AI-Aided Design for Next Generation of Wireless Communication Systems

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AI-Aided Design for Next Generation of Wireless Communication Systems

Recent advancements in artificial intelligence (AI) motivates wireless communication engineers to deploy machine and deep learning (DL) tools in different layers of communication protocol stacks. Among others, there has been a surge of interest in the applications of AI in the physical (PHY) layer of wireless communication systems. The basic idea behind the application of AI in PHY layer design is to improve the end-to-end performance, e.g., increasing data throughput, improving energy efficiency, reducing error rate, etc. and to alleviate the real-time computational complexity over conventional design approaches. In general, the conventional design of transmitter and receiver is block based, where each block can perform its task optimally and often efficiently. 



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  • Date: 30 Nov 2021
  • Time: 06:00 PM to 07:30 PM
  • All times are America/Denver
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  • Denver

  • Starts 05 November 2021 09:02 AM
  • Ends 30 November 2021 12:00 PM
  • All times are America/Denver
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  Speakers

Dr. Imtiaz Ahmed of University of Maryland

Topic:

AI-Aided Design for Next Generation of Wireless Communication Systems

Recent advancements in artificial intelligence (AI) motivates wireless communication engineers to deploy machine and deep learning (DL) tools in different layers of communication protocol stacks. Among others, there has been a surge of interest in the applications of AI in the physical (PHY) layer of wireless communication systems. The basic idea behind the application of AI in PHY layer design is to improve the end-to-end performance, e.g., increasing data throughput, improving energy efficiency, reducing error rate, etc. and to alleviate the real-time computational complexity over conventional design approaches. In general, the conventional design of transmitter and receiver is block based, where each block can perform its task optimally and often efficiently. However, block-based design approach may not guarantee an end-to-end optimal performance in error rate, throughput, energy efficiency, etc. for different communication systems. Furthermore, some of the existing robust signal processing algorithms often entail high computational complexity despite providing optimal and robust performance. These findings altogether motivated the wireless communication engineers to adopt AI tools to push the boundaries of the error rate and throughput performances while limiting the operational and computational complexity within a certain threshold. In this talk, we will discuss on a few cutting-edge problems of fifth generation (5G) and beyond 5G cellular communication systems and will observe how different AI tools can help us to solve these problems efficiently. Furthermore, I will  briefly discuss about other projects that I have been working on and some future research topics

Biography:

Dr. Imtiaz Ahmed is an Assistant Professor in the department of Electrical Engineering and Computer Science at Howard University, Washington, DC, USA. He works in the areas of wireless communications, signal processing, and computer networks. He did his Ph.D. in Electrical and Computer Engineering (ECE) from the University of British Columbia (UBC), Vancouver, BC, Canada in 2014. He then worked as a postdoctoral fellow at McGill University during 2014-15. Dr. Ahmed worked as a wireless systems engineer in Intel Corporation, San Diego, California for more than 3 years. He worked in developing performance simulation framework and baseband demodulation algorithms for LTE and 5G NR in Intel. He also worked as a visiting staff engineer in Oppo US research facility. Before joining Howard University, he worked as an Assistant Professor at Marshall University, Huntington, WV.

 





Agenda

6pm - Introductions and COMSOC Chapter News

6:15 - Volunteer Discussion

6:30 - Feature Talk

7:15pm Q&A