Application of Machine Learning 

in Electromagnetics

                Abstract

                 As an integral part of the electromagnetic system, antennas are becoming more advanced and versatile than ever before, thus making it necessary to adopt new techniques to enhance their performance. Machine Learning (ML), a branch of artificial intelligence, which is a method of data analysis that automates analytical model building with minimal human intervention. The potential of solving unpredictable and non-linear complex challenges is attracting researchers in the field of electromagnetics, especially in antenna and antenna-based systems. Although the accuracy of Machine Learning algorithms depends on the availability of sufficient data and expert handling of the model, it is steadily becoming the desired solution when the aim is for a cost-efficient and without excessive time consumption solution. 

                In this project we will be presenting an overview of machine learning and its applications in electromagnetics. Moreover, we will discuss what types of antennas can be used in different places based on the electromagnetic reading from that area, by using intelligent algorithms for the antenna design.

                 Introduction

                In Timis county, a multitude of measurements related to electromagnetic fields were performed. The measurements took place in all the big cities and in the surrounding villages and communes. The main points of interest were hospitals, schools, churches, GSM antennas and other public buildings and large intersections. The factors that could influence the results are the temperature, the weather and the time when the measurements took place, based on the number of dwellings present at these locations and the devices used.

                          Figure 1. Applications of Machine Learning in the field of electromagnetics.

                    The objective of the project covers the "Antenna positioning and direction estimation" based on the measurements noted from different parts of the city. The places where high concentrations of electromagnetic fields are detected, can be used to determine whether it is an appropriate place to install an antenna and it can also be used to determine if in the direction in which the antenna is pointed has disruption points.

                    How can Machine Learning help in electromagnetics? Electromagnetics in today's world is everywhere, in every device that consumes electricity. If a current passes through a wire, it will generate an electromagnetic field. Considering this, we want to generate electromagnetic fields when we want to communicate over Wi-Fi, Bluetooth or other types of wireless transmissions. This type of electromagnetic Wi-Fi communication has a drawback, it is prone to interferences. A good example would be if we have a lot of electronics in a place where we want to use our mobile phone to connect to a Wi-Fi network. In this case, the data can be corrupted, leading to loss of connection or other unintended behavior. Another problem is how can we separate multiple mobile phones by interfering with each other.

                    Machine learning can help by learning the interference pattern and canceling out those patterns. In this case, the error rate can be reduced by as much as 75-90%, yielding to a better data transmission and less error correcting work. By using different kind of models, we can adapt our antenna layout in ways that can optimize communication in a tight area, if we want a focused communication, like e a beam.

                    By using machine learning we can create a model to work more reliably in harsh condition, like rain, snow, or other interfering factors. Another way we can optimize the electromagnetic situation by using learning algorithms is by using less expensive antennas, because we can compensate with data predictions leading to a cost reduction solution.

Bibliography:

- https://www.mdpi.com/2079-9292/10/22/2752/pdf