Soft computing techniques are used, in this paper, to model and solve the inverse problem of a thin, circular, loop antenna that radiates in free space. The electromagnetic field intensity serves as the input to the inverse model, whereas the antenna radius is the output. Three different architectures, based on artificial neural networks (ANNs), are implemented and various training algorithms are tested in order to obtain the optimum performance. The effect of the size of the training data set and the number of the observers on the accuracy of the results are investigated. Specific information for the selection of the appropriate ANN architecture is provided, depending on the constraints imposed by various parameters of the problem. Extensive numerical tests indicate that the results predicted by the proposed models are in excellent agreement with the theoretical data obtained from the existing analytical solutions of the forward problem.

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The new generation of wireless communication technologies is already in development. Sixth Generation (6G) mobile communications are designed to push the limits for more bandwidth, more connected devices with minimal power requirements, and better signal quality. Previous technologies used in Fifth Generation (5G) are inadequate to handle the new requirements alone. One of the proposed solutions is the use of Reconfigurable Intelligent Surfaces (RISs). These surfaces, when combined with Artificial Intelligence (AI), may be a very powerful means of achieving this. In this paper, we review studies that focus on the use of RISs controlled by AI in determining the concept of Smart Radio Environment (SRE) for use in 6G wireless networks. We examine applications that span from Supervised to Federated Learning (FL) as enabled by the rise in Edge Computing. As the new generation of mobile devices is expected to have enhanced capabilities to perform computing and AI locally, thus reducing the need to transfer the data to a central hub, more opportunities are created for the extensive use of FL. In this context, we focus on research in FL as used in RIS-aided SRE.

Single-layer 4 × 4 and 8 × 8 Butler matrices (BMs) that operate in the L and S bands are implemented in this paper. Easy-to-fabricate microstrip layout topologies are designed and constructed; the final arrangement of the BMs allows realization without any crossovers. The performance of the networks is evaluated by measuring their frequency response. The return loss (RL) and the isolation are below -15 dB over the operation bandwidth for all structures, whereas the average insertion loss is less than 1 dB for the 4 × 4 BM and does not exceed 3 dB for the 8 × 8 BM. The amplitude imbalance is at most 0.5 dB and 1.5 dB, for the 4 × 4 and the 8 × 8 BMs, respectively. Moreover, multibeam antenna arrays fed by the BMs are constructed. The radiation patterns are measured and compared with theoretical data; a good agreement is achieved. The side lobes are sufficiently low, compared to the theoretical predictions, whereas they are further reduced by applying appropriate excitation schemes to the input ports of the BMs.

A versatile eccentric-spheres model of the human head is used to investigate radio-wave absorption. Numerical results, obtained by use of an exact analytical solution, are presented for the total, percentage, and gram-specific absorption. Interest is mainly in the brain and in the eyes of an adult or an infant head. Our model comprises a host sphere and several spherical inclusions, all concentrically stratified with respect to their own center. Any number of inclusions and any number of concentric layers for the host sphere and each one of the inclusions can be considered. Excitation is provided either by a plane-wave or by a nearby electric dipole. The analytical solution is obtained by use of the indirect-mode matching method. The theory of this paper and the accompanying computer code constitute a versatile tool for analytical studies of cellular-phone interactions with the human head. Specific absorption rate maps in a horizontal cross section of the head model manifest the existence of hot spots in the eyes and near the center of the brain.