MIMO Antenna Optimization: From Configuring Structure to Sizing with the aid of Neural Network

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IEEE

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info:eu-repo/semantics/closedAccess

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In the last decades, multiple input, multiple output (MIMO) antenna designs play important role and this trend will continue in next-generation mobile technologies. Designing high-performance MIMOs is significant since these types of antennas include multiple radiating elements. For these complex configurations, intelligent-based optimization methods can tackle the problem of designing. This paper devotes to designing and optimizing the configuration and design parameters of a MIMO antenna, respectively. Firstly bottom-up optimization (BUO) approach is executed successfully for building the general topology of the MIMO antenna and afterwards, artificial neural network (ANN) is utilized for obtaining the design parameters with the optimal values. The proposed approach results in generating the optimal topology with size values in a reduced effort by designers. The presented approach is applied to designing a MIMO antenna operating from 13.7 GHz to 29 GHz.

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16th IEEE Dallas Circuits and Systems Conference (DCAS) -- APR 14-16, 2023 -- Univ N Texas, Denton, TX

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Multiple Input, Multiple Output (Mimo), Bottom-Up Optimization (Buo), Artificial Neural Network (Ann)

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2023 Ieee 16th Dallas Circuits and Systems Conference, Dcas

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