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Publisher's version (útgefin grein), Multiple-input multiple-output (MIMO) antennas are considered to be the key components of fifth generation (5G) mobile communications. One of the challenges pertinent to the design of highly integrated MIMO structures is to minimize the mutual coupling among the antenna elements. The latter arises from two sources, the coupling in the free space and the coupling currents propagating on a ground plane. In this paper, an array of H-shaped parasitic patches is proposed as a decoupling structure for compact MIMO antennas to reduce propagation of the coupling currents on a shared ground plane. The proposed decoupling structure is generic, and it can be applied to different antenna configurations as demonstrated in the work. Furthermore, it is employed to develop a new high-performance compact dual-band MIMO structure featuring acceptable level of element coupling at both operating frequencies. The design is validated both numerically and experimentally. The mutual coupling levels are less than -17 dB and -20 dB, with the total efficiency of 89% and 90%, and the realized gain of 6.6 dB and 7 dB at the two resonant frequencies of 5 GHz and 6 GHz, respectively. Topological complexity of the compact MIMO systems featuring elaborated decoupling structures, a large number of geometry parameters, as well as the necessity of handling multiple performance figures, constitute the major challenges of antenna design, in particular, its re-design for various specifications. To alleviate these difficulties, the paper also provides a procedure for rapid geometry scaling of the dual-band MIMO antennas. Our approach is based on inverse surrogate modeling methods, and results in numerically-derived expressions that enable a precise control over the operating antenna bands within broad ranges thereof (from 4 GHz to 8 GHz for the lower band, and from 1.1 to 1.3 ratio of the upper to lower operating frequency). The aforementioned procedure is accompanied by an optimization-based design refinement scheme. A practical utility of the procedure is corroborated using multiple verification case studies as well as physical measurements of the antenna designed for the exemplary set of performance specifications., This work was supported in part by the Icelandic Centre for Research (RANNIS) under Grant 206606051, and in part by the National Science Centre of Poland under Grant 2020/37/B/ST7/01448.

Publisher's version (útgefin grein), Utilization of fast surrogate models has become a viable alternative to direct handling of full-wave electromagnetic (EM) simulations in EM-driven design. Their purpose is to alleviate the difficulties related to high computational cost of multiple simulations required by the common numerical procedures such as parametric optimization or uncertainty quantification. Yet, conventional data-driven (or approximation) modeling techniques are severely affected by the curse of dimensionality. This is a serious limitation when it comes to modeling of highly nonlinear antenna characteristics. In practice, general-purpose surrogates can be rendered for the structures described by a few parameters within limited ranges thereof, which is grossly insufficient from the utility point of view. This paper proposes a novel modeling approach involving variable-fidelity EM simulations incorporated into the recently reported nested kriging modeling framework. Combining the information contained in the densely sampled low- and sparsely sampled high-fidelity models is realized using co-kriging. The resulting surrogate exhibits the predictive power comparable to the model constructed using exclusively high-fidelity data while offering significantly reduced setup cost. The advantages over conventional surrogates are pronounced even further. The presented modeling procedure is demonstrated using two antenna examples and further validated through the application case studies., This work was supported in part by the Icelandic Centre for Research (RANNIS) under Grant 206606051, and in part by the National Science Centre of Poland under Grant 2018/31/B/ST7/02369.

Publisher's version (útgefin grein), Design of modern antennas relies-for reliability reasons-on full-wave electromagnetic simulation tools. In addition, increasingly stringent specifications pertaining to electrical and field performance, growing complexity of antenna topologies, along with the necessity for handling multiple objectives, make numerical optimization of antenna geometry parameters a highly recommended design procedure. Conventional algorithms, particularly global ones, entail often-unmanageable computational costs, so alternative approaches are needed. This work proposes a novel method for cost-efficient globalized design optimization of multi-band antennas incorporating the response feature technology into the trust-region framework. It allows for unequivocal allocation of the antenna resonances even for poor initial designs, where conventional local algorithms fail. Furthermore, the algorithm is accelerated by means of Jacobian variability tracking, which reduces the number of expensive finite-differentiation updates. Two real-world antenna design cases are used for demonstration purposes. The optimization cost is comparable to that of local routines while ensuring nearly global search capabilities., This work was supported in part by the Icelandic Centre for Research (RANNIS) under Grant 206606051, and in part by the National Science Centre of Poland under Grant 2017/27/B/ST7/00563., "Peer Reviewed"

