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Selected Papers from the 20th SBMO/IEEE MTT-S International Microwave and...
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Selected Papers from the 20th SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC 2023)

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "E：Engineering and Technology".

Deadline for manuscript submissions: closed (10 March 2024) | Viewed by 5462

Special Issue Editors

Dr. Ignacio Llamas-Garro

E-Mail Website
Guest Editor
Centre Tecnològic de Telecomunicacions de Catalunya, CTTC/CERCA, 08860 Castelldefels, Spain
Interests: micromachined sensors; MEMS; reconfigurable devices; additive manufacturing; electronics and communications engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marcos Tavares De Melo

E-Mail Website
Guest Editor
Departamento de Eletrônica e Sistemas, Universidade Federal de Pernambuco (UFPE), Recife 50740-550, Brazil
Interests: micromachined sensing technology for gas and liquids; microwave wireless communication device

Special Issue Information

Dear Colleagues,

The SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference is a biennial forum on microwave, millimeter wave, terahertz and photonics methods and techniques for both science and engineering, sponsored by the Brazilian Microwave and Optoelectronics Society (SBMO) and the IEEE Microwave Theory and Techniques Society of the Institute of Electrical and Electronics Engineers (IEEE MTT-S).

IMOC 2023 (https://www.events.sbmo.org.br/imoc2023/home) will provide a major international forum for exchanging information on research and development in the theoretical and experimental fields of microwaves and optoelectronics, including millimeter, terahertz, antennas, propagation, wireless communication, fiber optics and photonics networks. In its twentieth edition, the conference will be held in Castelldefels, Barcelona, near Barcelona Center, from November 5th to 9th 2023.

This Special Issue in Micromachines contains extended papers from the 20th SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC 2023).

Topics of interest include, but are not limited to, the following:

  • Antennas and radio propagation;
  • Artificial and smart electromagnetic materials;
  • Biological effects of electromagnetic radiation;
  • Electromagnetic compatibility and interference;
  • Microwave and mmWave components, circuits and devices;
  • Microwave and optical measurements;
  • Microwave and optical industrial applications;
  • Microwave and optical sensors;
  • Microwave systems;
  • Microwave, mmWave and terahertz devices and applications;
  • Optical communication systems and subsystems;
  • Optical components, fibers, and devices;
  • Optical networks, including control and management aspects;
  • Advanced photonic networks and enabling technologies;
  • Data center networks and technologies;
  • Quantum technologies and security in optical communications/networks;
  • Optical and wireless convergence, systems and networks in support of 6G;
  • Radio over fiber and microwave photonics;
  • Electromagnetic field theory and numerical techniques;
  • Active and non-linear microwave circuits;
  • New electromagnetics applications;
  • Smart antennas, digital beam-forming and MIMO antennas;
  • Applications of artificial intelligence in microwaves and optoelectronics.

Dr. Ignacio Llamas-Garro
Prof. Dr. Marcos Tavares De Melo
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. Micromachines 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 2600 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

  • microwave components and devices
  • optical components and devices
  • optoelectronics
  • terahertz
  • photonics
  • applications

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Published Papers (2 papers)

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13 pages, 3028 KiB  
Article
Integrative BNN-LHS Surrogate Modeling and Thermo-Mechanical-EM Analysis for Enhanced Characterization of High-Frequency Low-Pass Filters in COMSOL
by Jorge Davalos-Guzman, Jose L. Chavez-Hurtado and Zabdiel Brito-Brito
Micromachines 2024, 15(5), 647; https://doi.org/10.3390/mi15050647 - 13 May 2024
Viewed by 1407
Abstract
This paper pioneers a novel approach in electromagnetic (EM) system analysis by synergistically combining Bayesian Neural Networks (BNNs) informed by Latin Hypercube Sampling (LHS) with advanced thermal–mechanical surrogate modeling within COMSOL simulations for high-frequency low-pass filter modeling. Our methodology transcends traditional EM characterization [...] Read more.
This paper pioneers a novel approach in electromagnetic (EM) system analysis by synergistically combining Bayesian Neural Networks (BNNs) informed by Latin Hypercube Sampling (LHS) with advanced thermal–mechanical surrogate modeling within COMSOL simulations for high-frequency low-pass filter modeling. Our methodology transcends traditional EM characterization by integrating physical dimension variability, thermal effects, mechanical deformation, and real-world operational conditions, thereby achieving a significant leap in predictive modeling fidelity. Through rigorous evaluation using Mean Squared Error (MSE), Maximum Learning Error (MLE), and Maximum Test Error (MTE) metrics, as well as comprehensive validation on unseen data, the model’s robustness and generalization capability is demonstrated. This research challenges conventional methods, offering a nuanced understanding of multiphysical phenomena to enhance reliability and resilience in electronic component design and optimization. The integration of thermal variables alongside dimensional parameters marks a novel paradigm in filter performance analysis, significantly improving simulation accuracy. Our findings not only contribute to the body of knowledge in EM diagnostics and complex-environment analysis but also pave the way for future investigations into the fusion of machine learning with computational physics, promising transformative impacts across various applications, from telecommunications to medical devices. Full article
(This article belongs to the Special Issue Selected Papers from the 20th SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC 2023))
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16 pages, 5291 KiB  
Article
ANN-Based LiDAR Positioning System for B5G
by Egidio Raimundo Neto, Matheus Ferreira Silva, Tomás P. V. Andrade and Arismar Cerqueira Sodré Junior
Micromachines 2024, 15(5), 620; https://doi.org/10.3390/mi15050620 - 4 May 2024
Cited by 1 | Viewed by 1389
Abstract
This work reports the development of an efficient and precise indoor positioning system utilizing two-dimensional (2D) light detection and ranging (LiDAR) technology, aiming to address the challenging sensing and positioning requirements of the beyond fifth-generation (B5G) mobile networks. The core of this work [...] Read more.
This work reports the development of an efficient and precise indoor positioning system utilizing two-dimensional (2D) light detection and ranging (LiDAR) technology, aiming to address the challenging sensing and positioning requirements of the beyond fifth-generation (B5G) mobile networks. The core of this work is the implementation of a 2D-LiDAR system enhanced by an artificial neural network (ANN), chosen due to its robustness against electromagnetic interference and higher accuracy over traditional radiofrequency signal-based methods. The proposed system uses 2D-LiDAR sensors for data acquisition and digital filters for signal improvement. Moreover, a camera and an image-processing algorithm are used to automate the labeling of samples that will be used to train the ANN by means of indicating the regions where the pedestrians are positioned. This accurate positioning information is essential for the optimization of B5G network operation, including the control of antenna arrays and reconfigurable intelligent surfaces (RIS). The experimental validation demonstrates the efficiency of mapping pedestrian locations with a precision of up to 98.787%, accuracy of 95.25%, recall of 98.537%, and an F1 score of 98.571%. These results show that the proposed system has the potential to solve the problem of sensing and positioning in indoor environments with high reliability and accuracy. Full article
(This article belongs to the Special Issue Selected Papers from the 20th SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC 2023))
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