Machine Learning for Wireless Communications and Networking: Motivations, Case Studies, and Open Problems

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COMSOC Virtual Distinguished Lecture


While 5G deployment is being carried out in many places of the world, there has been great interest in the prospects of 5G beyond and the next generation. Among the various visions, a common theme is that artificial intelligence will play a key role, as evidenced by the great interest and advances in machine learning enabled wireless communications and networking. In this talk, we will discuss the motivation, potential, and challenges of incorporating machine learning in wireless communications and networking for 5G and beyond systems. 

We will start with two motivating examples, i.e., channel estimation and mobile edge computing, to show why machine learning could be helpful. We will share our experience of several case studies, including (i) a hybrid approach to the classical energy efficiency maximization problem, where traditional models could be used to train a deep learning model; (ii) data augmentation for convolutional neural network (CNN) based automatic modulation classification (AMC), where a conditional generative adversarial network (CGAN) is utilized to generate synthesized training data; and (iii) and an adaptive model for RFID-based 3D human skeleton tracking, which utilizes meta-learning and few-shot fine-tuning to achieve high adaptability to new environments. We will conclude this talk with a discussion of challenges and open problems. 



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  • Date: 28 Jun 2021
  • Time: 06:00 PM to 07:30 PM
  • All times are US/Mountain
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  • Denver, Colorado
  • United States

  • Co-sponsored by Kingston CA COMSOC Chapter
  • Starts 09 June 2021 10:00 AM
  • Ends 28 June 2021 12:00 PM
  • All times are US/Mountain
  • No Admission Charge


  Speakers

Dr. Shiwen Mao

Dr. Shiwen Mao

Biography:

Shiwen Mao [S'99-M'04-SM'09-F'19] received his Ph.D. in electrical engineering from Polytechnic University, Brooklyn, NY in 2004. He was a postdoc at Virginia Tech from 2004 to 2006, and joined Auburn University, Auburn, AL as an assistant professor of Electrical and Computer Engineering in 2006. He held the McWane Endowed Professorship from 2012 to 2015 and the Samuel Ginn Endowed Professorship from 2015 to 2020. Currently, he is a professor and Earle C. Williams Eminent Scholar Chair, and Director of the Wireless Engineering Research and Education Center at Auburn University. His research interest includes wireless networks, multimedia communications, and smart grid. He is on the editorial board of several IEEE and ACM journals. He is a Distinguished Lecturer of IEEE Communications Society and IEEE Council of RFID, and a Distinguished Speaker of IEEE Vehicular Technology Society. He received the IEEE ComSoc TC-CSR Distinguished Technical Achievement Award in 2019 and NSF CAREER Award in 2010. He is a co-recipient of the 2021 IEEE Communications Society Outstanding Paper Award and the IEEE Vehicular Technology Society 2020 Jack Neubauer Memorial Award.





Agenda

Virtual Distinguised Lecture by Dr. Shiwen Mao (Auburn University)

6pm (MT) - Introductions

6:10-7:15 - VDL Presentation

7:15-7:30 - Q&A



  Media

ComSoc-DL_Denvor-Kingston-Chapters 4.99 MiB