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ku酷游app入口,亚博app,皇冠hg666体育:Faster, Smarter, Greener: Intelligent Reflecting Surface for 6G

来源:通信工程ku酷游app入口,亚博app,皇冠hg666体育          点击:
报告人 Qingqing Wu 时间 11月10日9:30
地点 腾讯皇冠hg666体育议直播 报告时间

讲座名称:Faster, Smarter, Greener: Intelligent Reflecting Surface for 6G

讲座人:Qingqing Wu

讲座时间:11月10日9:30

讲座地点:腾讯皇冠hg666体育议直播(皇冠hg666体育议ID:326 469 806 皇冠hg666体育议密码:123456)

 

讲座人介绍:

Qingqing Wu (S’13-M’16) received the B.Eng. and the Ph.D. degrees in Electronic Engineering from South China University of Technology and Shanghai Jiao Tong University (SJTU) in 2012 and 2016, respectively. He is currently an assistant professor in the Department of Electrical and Computer Engineering at the University of Macau, China, and affiliated with the State key laboratory of Internet of Things for Smart City. He was a Research Fellow in the Department of Electrical and Computer Engineering at National University of Singapore. His current research interest includes intelligent reflecting surface (IRS), unmanned aerial vehicle (UAV) communications, and MIMO transceiver design. He has published over 70 IEEE journal and conference papers, including 15 ESI highly cited papers, 3 ESI hot papers, and 12 IEEE ComSoc Best Readings. His research has attracted about 5000 Google Scholar citations.

 

讲座内容:

In this talk, we introduce a new wireless research paradigm by employing a massive number of low-cost passive reflecting elements with controllable phase, named intelligent reflecting surface (IRS), which is able to smartly change the wireless signal propagation to enable various functions such as beamforming and interference nulling/cancelation. We illustrate the main applications of IRS in achieving spectrum and energy efficient as well as secure and sustainable wireless networks in the future, and its advantages as compared to existing technologies such as massive MIMO and active relaying. We then present the signal and channel model of IRS by taking into account its hardware limitation in practice. Next, we focus on discussing the main design challenges in IRS-aided wireless networks, including joint active and passive beamforming optimization, channel estimation, etc., and highlight important directions for future work.

 

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