Speaker: Shuping Dang

Talk Title: When Machine Learning Meets Wireless Communications

Abstract: To realize ever-increasing demands on various performance metrics and resolve new security challenges in wireless communications, machine learning has been regarded as an imperative tool to improve wireless communications in the pre-6G era. By learning through a large number of data samples, machine learning can produce a well-trained neural network model. Such a model is able to adapt a set of system parameters of wireless systems and/or assign wireless resources in an efficient manner to achieve better performance. In this talk, the basics of machine learning and two specific applications of machine learning for wireless communications, i.e., resource allocation and detection, will be introduced. Following these, related research challenges and future directions will also be shared and discussed.