Sparse Wire Grid UHF-Band Pyramidal Horn Antenna

Advanced technologies require the development of new antennas with smaller mass and size. In order to reduce the antenna mass, the solid metal surface of a UHF-band pyramidal horn antenna is approximated using the wire grid approach that based on the method of moments. The simulation results obtained for the wire grid structure are compared with those calculated using other numerical methods as well as with the measured results for the antenna fabricated prototype in another work. The comparisons showed that the results obtained for the wire grid structure are in good agreement with the measured ones. To further reduce the antenna mass, the Optimal Current Grid Approximation (OCGA) approach is applied to the original wire grid structure in order to generate sparse structures on its basis. The antenna characteristics of the generated sparse structures are compared with each other and with those of the original structure in the operating frequency range. The comparative analysis showed that the results obtained for the sparse structures agreed well with those for the original structure. The contribution of this study is to verify the effectiveness of the OCGA approach in generating UHF-band sparse structures. The generated sparse structure can be used to replace the wire grid structure as well as the solid metallic structure with controlled characteristics accuracy, while reducing its mass and modeling computational costs.

I. Introduction

Antennas play an important role in modern life, especially in wireless communication [1], [2], medicine [3], [4] and many other industries [5], [6]. The development of 5G networks and the popularity of their Internet of Things (IoT) applications complicate the requirements for antennas to provide high-speed and reliable data transmission [7], [8]. To deal with this challenge, recent studies have focused on the development of new types of antennas [9], [10]. However, this involves many difficulties, such as developing high performance antennas that can operate in diverse and crowded environments under all harsh conditions [11], [12]. In addition, reducing antennas size and mass to fit mobile devices and IoT applications without sacrificing their performance is also a significant challenge for researchers [13], [14]. Therefore, researchers use computer modeling to accurately evaluate the antenna characteristics and adjust its design according to real environment [15], [16].