2022 5th International Conference on Contemporary Computing and Informatics (IC3I) 619 979-8-3503-9826-7/22/$31.00 ©2022 IEEE Design of Optimized low-power GPS-Yagi Antenna using Machine Learning techniques D. Jessintha Electronics and Communication Engineering Easwari Engineering College Chennai, India jessintha.d@eec.srmrmp.edu.in T. Ananth Kumar Computer Science and Engineering IFET College of Engineering Chennai, Tamilnadu, India tananthkumar@ifet.ac.in Kenjaev Sanjar Sobirovich Faculty of International Education Programs Samarkand State University Uzbekistan s.kenjayev22@gmail.com Christo Ananth Department of Natural and Exact Sciences Samarkand State University Uzbekistan dr.christoananth@gmail.com Abstract—The time-consuming process of developing analytical models can be accelerated with the help of machine learning, which is a technique for data processing. Using machine learning, antenna designers can quickly and intelligently optimize their physical antenna designs. This is achieved by developing trained models of the designers' designs. Consequently, antenna designers can create more efficient antennas. Due to this, antenna designers can continue developing new designs despite the increasing complexity of antennas. When discussing this specific type of antenna, "Yagi" is frequently used as an abbreviation for "Yagi-Uda" the full name of the antenna. The length of the "driven dipole" may be equal to or shorter than the length of the "directors." The ability to rapidly execute a diverse set of optimization algorithms and objectives, made possible by the trained models, makes it easier to conduct rapid comparisons and a diverse set of studies (including stochastic analysis for tolerance studies, etc.). While the device was operating at a frequency of ten gigahertz, the concept of two parasitic directors was conceived, and these parasitic directors were designed and optimized to improve the device's directivity further. This antenna offers numerous advantages, one of which is its simplicity of manufacture. This antenna can be manufactured relatively easily due to its diminutive size and uncomplicated overall layout. The stochastic global search and optimization method known as simulated annealing (SA) is extraordinarily effective. This method is implemented instead of more conventional ones to achieve optimal element spacing. Keywords— GPS, Yagi Antenna, Machine learning, Radia- waves I. INTRODUCTION Typically, antennas are made of metal, used to transmit and receive radio waves. All radio transmissions, including broadcast radio, television, and point-to-point radio, require an antenna [1]. There is no method of radio transmission that does not involve an antenna. This directional antenna design, also known as a "Yagi-Uda array," focuses radio waves in a particular direction. The length of the reactor element will be same or longer. This antenna configuration increases both its gain and directional capabilities compared to a standard dipole [2]. The gain, resonant frequency, and directivity of an antenna, as well as its radiation pattern and efficiency, are among its most crucial performance characteristics. Additionally essential is the antenna's efficiency. Antennas are the link between the transmitter and the outside world. In addition to their primary function, antennas can connect the sender and the receiver [3]. Even though there are numerous advantages to using printed antennas, there are also disadvantages. Initially, the output power level is significantly lower than before. Typically, they have extremely limited bandwidths. On the other hand, Vivaldi and tapered slot antennas rely on traveling waves to provide broad bandwidth [4]. In recent years, computer-aided design (CAD) software has become increasingly important for designing, analyzing, optimizing, and fabricating microstrip antenna arrays and individual antennas. Many different simulation programs, such as HFSS®, CST®, MWO®, and many others, were used to model electromagnetic fields to a significant degree. The evaluation of a system's merits heavily depends on its antennas' performance. Antennas are adaptable devices with a wide variety of uses and can take on a variety of shapes. Some systems use antennas to direct the flow of electromagnetic energy, whereas other systems use antennas in an omnidirectional capacity. This is because some antennas are designed to transmit signals in a specific direction, while others are designed to transmit signals in all directions. Because some systems rely on antennas for point- to-point communication, increasing the gain of antennas while simultaneously reducing the amount of wave interference they encounter is essential. When discussing electromagnetic energy, any device capable of receiving or transmitting signals is referred to as an "antenna". An antenna is considered a receiver if it generates a variable current distribution in response to radiation from the outside, and a transmitter generates radiation in response to a variable current distribution on the antenna that is driven from the outside. These definitions are both widely accepted. Depending on their orientation, the majority of antennas can either transmit or receive signals. In addition, certain antennas can concentrate incoming electromagnetic waves, allowing them to receive and transmit signals simultaneously. In recent years, the development of the vast majority of 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) | 979-8-3503-9826-7/22/$31.00 ©2022 IEEE | DOI: 10.1109/IC3I56241.2022.10072553 Authorized licensed use limited to: National Institute of Technology Patna. Downloaded on March 27,2023 at 02:34:08 UTC from IEEE Xplore. Restrictions apply.