Optimization of a Multi-Function Car-Roof Antenna Using Deep Learning Method
Dingwen Tan ,
Hexue Liu ,
Bing Xu ,
Xiaoming Liu ,
Shuo Yu and
Lu Gan
This paper presents a dual-band car-roof antenna, which holds potential applications for 5G-MIMO, WLAN and V2X. The proposed antenna is installed within a shark-fin room on the roof of vehicles. The proposed design consists of two parts, the diversity antenna and the main antenna. To mitigate spatially selective fading and ensure coverage, both the diversity and main antennas have omnidirectional radiation patterns in the azimuth plane. To reach a multi-function design, deep learning method is used for optimization based on MATLAB-HFSS-API. Notably, the optimized antenna reaches a compact size of 27 mm × 30 mm × 2 mm. The antenna have two bands (-10 dB), including 3.35-3.75 GHz and 4.76-7.19 GHz, covering China Telecom (3.4-3.5 GHz), China Unicom (3.5-3.6 GHz), China Mobile (4.8-4.9 GHz), WLAN (5.15-5.35 GHz, 5.725-5.850 GHz), unlicensed Wi-Fi (5.850-5.895 GHz), V2X (5.895-5.925 GHz) and Wi-Fi 6E (5.925-7.125 GHz). The full-wave simulation results are in satisfactory consistency with the measured ones.