Publisher's version (útgefin grein), Optimization-based parameter tuning has become an inherent part of contemporary antenna design process. For the sake of reliability, it is typically conducted at the level of full-wave electromagnetic (EM) simulation models. This may incur considerable computational expenses depending on the cost of an individual EM analysis, the number of adjustable variables, the type of task (local, global, single-/multi-objective optimization), and the constraints involved. For these reasons, utilization of conventional algorithms is often impractical. This paper proposes a novel gradient-based algorithm with numerical derivatives for expedited antenna optimization. The improvement of computational efficiency is obtained by employing a rank-one Broyden formula and restricting finite differentiation sensitivity updates to the principal directions of the Jacobian matrix, i.e., those corresponding to the most significant changes of the antenna responses. Comprehensive numerical validation carried out using three wideband antennas indicates that the presented methodology offers considerable savings of sixty percent with respect to the reference trust-region algorithm. At the same time, virtually no degradation of the design quality is observed. Furthermore, algorithm reliability is greatly improved (while offering comparable computational efficiency) over the recent state-of-the-art accelerated gradient-based procedures., The Icelandic Centre for Research (RANNIS) Grant 174114051, and in part by the National Science Centre of Poland Grant 2015/17/B/ST6/01857., "Peer Reviewed"

Publisher's version (útgefin grein), In this paper, a multiple-input-multiple-output (MIMO) antenna featuring circular polarization diversity, and designed on a common coplanar ground is presented. The proposed antenna design utilizes a coplanar waveguide (CPW) feeding technique with three parallel coplanar ground planes, and two feedlines in-between. For circular polarization (CP), quasi-loops are created by etching slots on the outermost ground planes. With this configuration, circular polarization diversity is induced in the MIMO antenna with the left-hand CP (LHCP) from one antenna and the right-hand CP (RHCP) from the other. The total footprint of the antenna radiator is only 0.78 lambda(0) x 0.55 lambda(0) = 0.42 lambda(2)(0). Experimental results show perfectly overlapping impedance and axial ratio bandwidths of 39.3% (4.5 GHz to 6.7 GHz). In addition, average in-band isolation vertical bar S-21 vertical bar, This work was supported in part by the Abu Dhabi Department of Education and Knowledge (ADEK) Award for Research Excellence, in 2019, under Grant AARE19-245, in part by The Icelandic Centre for Research (RANNIS) under Grant 206606051, and in part by the National Science Centre of Poland under Grant 2017/27/B/ST7/00563., "Peer Reviewed"

Publisher's version (útgefin grein), Uncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to frequency shifts of the operating bands. Quantifying these effects is imperative to adequately assess the design quality, either in terms of the statistical moments of the performance parameters or the yield. Reducing the antenna sensitivity to parameter deviations is even more essential when increasing the probability of the system satisfying the prescribed requirements is of concern. The prerequisite of such procedures is statistical analysis, normally carried out at the level of full-wave electromagnetic (EM) analysis. While necessary to ensure reliability, it entails considerable computational expenses, often prohibitive. Following the recently fostered concept of constrained modeling, this paper proposes a simple technique for rapid surrogate-assisted yield optimization of narrow- and multi-band antennas. The keystone of the approach is an appropriate definition of the optimization domain. This is realized by considering a few pre-optimized designs that represent the directions of the major changes of the antenna resonant frequencies and operating bands. Due to a small volume of such a domain, an accurate replacement model can be established therein using a small number of training samples, and employed to improve the antenna yield. Verification results obtained for a ring-slot antenna, a dual-band and a triple-band uniplanar dipoles indicate that the optimization process can be accomplished at low cost of a few dozen of EM simulations: 62, 74 and 132 EM simulations, respectively. Result reliability is validated through comparisons with EM-based Monte Carlo simulations., This work was supported in part by the Icelandic Centre for Research (RANNIS) under Grant 206606051, in part by the National Science Centre of Poland under Grant 2017/27/B/ST7/00563, and in part by the Abu-Dhabi Department of Education and Knowledge (ADEK) Award for Research Excellence, in 2019, under Grant AARE19-245., "Peer Reviewed"

