内容簡介：高速移動場景、通感一體化典型場景等6G新特征引發了新波形技術——正交時頻空調制（OTFS）與仿射頻分複用（AFDM）的探索。此次報告，首先介紹OTFS與AFDM的基本原理以及各自的優缺點，然後說明性能提升的可行方案與多址接入形式，最後讨論面臨的技術挑戰。

報告人：溫淼文

報告人簡介：華南理工大學教授，博士生導師。主要從事無線通信與分子通信物理層技術研究。至今主持了3項國家自然科學基金項目，3項廣東省自然科學基金項目等。著有英文專著兩冊，發表IEEE Transactions論文100餘篇，谷歌引用逾萬次。獲IEEE通信學會亞太地區傑出青年學者獎（2020年），廣東省電子信息科學技術獎一等獎（2022年）等。現任IEEE Transactions on Wireless Communications, IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, IEEE Communications Letters期刊編委。曾任IEEE Transactions on Communications編委（2019-2024）。入選愛思唯爾中國高被引學者（2020-2023年）、第四屆中國科協青年人才托舉工程。

題目二：Quadratic Transform for Fractional Programming in Signal Processing and Machine Learning

内容簡介：Fractional programming (FP) is an invaluable optimization tool for communications and signal processing because many problems in these areas are fractionally structured, e.g., the signal-to-interference-plus-noise ratio (SINR) maximization for wireless transmission, the normalized cut maximization for graph clustering, the Cram\'{e}r-Rao bound (CRB) minimization for radar signal processing, the mean squared error minimization for pilot signal design, the margin maximization for support vector machine (SVM), and the age of information (AoI) minimization for sensor networks, etc. This feature article aims at a general introduction to the commonly used FP techniques upon which some latest advances in communications and signal processing are based. After briefly reviewing the classic FP theory, the article focuses on a recently developed method called the quadratic transform. We begin with the basic version of the quadratic transform considering the sum-of-ratios max FP, which the classic methods of Charnes-Cooper and Dinkelbach fail to address. The quadratic transform is further extended to a variety of other FP scenarios. For every FP method, in a top-down manner, we first present its general math framework and then specialize it to specific application. The article also gives insights into the quadratic transform by connecting it to other fundamental methods, such as the fixed-point iteration, weighted minimum mean squared error (WMMSE), majorization-minimization (MM), and gradient projection. Moreover, the convergence condition and the convergence rate are examined when we then turn our attention to the theoretical basis of the quadratic transform.

報告人：沈闓明

報告人簡介：Dr. Kaiming Shen received the B.Eng. degree from Shanghai Jiao Tong University in 2011, and the Ph.D. degree in electrical and computer engineering from the University of Toronto in 2020. Dr. Shen has been with the School of Science and Engineering at The Chinese University of Hong Kong (CUHK), Shenzhen, China as a tenure-track assistant professor since 2020. His research interests include optimization, wireless communications, information theory, and machine learning. Dr. Shen received the IEEE Signal Processing Society Young Author Best Paper Award in 2021, and the Frontiers of Science Award in 2024. Dr. Shen currently serves as an Editor for IEEE Transactions on Wireless Communications.

題目三：基于序号調制的下一代多址接入技術研究與挑戰

内容簡介：序号調制多址接入是第六代(6G)通信技術，具有顯著提高頻譜效率、能源效率、系統性能和支持大規模連接等優點，是傳統非正交多址(NOMA)技術的新擴展。本報告将首先介紹了序号調制多址接入的基本原理，然後研究了序号調制多址接入在車聯網、可重構智能表面網絡、協作網絡和安全網絡中的潛在應用，并重點介紹序号調制多址接入現有的挑戰和研究機會。

報告人：李俊

報告人簡介：韓國全北大學博士，廣州大學副教授，IEEE Senior Member，廣州市青年托舉人才，廣州市高層次人才青年後備人才，斯坦福大學全球前2%頂尖科學家。研究方向包括：序号調制、可重構智能表面等。主持國家自然科學基金青年項目、廣東省自然科學基金青年提升項目等，主要參與國家重點研發計劃課題、國家自然科學基金面上項目、廣東省科技計劃國際合作項目等。發表SCI/EI檢索論文80餘篇，授權國内發明專利10餘項，其中，ESI高被引論文6篇。擔任多個國際期刊編委和國際會議TPC成員。

時  間：2024年9月11日（周三）下午15：30開始

地  點：南海樓124室

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2024年9月9日