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.

This study aims to investigate the impact of the presence of buildings on the radiation characteristics of MF broadcast antennas. Two different antennas are considered: a monopole operating at 1494 kHz and a two-element linear array radiating at 1008 kHz. The buildings were modeled as wire-grids and the total electric field intensity was calculated as the sum of the scattered field by the wire-grid and the field radiated from the antenna in free space. The radiation pattern of the antennas, when one or two buildings were situated in their vicinity, were the end result of the analysis, and they were compared to the corresponding patterns in free space. The results demonstrate that the radiation characteristics of antennas are mostly affected by the heights of buildings. If these heights are less than a critical value, the buildings do not significantly obstruct the operation of the antenna, despite the value of other parameters, such as the length and the width of the buildings, as well as their distance from the antenna.

A complex cylindrical structure consisting of a group of parallel stratified circular lossy dielectric cylinders, embedded in a dielectric circular cylindrical region and surrounded by unbounded dielectric space, is considered in this paper. The scattering of electromagnetic (EM) plane waves by the aforementioned configuration was studied; the EM waves impinged obliquely upon the structure and were arbitrarily polarized. The formulation used was based on the boundary-value approach coupled with the generalized separation of variables method. The EM field in each region of space was expanded in cylindrical wave-functions. Furthermore, the translational addition theorem of these functions was applied in order to match the EM field components on any cylindrical interface and enforce the boundary conditions. The end result of the analysis is an infinite set of linear algebraic equations with the wave amplitudes as unknowns. The system is solved by the truncation of series and unknowns and then matrix inversion; thus, we provide a semi-analytical solution for the scattered far-field and, as a consequence, for the scattering cross section of the complex cylindrical structure. The numerical results focus on calculations of the electric- and magnetic-field intensity of the far-field as well as of the total scattering cross section of several geometric configurations that fall within the aforementioned general structure. The effect of the geometrical and electrical characteristics of the structure on the scattered field was investigated. Specifically, the cylinders’ size and spacing, their conductivity and permittivity as well as the incidence direction were modified in order to probe how these variations are imprinted on scattering. Moreover, comparisons with previously published results, as well as convergence tests, were performed; all tests and comparisons proved to be successful.

Energy-efficient wireless sensor networks (WSNs) rely on complex mathematical models to optimize critical operations such as coverage, routing, and energy harvesting. However, these equations impose diverse computational requirements: some demand rapid approximate methods to minimize overhead, while others require high-accuracy or even analytical solutions for precise optimization. This diversity introduces a key challenge: selecting the most suitable solving method for each equation type. This paper introduces the Argumentation-Based Equation-Solver Selector (ABESS), a decision-making framework that chooses a solver based on user-provided descriptors and also provides justification, by encoding rules, preferences, and contextual priorities. By leveraging computational argumentation, ABESS provides an adaptive and explainable approach to managing the resource-constrained nature of WSNs. Another contribution is a detailed functional behavior analysis of characteristic formulas in the WSN domain. This analysis on the one hand derives the descriptors for ABESS reasoning, e.g., verified localization intervals for design solutions, and on the other hand, cross-validates its performance. Thus, ABESS helps to avoid the use of failure-prone numerical methods and significantly improves computational efficiency. Empirical results across three core WSN models demonstrate the framework’s efficacy, including a 870× speedup in integer thresholding compared to uninformed exhaustive scanning.