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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.