Publisher's version (útgefin grein), The paper proposes a novel framework for accelerated re-design (dimension scaling) of antenna structures using inverse surrogates. The major contribution of the work is a sensitivity-based model identification procedure, which permits a significant reduction of the number of reference designs required to render the surrogate. Rigorous formulation of the approach is supplemented by its comprehensive numerical validation using a triple-band uniplanar dipole antenna and a dual-band monopole antenna re-designed with respect to operating frequencies as well as the substrate parameters (thickness and dielectric permittivity). It is demonstrated that—for the considered test cases—the reliable inverse model can be set up using a significantly smaller (by a factor of three) number of reference points as compared to the original version of the method, whereas the dimension scaling process itself requires up to four EM simulations of the antenna structure., This work was supported in part by the Icelandic Centre for Research (RANNIS) under Grant 174573051, and in part by the NationalScience Centre of Poland under Grant 2017/27/B/ST7/00563.

Publisher's version (útgefin grein), Butler matrices represent a popular class of feeding networks for antenna arrays. Large dimensions and the lack of flexibility in terms of achievable output phase difference make conventional Butler structures of limited use for modern communication devices. In this work, a com-pact planar 4×4 matrix with non-standard relative phase shifts of –30,150, –120, and 60° has been proposed. The structure is designed to operate at the centre frequency of 2.45 GHz. Small dimensions of 31.3×22.9 mm make it useful for Internet of Things applications. The structure operates from 2.35 to 2.55 GHz, which covers the industrial, scientific and medical bandwidth. At the centre frequency, the measured amplitude and phase imbalance are 1.65 dB and±4.3°, respectively. The proposed circuit has been compared to the state-of-the-art structures from the literature., This work was supported in part by National Centre for Research and Development Grant NOR/POLNOR/HAPADS/ 0049/2019-00, by National Science Centre of Poland Grant 2017/27/B/ST7/00563, and by Icelandic Centre for Research (RANNIS) Grant 206606051.

Publisher's version (útgefin grein), Antenna structures for modern applications are characterized by complex and unintuitive topologies that are difficult to develop when conventional, experience-driven techniques are of use.In this work, a method for the automatic generation of antenna geometries in a multi-objective set up has been proposed. The approach involves optimization of a generic spline-based radiator with an adjustable number of parameters using a nested, trust region-based algorithm. The latter iteratively increases the dimensionality of the radiator in order to gradually improve its performance. The method has been used to generate a set of nine antenna designs, representing a trade-off between minimization of reflection within 3.1 GHz to 10.6 GHz and a reduction of size. The properties of the optimized designs vary along the Pareto set from−10 dB to−20 dB and from 230 mm2to 757 mm2for the first and second objectives, respectively. The presented design approach has been validated against a genuine, population-based optimization routine. Furthermore, the smallest Pareto-optimal design has been compared to the antennas from the literature., This work was supported in part by the National Science Centre of Poland Grant 2017/27/B/ST7/00563 and by the National Centre for Research and Development Grant NOR/ POLNOR/HAPADS/0049/2019-00.

