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This paper presents a new hybrid methodology based on sequential quadratic programming (SQP) and neural networks to optimize the radiation pattern of a MIMO antenna array designed for 5G/6G systems. Using Chebyshev synthesis of amplitude weights, phase optimization, and neural performance prediction, the radiation pattern characteristics must be optimized. The obtained results, simulated using MATLAB software, yield a high gain of 14.9 dBi and a directivity of 15.3 dB, and minimize the side lobe level. The proposed approach guarantees an efficiency of around 97%, demonstrating a significant reduction in side lobe levels and rapid adaptability.
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DOI: 10.1109/scc66964.2025.11424861
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