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We have designed a deep neural network that could design an active metasurface antenna. The neural network provides a fast and accurate calculation of the radiation pattern of the metasurface. This process is unhindered by the miscalculation due to periodic approximations frequently used in calculating unit cells of the metasurface. Using the network, we have demonstrated the search for the highest antenna gains in five different directions. The results showed higher gains and lower side lobe levels than theoretical results.
Jaebum Noh andJunsuk Rho
"Deep learning enabled control of active metasurface antenna", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC126550S (5 October 2023); https://doi.org/10.1117/12.2676330
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Jaebum Noh, Junsuk Rho, "Deep learning enabled control of active metasurface antenna," Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC126550S (5 October 2023); https://doi.org/10.1117/12.2676330