Deep Learning based Microstrip Patch Array Antenna Structure for MIMO 5G Wireless Communication

The most recent wireless communication system (5G WCS) requires an antenna framework that is both optimal and efficient in order to achieve its goal of seamless transmission. In this paper, we investigate the design of a microstrip patch array antenna for MIMO 5G WCS and improve its performance using a deep learning (DL) technique. Both the presented DL and antenna structure are validated with a simulation model and subjected to mathematical analysis. In order to accomplish this goal, resonance frequencies of 35 gigahertz, a dielectric constant of 2.3, and a thickness of 0.5 millimeters are taken, and matrices such as bandwidth, mutual coupling, radiation efficiency, gain, and return loss are evaluated. The results of the comparison demonstrate that the DL-enabled antenna model performs effectively.