Publisher's version (útgefin grein), Design of contemporary antennas necessarily involves electromagnetic (EM) simulation tools. Their employment is imperative to ensure evaluation reliability but also to carry out the design process itself, especially, the adjustment of antenna dimensions. For the latter, traditionally used parameter sweeping is more and more often replaced by rigorous numerical optimization, which entails considerable computational expenses, sometimes prohibitive. A potentially attractive way of expediting the simulation-based design procedures is the replacement of expensive EM analysis by fast surrogate models (or metamodels). Unfortunately, due to the curse of dimensionality and considerable nonlinearity of antenna characteristics, applicability of conventional modeling methods is limited to structures described by small numbers of parameters within narrow ranges thereof. A recently proposed nested kriging technique works around these issues by allocating the surrogate model domain within the regions containing designs that are of high quality with respect to the selected performance figures. This paper investigates whether sequential design of experiments (DoE) is capable of enhancing the modeling accuracy over one-shot space-filling data sampling originally implemented in the nested kriging framework. Numerical verification carried out for two microstrip antennas indicates that no noticeable benefits can be achieved, which contradicts the common-sense expectations. This result can be explained by a particular geometry of the confined domain of the performance-driven surrogate. As this set consists of nearly-optimum designs, the average nonlinearity of the antenna responses therein is almost location independent, therefore optimum training data allocation should be close to uniform. This is indeed corroborated by our experiments., This work was supported in part by the Icelandic Centre for Research (RANNIS) under Grant 174114051 and Grant174573051, and in part by the National Science Centre of Poland under Grant 2018/31/B/ST7/02369.

Publisher's version (útgefin grein), Design of a compact wideband circularly polarized (CP) multiple-input multiple-output (MIMO) antenna with polarization diversity is proposed and characterized for off-body communication. The antenna is based on a simple coplanar waveguide (CPW)-fed monopole extension of the microstrip line. The orthogonal eld components required by CP are induced using a simply modied right/left side ground plane. In particular, a stub extending from the ground plane along the length of the microstrip line generates the vertical component, whereas the current along the width of the ground plane contributes to the horizontal components. To obtain a unidirectional radiation pattern in the off-body direction and to reduce the sensitivity to the human body loading effects, a at reector printed on a high permittivity exible substrate is applied. The simple topology of the antenna can be described by a few adjustable parameters, which facilitates its EM design closure. Prior to the experimental validation in the free space and on the body, the antenna is optimized at the full-wave level of description for all major performance gures. The overall footprint of the antenna radiator is only Ls Ws D 0.24 0 0.64 0 D 0.15 20. The proposed MIMO antenna features jS 11 j 10 dB, average isolation jS 21 j 22 dB, and axial ratio (AR) 3 dB from 5.2 GHz to 6.3 GHz with 100% bandwidth overlap between the impedance and axial ratio bandwidths. The envelope correlation coefcient (ECC) is less than 0.004 with the maximum diversity gain (DG) of approximately 9.99 dB. Moreover, the antenna maintains a high efciency of up to 90% when loaded on the body, and a low specic absorption rate (SAR)., This work was supported in part by the ADEK Award for Research Excellence under Grant AARE18-203 2018, in part by the Icelandic Centre for Research (RANNIS) under Grant 174114051, and in part by the National Science Centre of Poland under Grant 2017/27/B/ST7/00563., "Peer Reviewed"

Publisher's version (útgefin grein), Over the recent years, surrogate modeling has been playing an increasing role in the design of antenna structures. The main incentive is to mitigate the issues related to high cost of electromagnetic (EM)-based procedures. Among the various techniques, approximation surrogates are the most popular ones due to their flexibility and easy access. Notwithstanding, data-driven modeling of antenna characteristics is associated with serious practical issues, the primary one being the curse of dimensionality, particularly troublesome due to typically high nonlinearity of antenna responses. This limits applicability of conventional surrogates to simple structures described by a few parameters within narrow ranges thereof, which is grossly insufficient from the point of view of design utility. Many of these issues can be alleviated by the recently proposed constrained modeling techniques that restrict the surrogate domain to regions containing high-quality designs with respect to the relevant performance figures, which are identified using the pre-optimized reference designs at an extra computational effort. This paper proposes a methodology based on gradient-enhanced kriging (GEK). It enables a considerable reduction of the number of reference points required to construct the inverse surrogate (employed in surrogate model definition) by incorporating the sensitivity data into the nested kriging framework. Using two antenna examples, it is demonstrated to yield significant savings in terms of the surrogate model setup cost as compared to both conventional modeling methods and the original nested kriging., The Icelandic Centre for Research (RANNIS) under Grant 206606051, in part by the National Science Centre of Poland under Grant 2017/27/B/ST7/00563, and in part by the Abu-Dhabi Department of Education and Knowledge (ADEK) Award for Research Excellence, in 2019, under Grant AARE19-245., "Peer Reviewed"

