Abstract
A new tool, machine learning optimization (MLAO), has recently been introduced to accelerate antenna and array design. In order to improve fast response prediction, machine learning (ML) techniques, including GPR, SVM, and ANN, were used to develop antenna models. The Multiple-Input Multiple-Output (MIMO) acquainted with the 4G versatile system should be effectively tried and may work in the current recurrence of correspondence. By HFSS, the planning scheme for a dual MIMO broadband antenna has been introduced. Then the info of frequency and S parameters are collected and check out to seek out a far better algorithm that will be used for antenna designing purposes and parameter optimization. A spread of modeling techniques of AI like support vector regression, genetic algorithm has been used.
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Ranjan, P., Gupta, H., Sharma, A., Yadav, S., Potrebićc, M. (2022). Investigation and Optimization of Dielectric Resonator MIMO Antenna Using Machine Learning Approach. In: Dhawan, A., Mishra, R.A., Arya, K.V., Zamarreño, C.R. (eds) Advances in VLSI, Communication, and Signal Processing. Lecture Notes in Electrical Engineering, vol 911. Springer, Singapore. https://doi.org/10.1007/978-981-19-2631-0_56
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DOI: https://doi.org/10.1007/978-981-19-2631-0_56
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