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SUMMARY:On-Chip Self-Interference Cancellation for Full Duplex Radios and 
 Other Applications
DTSTART:20220331T170000
DTEND:20220331T180000
DTSTAMP:20260407T081252Z
UID:4a240e5513c221c1e58040c24615f26161fe375b45018bf22a626ec6
CATEGORIES:Conferences - Seminars
DESCRIPTION:Jacques C. Rudell\, University of Washington\, Seattle\, WA\nA
 bstract - Several efforts of the last decade have demonstrated the ability
  of a radio transceiver to simultaneously transmit and receive using the s
 ame frequency band – this is commonly referred to as in-band full duplex
  communication. Numerous performance challenges are presented to the analo
 g\, mixed-signal and digital IC designers when attempting to realize an in
 tegrated full duplex radio. Specifically\, the strong transmitter self-int
 erference will degrade the RX SNDR which is impacted by a number of perfor
 mance issues including receiver linearity and noise figure degradation\, r
 eciprocal mixing\, demand for high cancellation bandwidth and depth\, in a
 ddition to algorithms to adapt and optimize suppression circuits in real-t
 ime. Although the last few years research on circuits and systems which en
 able full duplex radio communication have been widely published\, the topi
 c of self-interference cancellation is by no means limited to wireless com
 munication systems. In fact\, many other commercial and biomedical applica
 tions benefit from the ability to suppress transmitted/emitted signals in 
 a system that is attempting simultaneously receive another signal. Example
 s include neural interfaces\, radar\, wireline communication and medical i
 maging. This presentation will begin by exploring the similarity and diffe
 rences between the problem of self-interference/signal cancellation in ver
 y diverse applications from the perspective of noise\, linearity\, cancell
 ation bandwidth\, convergence of adaptation algorithms and suppression dep
 th. Then two examples of integrated self-interference cancellation will be
  presented\,  for neural interfaces and wireless communication which repr
 esent the state-of-the-art with respect to linearity\, noise and the abili
 ty to adapt cancellation filters on chip in real-time.\n\nJacques “Chris
 ”tophe Rudell received degrees in electrical engineering from the Univer
 sity of Michigan (BS)\, and UC Berkeley (MS\, PhD). After finish his PhD\,
  he worked for several years as an RF IC designer at Berkana Wireless (now
  Qualcomm)\, and Intel Corporation.  In January 2009\, he joined the facu
 lty at the University of Washington\, Seattle\, where he is now an Associa
 te Professor of Electrical and Computer Engineering. He is also a member o
 f the Center for Neural Technology (CNT) and serves as the co-director of 
 the Center for Design of Analog-Digital Integrated Circuits (CDADIC).  Wh
 ile a PhD student at UC Berkeley\, Dr. Rudell received the Demetri Angelak
 os Memorial Achievement Award\, a citation given to one student per year b
 y the EECS department. He has twice been co-recipient of the best paper aw
 ards at the IEEE International Solid-State Circuits Conference\, the first
  of which was the 1998 Jack Kilby Award\, followed by the 2001 Lewis Winne
 r Award. He received the 2008 ISSCC best evening session award\, and best 
 student paper awards at the 2011 and 2015 RFIC Symposium. Chris is the rec
 ipient of the National Science Foundation (NSF) CAREER Award. Dr. Rudell s
 erved on the ISSCC technical program committee (2003-2010)\, and on the IE
 EE Radio Frequency Integrated Circuits (RFIC) Symposium steering committee
  (2002-2013)\, where he was the 2013 General Chair. He was an Associate Ed
 itor for the IEEE Journal of Solid-State Circuits (2009-2015). At present\
 , he serves on the technical program committees of the IEEE European Solid
 -State Circuits Conference (ESSCirC) and the IEEE Custom Integrated Circui
 ts Conference (CICC).
LOCATION:INF 328 https://plan.epfl.ch/?room==INF%20328 https://epfl.zoom.u
 s/j/66324727001?pwd=WnBaTDFYQmdpOVE0V3ZiRVJCZDloQT09
STATUS:CONFIRMED
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