Publisher's version (útgefin grein), 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., The National Natural Science Foundation of China Grant 61471258 and by Science & Technology Innovation Committee of Shenzhen Municipality Grant KQJSCX20170328153625183., "Peer Reviewed"

Maintaining small physical dimensions of antenna structures is an important consideration for contemporary wireless communication systems. Typically, antenna miniaturization is achieved through various topological modifications of the basic antenna geometries. The modifications can be applied to the ground plane, the feed line, and/or antenna radiator. Unfortunately, various topology alteration options are normally reported on a case-to-case basis. The literature is lacking systematic investigations or comparisons of different modification methods and their effects on antenna miniaturization rate as well as electrical performance. Another critical issue—apart from setting up the antenna topology—is a proper adjustment of geometry parameters of the structure so that the optimum design can be identified. Majority of researchers utilize experience-driven parameter sweeping which typically yields designs that are acceptable, but definitely not optimal. Furthermore, in many of the cases, the authors provide a cooperative progression before and after topological modifications that generally lead to a certain reduction of the antenna size, however, with appropriate parameter adjustment missing. Consequently, suitability of particular modifications in the miniaturization context is not conclusively assessed. In order to carry out such an assessment in a reliable manner, identification of the truly optimum design is necessary. This requires rigorous numerical optimization of all antenna parameters (especially in the case of complex antenna topologies) with the primary objective being size reduction, and supplementary constraints imposed on selected electrical or field characteristics. This thesis is an attempt to carry out systematic investigations concerning the relevance of geometry modifications in the context of wideband antenna miniaturization. The studies are carried out based on selected benchmark sets of wideband antennas. In order to ensure a fair comparison, all geometry parameters are rigorously tuned through EM-driven optimization to obtain the minimum footprint while maintaining acceptable electrical performance. The results demonstrate that it is possible to conclusively distinguish certain classes of topology alterations that are generally advantageous in the context of size reduction, as well as quantify the benefits of modifications applied to various parts of the antenna structure, e.g., with feed line modifications being more efficient than the ground plane and radiator ones. Several counterexamples have been discussed as well, indicating that certain modifications can be counterproductive when introduced ad hoc and without proper parameter tuning. The results of these investigations have been utilized to design several instances of novel compact wideband antennas with the focus on isolation improvement and overall antenna size reduction in multi-input-multi-output (MIMO) systems. Experimental validations confirming the numerical findings are also provided. To the best of the author’s knowledge, the presented study is the first systematic investigation of this kind in the literature and can be considered a step towards the development of better, low-cost, and more compact antennas for wireless communication systems., Fyrir þráðlaus fjarskiptakerfi er mikilvægt að tryggja að loftnet séu lítil að umfangi. Yfirleitt er smækkun loftneta náð með ýmis konar formbreytingum á grunngerðum þeirra. Formbreytingarnar geta verið á jarðtengingu, fæðilínu og / eða geislagjafa. Því miður er venjulega einungis sagt frá slíkum formbreytingum fyrir einstaka tilvik. Skortur er á kerfisbundnu mati og samanburði á mismunandi formbreytingum og hvaða áhrif þær hafa á smækkun og raffræðilega eiginleika loftneta. Annað mikilvægt atriði, fyrir utan að ákveða gerð formbreytingarinnar, er að velja stika sem lýsa nákvæmri lögun svo að bestuð hönnun geti átt sér stað. Flestir hönnuðir notast við þá aðferð að notast við stikaskimun sem byggir á reynslugögnum, en sú aðferð skilar almennt ásættanlegri hönnun, þó ekki bestaðri. Einnig er í mörgum tilvikum sagt frá samhliða þróun fyrir og eftir formbreytingu sem leiðir til smækkunar án þess að tilgreina breytingar á stikum. Fyrir vikið er erfitt að meta til hlítar ávinning af mismunandi formbreytingum. Til þess að framkvæma slíkt mat með áreiðanlegum hætti er nauðsynlegt að geta metið bestu hönnunarútfærslu nákvæmlega. Þetta kallar á ítarlega tölulega bestun allra stika sem lýsa loftnetinu (einkum fyrir loftnet flókinnar lögunnar) þar sem aðalmarkmkið bestunar er smækkun en skorður eru settar af raffræðilegum eiginleikum. Í þessari ritgerð er leitast við að kerfisbundna rannsókn á mikilvægi formbreytingna í tengslum við smækkun bandbreiðra loftneta. Rannsóknin byggir á völdum söfnum viðmiðunarloftneta. Til að tryggja rétt mat eru allir stikar er varða lögun stilltir með rafsegulfræðilegri hermun til að tryggja minnst rúmtak með ásættanlegum raffræðilegum eiginleikum. Niðurstöðurnar sýna að unnt er að greina, án vafa, ákveðna flokka formbreytinga sem eru að jafnaði til þess fallnir að smækka loftnet. Auk þessa er hægt að reikna ávinning af formbreytingum mismunandi hluta loftnetsins, t.d. að breytingar á fæðilínu eru almennt hagkvæmari en breytingar á geislagjafa eða jarðtengingu. Þá er greint frá nokkrum tilvikum þar sem tilfallandi formbreytingar geta verið til tjóns ef ekki stikaval er ekki gert með réttum hætti. Niðurstöður þessara rannsóknar hafa verið notaðar til að hanna nokkur nýstárleg breiðbandsloftnet með áherslu á smækkun og bættan aðskilnað fjölgátta (MIMO) loftneta. Töluleg hermun er sannreynd með tilraunum. Að bestu vitund höfundar er hér um fyrstu kerfisbundnu rannsókn þessarar gerðar að ræða og má reikna með að hún leiði til þróunar betri, ódýrari og smærri loftneta fyrir þráðlaus fjarskiptakerfi., The Ph.D. project was supported by the Icelandic Research Center (RANNIS) Grant 163299051

