Planning of EM Skins for Improved Quality-of-Service in Urban Areas

The optimal planning of electromagnetic skins (EMSs) installed on the building facades to enhance the received signal strength, thus the wireless coverage and/or the quality-ofservice (QoS) in large-scale urban areas, is addressed. More specifically, a novel instance of the System-by-Design (SbD) paradigm is proposed towards the implementation of a smart electromagnetic environment (SEME) where low-cost passive static reflective skins are deployed to enhance the level of the power received within selected regions-of-interest (RoIs). Thanks to the ad-hoc customization of the SbD functional blocks, which includes the exploitation of a digital twin (DT) for the accurate yet fast assessment of the wireless coverage condition, effective solutions are yielded. Numerical results, dealing with realworld test-beds, are shown to assess the capabilities, the potentialities, and the current limitations of the proposed EMSs planning strategy.

[1]  Andy J. Keane,et al.  Engineering Design via Surrogate Modelling - A Practical Guide , 2008 .

[2]  Dimitris E. Anagnostou,et al.  Analysis and Design of a 45 $^{\circ}$ Slant-Polarized Omnidirectional Antenna , 2014, IEEE Transactions on Antennas and Propagation.

[3]  Marco Salucci,et al.  On the Design of Complex EM Devices and Systems Through the System-by-Design Paradigm: A Framework for Dealing With the Computational Complexity , 2021, IEEE Transactions on Antennas and Propagation.

[4]  Paolo Rocca,et al.  Holographic Smart EM Skins for Advanced Beam Power Shaping in Next Generation Wireless Environments , 2021, IEEE Journal on Multiscale and Multiphysics Computational Techniques.

[5]  Sergei A. Tretyakov,et al.  On the Integration of Reconfigurable Intelligent Surfaces in Real-World Environments: A Convenient Approach for Estimation Reflection and Transmission , 2021, IEEE Antennas and Propagation Magazine.

[6]  Mohamed-Slim Alouini,et al.  Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead , 2020, ArXiv.

[7]  P. Rocca,et al.  Evolutionary optimization as applied to inverse scattering problems , 2009 .

[8]  Sotirios K Goudos,et al.  Emerging Evolutionary Algorithms for Antennas and Wireless Communications , 2022 .

[9]  Andrea Alù,et al.  Dynamic Beam Steering With Reconfigurable Metagratings , 2020, IEEE Transactions on Antennas and Propagation.

[10]  F. Bilotti,et al.  Design of In-phase and Quadrature Two Paths Space-Time-Modulated Metasurfaces , 2021, IEEE Transactions on Antennas and Propagation.

[11]  P. Rocca,et al.  Differential Evolution as Applied to Electromagnetics , 2011, IEEE Antennas and Propagation Magazine.

[12]  Linglong Dai,et al.  Active Reconfigurable Intelligent Surface: Fully-Connected or Sub-Connected? , 2022, IEEE Communications Letters.

[13]  Alessandro Toscano,et al.  Controlling Scattering and Absorption With Metamaterial Covers , 2014, IEEE Transactions on Antennas and Propagation.

[14]  Marco Di Renzo,et al.  On the Path-Loss of Reconfigurable Intelligent Surfaces: An Approach Based on Green’s Theorem Applied to Vector Fields , 2020, IEEE Transactions on Communications.

[15]  X. Lucas Travassos,et al.  Ground Penetrating Radar , 2008 .

[16]  Ahmed Alkhateeb,et al.  Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment , 2021, IEEE Open Journal of the Communications Society.

[17]  Mohamed-Slim Alouini,et al.  Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come , 2019, EURASIP Journal on Wireless Communications and Networking.

[18]  Changsheng You,et al.  Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial , 2020, IEEE Transactions on Communications.

[19]  Giacomo Oliveri,et al.  System-by-Design Paradigm-Based Synthesis of Complex Systems: The Case of Spline-Contoured 3D Radomes , 2021, IEEE Antennas and Propagation Magazine.

[20]  Peter J. Roberts,et al.  Accessed from , 2022 .

[21]  Orestis Georgiou,et al.  Wireless Fingerprinting Localization in Smart Environments Using Reconfigurable Intelligent Surfaces , 2021, IEEE Access.

[22]  Donglin Su,et al.  Design, Analysis, and Experiment on High-Performance Orbital Angular Momentum Beam Based on 1-Bit Programmable Metasurface , 2021, IEEE Access.

[23]  Samuel Y. Liao Measurements and Computations of Electric Field Intensity and Power Density , 1977, IEEE Transactions on Instrumentation and Measurement.

[24]  Mohamed-Slim Alouini,et al.  Wireless Communications Through Reconfigurable Intelligent Surfaces , 2019, IEEE Access.

[25]  Xiaohu You,et al.  Reconfigurable Intelligent Surfaces for 6G Systems: Principles, Applications, and Research Directions , 2021, IEEE Communications Magazine.

[26]  Ming Ding,et al.  Optimal Base Station Antenna Downtilt in Downlink Cellular Networks , 2018, IEEE Transactions on Wireless Communications.

[27]  Andrea Massa,et al.  A New Meta-Paradigm for the Synthesis of Antenna Arrays for Future Wireless Communications , 2019, IEEE Transactions on Antennas and Propagation.

[28]  Fu Liu,et al.  A multi-functional reconfigurable metasurface: Electromagnetic design accounting for fabrication aspects , 2020 .

[29]  Maokun Li,et al.  Design and Measurement of a Reconfigurable Transmitarray Antenna With Compact Varactor-Based Phase Shifters , 2021, IEEE Antennas and Wireless Propagation Letters.

[30]  Marco Di Renzo,et al.  End-to-End Mutual Coupling Aware Communication Model for Reconfigurable Intelligent Surfaces: An Electromagnetic-Compliant Approach Based on Mutual Impedances , 2020, IEEE Wireless Communications Letters.

[31]  Alessio Zappone,et al.  Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends , 2020, IEEE Wireless Communications.

[32]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[33]  Fan Yang,et al.  A 1-Bit Multipolarization Reflectarray Element for Reconfigurable Large-Aperture Antennas , 2017, IEEE Antennas and Wireless Propagation Letters.

[34]  Chau Yuen,et al.  Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication , 2018, IEEE Transactions on Wireless Communications.

[35]  R. Bansal,et al.  Antenna theory; analysis and design , 1984, Proceedings of the IEEE.

[36]  H. Vincent Poor,et al.  Ultrareliable and Low-Latency Wireless Communication: Tail, Risk, and Scale , 2018, Proceedings of the IEEE.

[37]  Maokun Li,et al.  A programmable metasurface with dynamic polarization, scattering and focusing control , 2016, Scientific Reports.

[38]  Donald R. Jones,et al.  Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..

[39]  Paolo Rocca,et al.  Learning-by-examples techniques as applied to electromagnetics , 2018 .

[40]  Atef Z. Elsherbeni,et al.  Beam-Scanning Reflectarray Antennas: A technical overview and state of the art. , 2015, IEEE Antennas and Propagation Magazine.

[41]  Jian Yi Zhou,et al.  The Role of Millimeter-Wave Technologies in 5G/6G Wireless Communications , 2021, IEEE Journal of Microwaves.

[42]  Emil Björnson,et al.  Reconfigurable Intelligent Surfaces: Three Myths and Two Critical Questions , 2020, IEEE Communications Magazine.

[43]  Paolo Rocca,et al.  Designing Smart Electromagnetic Environments for Next-Generation Wireless Communications , 2021, Telecom.