主题：From Cognitive to Docitive Radios: The Role of Machine Learning in Intelligent Wireless Multimedia Networks

主讲人：Fei Hu

时间：2015年7月14日（周二），下午14:00-16:00

地点：交通运输工程学院103报告厅

主讲人简介：

Fei Hu博士目前担任美国Alabama大学（主校区）电子计算机工程学院教授。于1999年获得同济大学信号处理博士学位,师从张树京先生，2002年获得美国纽约克拉克森大学电子计算机工程博士学位。目前已经发表200余篇期刊/会议论文、书籍、专书章节。其研究内容获得美国国家科学基金会，美国国防部，思科有限公司，Sprint通信有限公司等其他机构部分支持，并担任过无线通信国际会议主席。

Hu博士研究方向为：（1）安全：如何解决复杂无线或有线网络中的不同网络攻击。目前主要重点研究网络物理系统安全和MAC安全问题；（2）信号：主要指智能信号处理，运用机器学习算法处理感知信号，智能提取信号图形（信号识别）；（3）传感器：包括为传感器设计和无线传感器网络问题。

主讲内容简介：

In recent years, multimedia wireless transmissions have become a rapidly growing field and have received increasing attentions. Enabling multimedia communications over wireless networks to reach their full potential is a challenging task, due to the complex and time-varying features of wireless networks. This dissertation presents intelligent multimedia wireless transmission schemes that enable prioritized multimedia transmission over various wireless networks, using advanced wireless networking techniques and cutting-edge machine learning techniques. Particularly, cross-layer design for multimedia transmission, spectrum handoff for cognitive radio networks, and multi-channel wireless mesh networks with multi-beam antennas are addressed for the improvement of multimedia wireless transmission. Non-linear optimization is utilized for cooperative design of cross-layer wireless transmission; manifold learning is explored for dimensional reduction and user similarity measurement. Mixed preemptive resume priority and non-preemptive resume priority M/G/1 queueing models are proposed to for modeling the spectrum usage behavior for prioritized multimedia applications in wireless networks. Reinforcement learning is adapted to enable users to learn from their experience and the environment and apprenticeship learning is adapted to enable users to learn from other experienced users in a similar wireless network environment. These proposed transmission schemes have one or multiple advantages as: (1) efficiently uses available wireless resources to achieve the optimum transmission performance by means of cooperative design between different wireless layers and/or different users; (2) explicitly considers complex wireless communication conditions; (3) enables prioritized multimedia applications through allocating more wireless resources to applications with a higher priority; (4) opportunistically optimizes spectrum usage through a hybrid queueing model that manages all the spectrum usage in the network; (5) enables users to conduct spectrum behavior intelligently through learning from experience of their own as well as of other experienced users.

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