Publisher's version (útgefin grein), 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., National Natural Science Foundation of China Grant, 61471258 and by Science & Technology Innovation Committee of Shenzhen Municipality Grant, KQJSCX20170328153625183., "Peer Reviewed"

Re-design of a given antenna structure for various substrates is a practically important issue yet non trivial, particularly for wideband and ultra-wideband antennas. In this work, a technique for expedited redesign of ultra-wideband antennas for various substrates is presented. The proposed approach is based on inverse surrogate modeling with the scaling model constructed for several reference designs that are optimized for selected values of the substrate permittivity. The surrogate is set up at the level of coarse-discretization EM simulation model of the antenna and, subsequently, corrected to provide prediction at the high-fidelity EM model level. The dimensions of the antenna scaled to any substrate permittivity within the region of validity of the surrogate are obtained instantly, without any additional EM simulation necessary. The proposed approach is demonstrated using an ultra-wideband monopole with the permittivity scaling range from 2.2 to 4.5. Numerical validation is supported by physical measurements of the fabricated prototypes of the re-designed antennas., The authors would like to thank Computer Simulation Technology AG, Darmstadt, Germany, for making CST Microwave Studio available. This work is partially supported by the Icelandic Centre for Research (RANNIS) Grant 141272051 and by National Science Centre of Poland Grant 2014/15/B/ST7/04683.

