MIMO Interference Channels Assisted by Reconfigurable Intelligent Surfaces: Mutual Coupling Aware Sum-Rate Optimization Based on a Mutual Impedance Channel Model”, IEEE Wirel. Commun. Lett. 10(12): 2624-2628 (2021).
[12] https://portal.etsi.org/tb.aspx?tbid=900&SubTB=900#/

[13] A. Abrardo, A. Toccafondi, and M. Di Renzo, “Analysis and Optimization of Reconfigurable Intelligent Surfaces Based on -Parameters Multiport Network Theory”, arXiv:2308.16856.

[14] J. C. Ruiz-Sicilia, M. Di Renzo, M. D. Migliore, M. Debbah, and H. V. Poor, “On the Degrees of Freedom and Eigenfunctions of Line-of-Sight Holographic MIMO Communications”, arXiv:2308.08009.

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About Marco Di Renzo, PhD:

Marco Di Renzo (Fellow, IEEE) received the Laurea (cum laude) and Ph.D. degrees in electrical engineering from the University of L’Aquila, Italy, in 2003 and 2007, respectively, and the Habilitation à Diriger des Recherches (Doctor of Science) degree from University Paris-Sud (currently Paris-Saclay University), France, in 2013. Currently, he is a CNRS Research Director (Professor) and the Head of the Intelligent Physical Communications group in the Laboratory of Signals and Systems (L2S) at Paris-Saclay University – CNRS and CentraleSupelec, Paris, France. Also, he is an elected member of the L2S Board Council and a member of the L2S Management Committee. At Paris-Saclay University, he serves as the Coordinator of the Communications and Networks Research Area of the Laboratory of Excellence DigiCosme, as a Member of the Admission and Evaluation Committee of the Ph.D. School on Information and Communication Technologies, and as a Member of the Evaluation Committee of the Graduate School in Computer Science. He is a Founding Member and the Academic Vice Chair of the Industry Specification Group (ISG) on Reconfigurable Intelligent Surfaces (RIS) within the European Telecommunications Standards Institute (ETSI), where he serves as the Rapporteur for the work item on communication models, channel models, and evaluation methodologies. He is a Fellow of the IEEE, IET, and AAIA; an Ordinary Member of the European Academy of Sciences and Arts, an Ordinary Member of the Academia Europa; and a Highly Cited Researcher. Also, he holds the 2023 France-Nokia Chair of Excellence in ICT, and was a Fulbright Fellow at City University of New York, USA, a Nokia Foundation Visiting Professor, and a Royal Academy of Engineering Distinguished Visiting Fellow. His recent research awards include the 2021 EURASIP Best Paper Award, the 2022 IEEE COMSOC Outstanding Paper Award, the 2022 Michel Monpetit Prize conferred by the French Academy of Sciences, the 2023 EURASIP Best Paper Award, the 2023 IEEE ICC Best Paper Award (wireless), the 2023 IEEE COMSOC Fred W. Ellersick Prize, the 2023 IEEE COMSOC Heinrich Hertz Award, and the 2023 IEEE VTS James Evans Avant Garde Award. He served as the Editor-in-Chief of IEEE Communications Letters during the period 2019-2023, and he is now serving in the Advisory Board.

About Marco Donald Migliore, PhD.:

Marco Donald Migliore (Senior Member, IEEE) received the Laurea degree (Hons.) and the Ph.D. degree in electronic engineering from the University of Naples, Naples, Italy. He was a Visiting Professor with The University of California at San Diego, La Jolla, CA, USA, in 2007, 2008, and 2017; the University of Rennes I, Rennes, France, in 2014 and 2016; the Centria Research Center, Ylivieska, Finland, in 2017; the University of Brasilia, Brazil, in 2018; and the Harbin Technical University, China, in 2019. He was a Speaker with the Summer Research Lecture Series of the UCSD CALIT2 Advanced Network Science, in 2008. He is currently a Full Professor with the University of Cassino and Southern Lazio, Cassino, Italy, where he is also the Head of the Microwave Laboratory and the Director of studies of the ITC Courses. He is also a member of the ELEDIA@UniCAS Research Laboratory, the ICEMmB – National Interuniversity Research Center on the Interactions between Electromagnetic Fields and Biosystems, where he is the Leader of the 5G Group, the Italian Electromagnetic Society (SIEM), and the National Interuniversity Consortium for Telecommunication (CNIT). His current research interests include connections between electromagnetism and information theory, analysis, synthesis and characterization of antennas in complex environments, antennas and propagation for 5G, ad hoc wireless networks, compressed sensing as applied to electromagnetic problems, and energetic applications of microwaves. He serves as a referee for many scientific journals and has served as an Associate Editor for IEEE Transactions on Antennas and Propagation.