Designing of a 5G Multiband Antenna Using Decision Tree and Random Forest Regression Models

Abstract

In this paper, a comparative study of decision tree and random forest regression models for the design of a multiband inverted E and U-shaped compact antenna for future 5G applications is presented. The results obtained from these regression models are compared with the simulation results of openEMS software. Found that Random Forest (RF) regression model results are in good agreement with the openEMS results when compared to the decision tree regression model. The advantage of the proposed method lies in the fact that the final RF model can be used for the designing of this multiband antenna between 2GHz to 10GHz range of frequencies.