摘要:
Modern networks will heavily be heterogeneous in nature. In order to optimize resources and mitigate interference it is often essential for radio devices to cooperate with each other. Cooperation in the presence of channel/system state information uncertainties is a highly challenging problems for which no simple mathematically based robust solution exist, at least in most cases. In this talk, we describe a machine learning approach this problem where so called Team deep learning networks (Team-DNN) are exploited to learn how can radio node message each other relevant information and take appropriate tranmission decisions. We consider a power control example as our main application example in this presentation.
该讲座为前沿讲座，欢迎全校师生踊跃参加。
附主讲人简介：
David Gesbert (IEEE Fellow) is Professor and Head of the Communication Systems Department, EURECOM. He obtained the Ph.D degree from Ecole Nationale Superieure des Telecommunications, France, in 1997. From 1997 to 1999 he has been with the Information Systems Laboratory, Stanford University. He was then a founding engineer of Iospan Wireless Inc, a Stanford spin off pioneering MIMO-OFDM (now Intel). Before joining EURECOM in 2004, he has been with the Department of Informatics, University of Oslo as an adjunct professor. D. Gesbert has published about 270 papers and 25 patents, some of them winning the 20015 IEEE Best Tutorial Paper Award (Communications Society), 2012 SPS Signal Processing Magazine Best Paper Award, 2004 IEEE Best Tutorial Paper Award (Communications Society), 2005 Young Author Best Paper Award for Signal Proc. Society journals, and paper awards at conferences 2011 IEEE SPAWC, 2004 ACM MSWiM. He has been a Technical Program Co-chair for ICC2017. He was named a Thomson-Reuters Highly Cited Researchers in Computer Science. Since 2015, he holds the ERC Advanced grant "PERFUME" on the topic of smart device Communications in future wireless networks.
He held visiting professor positions in KTH (2014) and TU Munich (2016). Since 2017 he is also a visiting Academic Master within the Program 111 at the Beijing University of Posts and Telecommunications as well as as a member in the Joint BUPT-EURECOM Open5G Lab. He is a board member of the OpenAirInterface (OAI) Software Alliance.
