Performance Enhancement of 5G MIMO Antenna Utilizing Verifiable Convolutional Neural Network Optimized With Human Evolutionary Optimization Algorithm

ABSTRACT The evolution of 5G mmWave technology has significantly advanced wireless communication by enabling ultrafast data transmission and reduced latency. The integration of large‐scale multiple‐input multiple‐output (MIMO) systems has improved spectral efficiency and supported high user density for more robust and scalable network infrastructures. The interference and dynamic channel fluctuations present substantial obstacles in multicellular systems. User mobility complicates effective beam forming. In this manuscript, Performance Enhancement of 5G MIMO Antennas utilizing Verifiable Convolutional Neural Network optimized with Human Evolutionary Optimization Algorithm (5G‐MIMO‐VCNN‐HEOA) is proposed. The different antenna characteristics for the proposed antenna are analyzed by using optimization and parametric analysis through high frequency electromagnetic solver tool (Ansys HFSS). Then, the suppression of mutual coupling among MIMO antenna elements and enhancement of the isolation are achieved by using different techniques and the fabrication and verification of the proposed model by designing the prototype. Then, the Verifiable Convolutional Neural Network (VCNN) is used for design and development of MIMO Antenna in 5G applications. Human Evolutionary Optimization Algorithm (HEOA) is implemented for optimizing the VCNN hyper parameters. The proposed 5G‐MIMO‐VCNN‐HEOA accurately displays the outcomes of the design. The proposed technique is simulated, and efficiency is examined under several performance metrics like variance score, R square, mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). The proposed 5G‐MIMO‐VCNN‐HEOA approach attains 15.21%, 18.11%, and 16.22% lower MAE; 17.13%, 14.18%, and 14.25% lower MAPE; and 15.16%, 18.12%, and 21.23% lower MAE when compared with existing methods like broadband high gain performance MIMO antenna array in 5Gmm‐wave applications (BHG‐MIMO‐5G), compact and highly effective four‐port MIMO antenna directivity prediction for 5G mmwave applications (DP‐MIMO‐5G), and MIMO rectangular dielectric resonator antenna in 5G NR mmwave (MIMO‐RDRA‐5G), respectively.