
H. Vincent Poor
教授
Department of Electrical and Computer Engineering
School of Engineering and Applied Science, Princeton University;Center for Statistics and Machine Learning, Princeton University;Andlinger Center for Energy and the Environment, Princeton University;Princeton Environmental Institute, Princeton University;Department of Operations Research & Financial Engineering, Princeton University
关注
立即认领
分享
关注
立即认领
分享
基本信息
浏览量:10856

个人简介
My current research activities are focused on advances in several fields of rapid technology development, notably wireless networks and energy systems, and on the fundamentals underlying them, including information theory, machine learning and network science.
The dramatic increase in demand for new capacity and higher performance has been a major issue in the design and deployment of contemporary wireless networks. The development of these capabilities is severely limited by the scarcity of two of the principal resources in wireless networks: energy and bandwidth. Emerging generations of wireless standards and applications such as Internet of Things (IoT) are addressing these issues through the use of techniques such as cooperative communications, spectrum sharing, energy harvesting, cloud processing and densification of infrastructure. One focus of our recent work has addressed the fundamental limits of such techniques through information theoretic and related analyses of high-reliability and low-latency communications. Another focus has been on addressing the fundamental ability of the physics of the radio channel to provide security in data transmission, and the development of codes and other methods to exploit this capability. A further issue that we are exploring is the use of wireless networks as platforms for machine learning, through the development of federated and decentralized learning algorithms and the study of their interactions with the wireless medium.
The dramatic increase in demand for new capacity and higher performance has been a major issue in the design and deployment of contemporary wireless networks. The development of these capabilities is severely limited by the scarcity of two of the principal resources in wireless networks: energy and bandwidth. Emerging generations of wireless standards and applications such as Internet of Things (IoT) are addressing these issues through the use of techniques such as cooperative communications, spectrum sharing, energy harvesting, cloud processing and densification of infrastructure. One focus of our recent work has addressed the fundamental limits of such techniques through information theoretic and related analyses of high-reliability and low-latency communications. Another focus has been on addressing the fundamental ability of the physics of the radio channel to provide security in data transmission, and the development of codes and other methods to exploit this capability. A further issue that we are exploring is the use of wireless networks as platforms for machine learning, through the development of federated and decentralized learning algorithms and the study of their interactions with the wireless medium.
研究兴趣
论文共 2603 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
arxiv(2023)
引用0浏览0引用
0
0
IEEE Communications Surveys & Tutorialsno. 1 (2023): 251-288
arxiv(2023)
引用0浏览0EIWOS引用
0
0
arxiv(2023)
引用0浏览0引用
0
0
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023)
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn