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Advancements in CAD Techniques for IoT: Modeling, Optimization, Surrogate-Assisted Methods
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Advancements in CAD Techniques for IoT: Modeling, Optimization, Surrogate-Assisted Methods

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 16780

Special Issue Editor

Dr. Adrian Bekasiewicz

E-Mail Website
Guest Editor
Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gdansk, Poland
Interests: surrogate-assisted design; circuit miniaturization; compact antennas; multi-objective optimization, computer-aided design; surrogate modeling; automated design of RF circuits and antenna structures
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is a part of the ongoing technological revolution oriented towards the seamless gathering and processing of data by ubiquitous interconnected electronic devices. The reliability of IoT-based services depends on the availability of cheap radio-frequency (RF) components characterized not only by high performance, but also small dimensions and a low power consumption. The development of computer-aided design (CAD) techniques, associated with the boost of computational power over the past two decades, significantly affected the design paradigms of such components. The availability of advanced tools integrated with accurate electromagnetic (EM) solvers has led to the replacement of theory-based design methods by more versatile simulation-driven approaches. The latter stimulate the development of modern RF components that exceed the capabilities of conventional structures. However, simulation-driven design heavily relies on numerical optimization. As a consequence, its computational cost—associated with a large number of EM evaluations required to find the desired solution—is often prohibitive when complex multi-parameter structures are considered. In this context, the availability of reliable methods for the rapid design of state-of-the-art RF components for IoT applications is an important problem that remains open.

Challenges related to the design of RF structures can be addressed using advanced modeling techniques, surrogate-assisted methods, as well specialized single- and multi-objective optimization algorithms. Despite being useful for providing high-quality solutions within limited computational budgets, these tools have not received broader attention in the design of IoT components. Their introduction is considered to be of great practical importance for lowering development costs and shortening the time-to-market design cycles of IoT-based services.

The objective of this Special Issue is to report innovative methodologies for the design of IoT components that reach beyond the frontiers of the current state of the art. Review articles focused on introducing the concepts of rapid simulation-driven design are also anticipated. Topics of interest cover the design, modeling, and optimization of IoT circuits and devices, including but not limited to:

  • computer-aided design and techniques for IoT;
  • microwave circuits for IoT;
  • antenna structures for IoT;
  • on-body IoT devices;
  • energy harvesting circuits for IoT;
  • miniaturization of IoT devices and circuits;
  • modeling of IoT devices and circuits;
  • inverse design problems for IoT circuits and devices;
  • parallel computing for IoT design;
  • surrogate-assisted methods for low-cost IoT design;
  • optimization techniques for IoT;
  • multi-objective design of IoT components;
  • combination of analytical and numerical modeling of IoT;
  • measurement techniques for IoT;
  • effects of wearable IoT devices on human body;
  • failure identification in IoT systems;
  • evolution of IoT components topologies.

Dr. Adrian Bekasiewicz
Guest Editor

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. Sensors is an international peer-reviewed open access semimonthly 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

  • multi-objective design
  • surrogate-assisted design
  • passive microwave circuits
  • antennas
  • internet of things
  • energy harvesting
  • circuit miniaturization
  • computer-aided design
  • optimization algorithms
  • automated design of RF circuits

Published Papers (5 papers)

