講座名稱：Wireless Federated Learning for 6G Networks

講座人：George K. Karagiannidis 教授

講座時間：5月31日16:00

講座地點：Zoom會議直播（ID: 534 960 4445 密碼： 897420）

講座人介紹：

George K. Karagiannidis（IEEE研究員）現(xiàn)任希臘塞薩洛尼基亞里士多德大學(xué)電氣與計算機工程系教授，并且是無線通信與信息處理集團的和負(fù)責(zé)人。他的研究興趣是廣泛的數(shù)字通信系統(tǒng)和信號處理領(lǐng)域，重點是無線通信、光無線通信、無線能量傳輸與應(yīng)用、生物醫(yī)學(xué)工程通信與信號處理。Dr. Karagiannidis是《IEEE通訊快報》的主編，目前擔(dān)任《IEEE通訊學(xué)會開放期刊》的副主編。Dr. Karagiannidis是電氣工程所有領(lǐng)域的高引用作者之一，在2015-2020年連續(xù)六年被Clarivate Analytics評為科學(xué)網(wǎng)高引用研究員。

講座內(nèi)容：

Conventional machine learning techniques are conducted in a centralized manner. Recently, the massive volume of generated wireless data, the privacy concerns and the increasing computing capabilities of wireless end-devices have led to the emergence of a promising decentralized solution, termed as Wireless Federated Learning (WFL). In this talk, the application of WFL in 6G networks will be presented. After analyzing the key concepts of WFL, we will discuss the core challenges of WFL imposed by the wireless environment. Finally, we shed light to the future directions of WFL, aiming to compose a constructive integration of FL into the future wireless networks. Finally, a novel communication protocol for WFL networks, that is based on NOMA will be introduced and optimized.

主辦單位：通信工程學(xué)院