智慧城市感知与计算重点实验室

【海韵讲座】2017年第39期-Structured Signal Processing for Massive IoT Networks


 

题目:Structured Signal Processing for Massive IoT Networks

主讲人:石远明,研究员

上海科技大学信息科学与技术学院

时间:2019年7月11日 下午2:30

地点:海韵行政楼C510

报告摘要:The significant success of wireless technologies has been achieved towards connecting sensors, machines and robots for intelligent applications, thereby establishing the bedrock for the Internet-of-Things (IoT). The massive IoT connectivity will bring remarkable benefits to our lives, e.g., smart home, smart city, healthcare, transportation system, etc. A typical IoT connectivity involves a massive number of machine-type communication devices, where a large number of devices need to be connected sporadically, i.e., only a subset of users are active at any given time. Furthermore, for the emerging Tactile Internet services, e.g., immersive virtual reality and cooperative automated driving, the additional haptic information needs to be further delivered in ultra-low latency communications. It is thus crucial to support massive connectivity with low-latency communications to satisfy the diversified and tight traffic requirements in the IoT networks. The aim of this tutorial is to present recent advances in sparse and low-rank signal processing, as well as the unlabeled sensing techniques for massive device connectivity with low-latency communications and header-free communications, with a comprehensive coverage including modeling, algorithm design, statistical and geometric analysis. Through typical examples, including taming nonconvexity in the generalized sparse and low-rank models, the powerfulness of this set of tools will be demonstrated, and their abilities in supporting low-latency and massive connectivity be highlighted.

报告人简介:石远明博士于2011年7月获得清华大学电子工程学士学位(2007-2009学年于“数学物理基础科学班”培养);2015年8月获得香港科技大学电子及计算机工程博士学位,师从Khaled B. Letaief教授。他于2015年9月加入上海科技大学信息科学与技术学院任助理教授/研究员,2019年1月任上海科技大学信息科学与技术学院常任副教授/研究员。他于2016年秋季学期任加州大学伯克利分校访问教授,访问统计机器学习领域Martin J. Wainwright教授。他的研究成果荣获2016 IEEE通信学会马可尼最佳论文奖(无线通信领域最重要学术奖项之一),以及2016 IEEE信号处理学会最佳青年作者论文奖。他主要的研究方向为运筹优化、高维统计、机器学习、信号处理,及其在无线通信、量化金融中的应用。

邀请人:信息与通信工程系 付立群教授