29 اردیبهشت 1403
رضا عبدي قلعه

رضا عبدی قلعه

مرتبه علمی: دانشیار
نشانی: دانشگاه بناب، بناب، ایران
تحصیلات: دکترای تخصصی / فیزیک- اپتیک و لیزر
تلفن: 04137745000
دانشکده: دانشکده علوم پایه
گروه: گروه مهندسی اپتیک و لیزر

مشخصات پژوهش

عنوان
Realization of Index Modulation with Intelligent Spatiotemporal Metasurfaces
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
Deep learning, Index modulation, Inverse design, Spatiotemporal metasurfaces, Wireless communications.
پژوهشگران شیایو ژو (نفر اول)، چایو کیان (نفر دوم)، یوتیان جیا (نفر سوم)، جیتینگ چن (نفر چهارم)، یوان فانگ (نفر پنجم)، ژیشیانگ فان (نفر ششم به بعد)، جی ژانگ (نفر ششم به بعد)، دانگ دانگ لی (نفر ششم به بعد)، رضا عبدی قلعه (نفر ششم به بعد)، هونگ شنگ چن (نفر ششم به بعد)

چکیده

Advanced wireless communication with high spectrum efficiency and energy efficiency has always fascinated humanity, especially with the explosive increase of global mobile data services. Index modulation (IM) has recently been found to be a promising technique due to the transmission of additional data bits via the indices of the available transmit entities. However, the practical implementation of IM remains a great challenge associated with complicated radio components. Herein, IM with intelligent spatiotemporal metasurfaces is experimentally demonstrated. The spatiotemporal metasurfaces provide a natural and versatile platform to achieve IM in a green and lightweight manner. The whole system is driven by a built-in inverse-design agent that automates spatiotemporal metasurfaces to cater to diverse application demands. In doing so, how to mitigate the inherent nonuniqueness issue and how to setup the input target from practical scenes are concretely discussed. In the microwave experiment, the spatiotemporal metasurfaces are fabricated and demonstrate the feasibility by harvesting two harmonic waves as communication channels. An intelligent electromagnetic platform that can manipulate electromagnetic waves in multidimensions is provided, meriting other numerous intelligent meta-devices that avoid overburdening data analysis networks in smart cities of the future.