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 코드번호 : 80 |
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| 발표자 : 윤성환 |
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| 소속 : UNIST |
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| 부서 : |
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| 직위 : 교수 |
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| 세션시간 : 9:00~10:50 |
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| 발표자약력 : |
I am currently working as an assistant professor at the Graduate School of AI & Department of Electrical Engineering at UNIST from Mar. 2020. I received my Ph.D. degree from the School of EE at KAIST, in Aug. 2017, under the supervision of Prof. Jaekyun Moon. Before joining UNIST, I was a postdoctoral researcher at KAIST from Sep. 2017 to Mar. 2020. My current research interests focus on the generalization of AI, including meta-learning, few-shot learning, continual learning, and federated learning. Also, AI-native intelligent communications and networks are another branch of my research topics. |
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| 강연요약 : |
In this talk, we will discuss RAN-agnostic communication that allows the coexistence of incompatible RANs within the same bandwidth, which is expected to be a key technology of future communications. To envision the concept of RAN-agnostic communication, we will introduce the AI-native algorithm for the blind recognition of the coexisting interference and the reinforcement learning-based coexistence of incompatible RANs, which yield a remarkable throughput gain beyond the conventional SNR-based coexistence. |
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