Abstract

PurposeThe purpose of this study is to develop a method to reduce the computation time necessary for the automated optimal design of dual-band wearable antennas. In particular, the authors investigated if this can be achieved by the use of a hierarchical optimization paradigm combined with a simplified human body model. The geometry of the antenna under consideration is described via eight geometrical parameters which are automatically adjusted with the use of an evolutionary algorithm to improve the impedance matching of an antenna located in the proximity of a human body. Specifically, the antennas were designed to operate in the ISM band which covers two frequency ranges: 2.4-2.5 GHz and 5.7-5.9 GHz.Design/methodology/approachDuring the studies on the automated design of wearable antennas using evolutionary computing, the authors observed that not all design parameters exhibit equal influence on the objective function. Therefore, it was hypothesized that to reduce the computation effort, the design parameters can be activated sequentially based on their influence. Accordingly, the authors’ computer code has been modified to include this feature.FindingsThe authors’ novel hierarchical multi-parameter optimization method was able to converge to a better solution within a shorter time compared to an equivalent method not exploiting automatic activation of an increasing number of design parameters. Considering a significant computational cost involved in the calculation of the objective function, this exhibits a convincing advantage of their hierarchical approach, at least for the considered class of antennas.Research limitations/implicationsThe described method has been developed for the design of single- or dual-band wearable antennas. Its application to other classes of antennas and antenna environments may require some adjustments of the objective functions or parameter values of the evolutionary algorithm. It follows from the well-recognized fact that all optimization methods are to some extent application-specific.Practical implicationsComputation load involved in the automated design and optimization can be significantly reduced compared to the non-hierarchical approach with a heterogeneous human body model.Originality/valueTo the best of the authors’ knowledge, the described application of hierarchical paradigm to the optimization of wearable antennas is fully original, as well as is its combination with simplified body models.

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