Yindi Jing received the B.Eng. and M.Eng. degrees in automatic control from the University of Science and Technology of China, Hefei, China, in 1996 and 1999, respectively. She received the M.Sc. degree and the Ph.D. in electrical engineering from California Institute of Technology, Pasadena, CA, in 2000 and 2004, respectively. From October 2004 to August 2005, she was a postdoctoral scholar at the Department of Electrical Engineering of California Institute of Technology. Since February 2006 to June 2008, she was a postdoctoral scholar at the Department of Electrical Engineering and Computer Science of the University of California, Irvine. In 2008, she joined the Electrical and Computer Engineering Department of the University of Alberta, where she is currently an associate professor.
She was an Associate Editor for the IEEE Transactions on Wireless Communications 2011-2016 and currently serves as a Senior Area Editor for IEEE Signal Processing Letters. She has been a member of the IEEE Signal Processing Society Signal Processing for Communications and Networking (SPCOM) Technical Committee since 2015 and a member of the NSERC Discover Grant Evaluation Group for Electrical and Computer Engineering since 2017.
Dr. Jing's research interests are in wireless communications. The long-term objective is to design wireless networks that can fulfill current and future needs, more specifically, to explore rudimentary transceiver schemes that allow seamless and high quality data exchange, to support concurrent communications of a large volume of users, and to understand the fundamental laws of complicated wireless systems and the effects of practical hardware and software limits.
Deterministic and probabilistic models. Basics of probability theory: random experiments, axioms of probability, conditional probability and independence. Discrete and continuous random variables: cumulative distribution and probability density functions, functions of a random variable, expected values, transform methods. Pairs of random variables: independence, joint cdf and pdf, conditional probability and expectation, functions of a pair of random variables, jointly Gaussian random variables. Sums of random variables: the central limit theorem; basic types of random processes, wide sense stationary processes, autocorrelation and crosscorrelation, power spectrum, white noise. Prerequisite: MATH 209. Credit may be obtained in only one of ECE 342 or E E 387.Winter Term 2021