A structure of a compact ultra‐wideband monopole antenna has been presented. The antenna consists of a microstrip‐fed rectangle radiator as well as a ground plane with a rectangle slit and an L‐shaped stub. The critical factor in achieving a small size is a careful design procedure involving numerical optimisation of all geometry parameters of the antenna aiming at explicit size reduction while maintaining acceptable electrical performance. The final design exhibits dimensions of only 9.45 × 18.5 mm and a footprint of 175 mm ² . Experimental validation and comparisons with competitive designs are also provided.

In this study, a concept and design optimisation procedure of a novel compact multiple‐input–multiple‐output (MIMO) slot antenna is presented. As the authors’ primary objective is to achieve a better utilisation of the available space, individual ultra‐wideband (UWB) antennas are constrained to a triangular shape and optimised for a reduced size. Subsequently, the MIMO structure is assembled using the previously designed radiators in orthogonal arrangement. Low computational cost of antenna geometry parameter adjustment is maintained by employing surrogate‐assisted optimisation involving variable‐fidelity electromagnetic simulation models. The footprint of the optimised MIMO design is only 630 mm ² and features very good isolation in the entire UWB frequency band. Numerical results are confirmed by experimental measurements of the fabricated prototype.

A structure and computationally efficient design optimisation procedure of a novel miniaturised UWB slot antenna has been proposed. Upon geometry parameter adjustment, the structure exhibits a very small footprint of just 161 mm ² . This has been achieved by introducing sufficient number of degrees of freedom, including the parameterised multi‐section slot and a multi‐section load of the feed line as well as efficient numerical optimisation of all relevant geometry dimensions of the structure. The design process has been formulated as explicit size reduction problem. The electrical performance parameters (here, a maximum in‐band reflection) are controlled by suitably defined constraints. The final design has been verified through full‐wave electromagnetic simulation as well as physical measurements of the fabricated antenna prototype.

A technique for fast multi‐objective optimisation of antennas is introduced. The core of the proposed methodology is a reliable initial estimation of the design space subset that contains a set of Pareto optimal solutions, i.e. those representing the best possible trade‐offs between the conflicting objectives (such as the antenna size and its electrical performance parameters). A fast response surface approximation (RSA) surrogate is subsequently constructed in a reduced search space using sampled coarse‐discretisation electromagnetic (EM) simulation data. Owing to the authors’ reduction approach, the surrogate model construction is computationally feasible even when the number of antenna parameters is high. The RSA model is optimised using a multi‐objective evolutionary algorithm to yield an initial approximation of the Pareto set. The latter is further refined (to obtain its representation at the high‐fidelity EM antenna model level). The approach is illustrated using two design cases. A comparison with previously published methods, as well as experimental validation, is also provided.

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 setup 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 mm² to 757 mm² for 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.