Publisher's version (útgefin grein), Parameter optimization, also referred to as design closure, is imperative in the development of modern antennas. Theoretical considerations along with rough dimension adjustment through supervised parameter sweeping can only yield initial designs that need to be further tuned to boost the antenna performance. The major challenges include handling of multi-dimensional parameter spaces while accounting for several objectives and constraints. Due to complexity of modern antenna topologies, parameter interactions are often involved, leading to multiple local optima as well as difficulties in identifying decent initial designs that can be improved using local procedures. In such cases, global search is required, which is an expensive endeavor, especially if full-wave electromagnetic (EM) analysis is employed for antenna evaluation. This paper proposes a novel technique accommodating the search space exploration using local kriging surrogates and local improvement by means of trust-region gradient search. Computational efficiency of the process is achieved by constructing the metamodels over appropriately defined affine subspaces and incorporation of coarse-mesh EM simulations at the exploratory stages of the optimization process. The resulting framework enables nearly global search capabilities at the costs comparable to conventional gradient-based local optimization. This is demonstrated using two antenna examples and comparative studies involving multiple-start local tuning., This work is partially supported by the Icelandic Centre for Research (RANNIS) Grant 174573051 and by National Science Centre of Poland Grant 2018/31/B/ST7/02369., "Peer Reviewed"

Publisher's version (útgefin grein), This paper addresses computationally feasible multi-objective optimization of antenna structures. We review two recent techniques that utilize the multi-objective evolutionary algorithm (MOEA) working with fast antenna replacement models (surrogates) constructed as Kriging interpolation of coarse-discretization electromagnetic (EM) simulation data. The initial set of Pareto-optimal designs is subsequently refined to elevate it to the high-fidelity EM simulation accuracy. In the first method, this is realized point-by-point through appropriate response correction techniques. In the second method, sparsely sampled high-fidelity simulation data is blended into the surrogate model using Co-kriging. Both methods are illustrated using two design examples: an ultra-wideband (UWB) monocone antenna and a planar Yagi-Uda antenna. Advantages and disadvantages of the methods are also discussed., The authors would like to thank the Computer Simulation Technology AG, Darmstadt, Germany, for making CST Microwave Studio available. This work was supported in part by the Icelandic Centre for Research (RANNIS), the Grant 130450051, and by the National Science Centre of Poland, the Grants 2013/11/B/ST7/04325 and 2014/12/ST7/00045.

Efficiency improvement is of great significance for simulation-driven antenna design optimization methods based on evolutionary algorithms (EAs). The two main efficiency enhancement methods exploit data-driven surrogate models and/or multi-fidelity simulation models to assist EAs. However, optimization methods based on the latter either need ad hoc low-fidelity model setup or have difficulties in handling problems with more than a few design variables, which is a main barrier for industrial applications. To address this issue, a generalized three stage multi-fidelity simulation -model assisted antenna design optimization framework is proposed in this paper. The main ideas include introduction of a novel data mining stage handling the discrepancy between simulation models of different fidelities, and a surrogate-model-assisted combined global and local search stage for efficient high-fidelity simulation model-based optimization. This framework is then applied to SADEA, which is a state-ofthe-art surrogate-model-assisted antenna design optimization method, constructing SADEA-II. Experimental results indicate that SADEA-II successfully handles various discrepancy between simulation models and considerably outperforms SADEA in terms of computational efficiency while ensuring improved design quality., The authors thank CST AG for making CST Microwave Studio available. The authors would like to thank Dr. Renato Cordeiro de Amorim, Glyndwr University, UK for valuable discussions., "Peer Reviewed"

Publisher's version (útgefin grein), 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., The Icelandic Centre for Research (RANNIS) Grant 174114051, and by National Science Centre of Poland Grant 2015/17/B/ST6/01857., "Peer Reviewed"