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Research

25 pages, 4279 KiB  
Article
Low-Cost Automated Design of Compact Branch-Line Couplers
by Adrian Bekasiewicz
Sensors 2020, 20(12), 3562; https://doi.org/10.3390/s20123562 - 23 Jun 2020
Cited by 4 | Viewed by 2198
Abstract
Branch-line couplers (BLCs) are important components of wireless communication systems. Conventional BLCs are often characterized by large footprints which make miniaturization an important pre-requisite for their application in modern devices. State-of-the-art approaches to design compact BLCs are largely based on the use of [...] Read more.
Branch-line couplers (BLCs) are important components of wireless communication systems. Conventional BLCs are often characterized by large footprints which make miniaturization an important pre-requisite for their application in modern devices. State-of-the-art approaches to design compact BLCs are largely based on the use of high-permittivity substrates and multi-layer topologies. Alternative methods involve replacement of transmission-line sections of the circuit, with their composite counterparts, referred to as compact cells (CCs). Due to the efficient use of available space, CC-based couplers are often characterized by small footprints. The design of compact BLCs is normally conducted based on engineering experience. The process is laborious and requires many adjustments of topology followed by manual or, semi-automatic tuning of design parameters. In this work, a framework for low-cost automated design of compact BLCs using pre-defined CCs is proposed. The low cost of the presented design technique is ensured using equivalent-circuit models, space mapping correction methods, and trust-region-based local optimization algorithms. The performance of the framework is demonstrated based on three examples, concerning the design of unequal-power split coupler, comparison of automatically generated compact BLCs, as well as rapid re-design of the coupler for different substrates. Furthermore, the approach has been benchmarked against the state-of-the-art methods for low-cost design of circuits. Full article
(This article belongs to the Special Issue Advancements in CAD Techniques for IoT: Modeling, Optimization, Surrogate-Assisted Methods)
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15 pages, 1309 KiB  
Article
Numerical Optimization of a Fully Cross-Coupled Rectifier Circuit for Wireless Passive Ultra Low Power Sensor Nodes
by Dominik Mair, Manuel Ferdik, Christof Happ, Michael Renzler and Thomas Ussmueller
Sensors 2019, 19(20), 4527; https://doi.org/10.3390/s19204527 - 18 Oct 2019
Cited by 9 | Viewed by 4183
Abstract
In the context of the Internet of Things, billions of devices—especially sensors—will be linked together in the next few years. A core component of wireless passive sensor nodes is the rectifier, which has to provide the circuit with sufficient operating voltage. In these [...] Read more.
In the context of the Internet of Things, billions of devices—especially sensors—will be linked together in the next few years. A core component of wireless passive sensor nodes is the rectifier, which has to provide the circuit with sufficient operating voltage. In these devices, the rectifier has to be as energy efficient as possible in order to guarantee an optimal operation. Therefore, a numerical optimization scheme is proposed in this paper, which is able to find a unique optimal solution for an integrated Complementary Metal-Oxide-Semiconductor (CMOS) rectifier circuit with Self-Vth-Cancellation (SVC). An exploration of the parameter space is carried out in order to generate a meaningful target function for enhancing the rectified power for a fixed communication distance. In this paper, a mean conversion efficiency is introduced, which is a more valid target function for optimization than the Voltage Conversion Efficiency (VCE) and the commonly used Power Conversion Efficiency (PCE) and is defined as the arithmetic mean between PCE and VCE. Various trade-offs between output voltage, PCE, VCE and MCE are shown, which provide valuable information for low power rectifier designs. With the proposed method, a rectifier in a low power 55 nm process from Globalfoundries (GF55LPe) is optimized and simulated at −30 dBm input power. A mean PCE of 63.33% and a mean VCE of 63.40% is achieved. Full article
(This article belongs to the Special Issue Advancements in CAD Techniques for IoT: Modeling, Optimization, Surrogate-Assisted Methods)
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16 pages, 4517 KiB  
Article
A Generalized SDP Multi-Objective Optimization Method for EM-Based Microwave Device Design
by Ying Liu, Qingsha S. Cheng and Slawomir Koziel
Sensors 2019, 19(14), 3065; https://doi.org/10.3390/s19143065 - 11 Jul 2019
Cited by 10 | Viewed by 2513
Abstract
In this article, a generalized sequential domain patching (GSDP) method for efficient multi-objective optimization based on electromagnetics (EM) simulation is proposed. The GSDP method allowing fast searching for Pareto fronts for two and three objectives is elaborated in detail in this paper. The [...] Read more.
In this article, a generalized sequential domain patching (GSDP) method for efficient multi-objective optimization based on electromagnetics (EM) simulation is proposed. The GSDP method allowing fast searching for Pareto fronts for two and three objectives is elaborated in detail in this paper. The GSDP method is compared with the NSGA-II method using multi-objective problems in the DTLZ series, and the results show the GSDP method saved computational cost by more than 85% compared to NSGA-II method. A diversity comparison indicator (DCI) is used to evaluate approximate Pareto fronts. The comparison results show the diversity performance of GSDP is better than that of NSGA-II in most cases. We demonstrate the proposed GSDP method using a practical multi-objective design example of EM-based UWB antenna for IoT applications. Full article
(This article belongs to the Special Issue Advancements in CAD Techniques for IoT: Modeling, Optimization, Surrogate-Assisted Methods)
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13 pages, 3170 KiB  
Article
Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization
by Yiran Song, Qingsha S. Cheng and Slawomir Koziel
Sensors 2019, 19(13), 3023; https://doi.org/10.3390/s19133023 - 09 Jul 2019
Cited by 17 | Viewed by 3394
Abstract
In order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of [...] Read more.
In order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation to construct a series of local surrogate models. In the optimization process, local region modeling and optimization are performed iteratively. A judgment factor is introduced to provide information for local region size update. The last local surrogate model is refined by space mapping techniques to obtain the optimal design with high accuracy. The operation and efficiency of the approach are demonstrated through design of a bandpass filter and a compact ultra-wide-band (UWB) multiple-in multiple-out (MIMO) antenna. The response of the optimized design of the fine model meet the design specification. The proposed method not only has better convergence compared to an existing local surrogate method, but also reduces the computational cost substantially. Full article
(This article belongs to the Special Issue Advancements in CAD Techniques for IoT: Modeling, Optimization, Surrogate-Assisted Methods)
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12 pages, 895 KiB  
Article
Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
by Slawomir Koziel and Anna Pietrenko-Dabrowska
Sensors 2019, 19(8), 1806; https://doi.org/10.3390/s19081806 - 15 Apr 2019
Cited by 34 | Viewed by 3627
Abstract
Design of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of [...] Read more.
Design of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that need tuning. Conventional optimization procedures are typically too expensive when the antenna is evaluated using high-fidelity electromagnetic (EM) analysis, otherwise required to ensure accuracy. This paper proposes a novel surrogate-assisted optimization algorithm for computationally efficient design optimization of antenna structures. In the paper, the optimization of antenna input characteristic is presented, specifically, minimization of the antenna reflection coefficient in a given bandwidth. Our methodology involves variable-fidelity EM simulations as well as a dedicated procedure to reduce the cost of estimating the antenna response gradients. The latter is based on monitoring the variations of the antenna response sensitivities along the optimization path. The procedure suppresses the finite-differentiation-based sensitivity updates for variables that exhibit stable gradient behavior. The proposed algorithm is validated using three compact wideband antennas and demonstrated to outperform both the conventional trust region algorithm and the pattern search procedure, as well as surrogate-based procedures while retaining acceptable design quality. Full article
(This article belongs to the Special Issue Advancements in CAD Techniques for IoT: Modeling, Optimization, Surrogate-Assisted Methods)
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