Sort by
Ultrahigh frequency path loss prediction based on K-nearest neighbors

Abstract Path loss prediction (PLP) is an important feature of wireless communications because it allows a receiver to anticipate the signal strength that will be received from a transmitter at a given distance. The PLP is done by using machine learning models that take into account numerous aspects such as the frequency of the signal, the surroundings, and the type of antenna. Various machine learning methods are used to anticipate path loss propagation but it is difficult to predict path loss in unknown propagation conditions. In existing models rely on incomplete or outdated data, which can affect the accuracy and reliability of predictions and they do not take into account the effects of environmental factors, such as terrain, foliage, and weather conditions, on path loss. Furthermore, existing models are not robust enough to handle the real-world variability and uncertainty, leading to significant errors in predictions. To tackle this issue, a novel ultrahigh frequency (UHF) PLP based on K-nearest neighbors (KNNs) is developed for predicting and optimizing the path loss for UHF. In this proposed model, a KNN-based PLP has been used to predict the path loss in the UHF. This technique is used for high-accuracy PLP through KNN forecast route loss by determining the K-nearest data points to a particular test point based on a distance metric. Moreover, the existing models were not able to optimize path loss due to complex and large-scale machine learning models. Therefore, the stochastic gradient descent technique has been used to minimize the objective function, which is often a measure of the difference between the model’s predictions and the actual output that will fine-tune the parameters of the KNN model, by measuring the similarity between data points. This model is implemented using Python to make it a lot more convenient.

Relevant
Design of TE-polarized resonant Bessel-beam launchers for wireless power transfer links in the radiative near-field region

Abstract Resonant Bessel-beam launchers (BBLs)are radiating devices constituted by a cylindrical metallic cavity with a partially reflecting sheet (PRS) on top. Millimeter-wave resonant BBLs typically exhibit transverse magnetic (TM) polarization due to the use of coaxial probes as feeders and homogenized metasurfaces as PRS. Launchers showing either a purely transverse electric (TE) or a hybrid (quasi-TE) polarization have recently been proposed for realizing wireless power transfer (WPT) links in the radiative near-field region at millimeter waves. The former are obtained by means of a radial slot array as a feeder and a homogenized metasurface as a PRS. The latter are obtained by using a loop antenna as a feeder and an annular strip grating in the homogenization limit as radiating aperture. In this work, based on an original semi-analytical model, such a metasurface is demonstrated to show a dichroic behavior. This interpretation explains the improvement in terms of polarization purity with respect to more nondichroic conventional homogenized metasurfaces. The behavior of the annular strip grating under a pure TM polarization is tested with a coaxial feeder, whereas its behavior under a pure TE polarization is tested by means of the radial slot array feeder. Results confirm the validity of the proposed analysis, which is finally exploited to evaluate the WPT performance.

Open Access
Relevant