报告题目：80 Years of Research on Sum of Lognormal Random Variables: Recent Breakthroughs and Applications in Wireless Communications

主讲人：Prof. Julian Cheng

单位：The University of British Columbia

时间：9月22日10:00

腾讯ID：471-655-996

摘要：The distribution for the sum of lognormal random variables finds applications in many science and engineering disciplines, and it is particularly important for wireless communication engineers. However, the distribution for the simplistic sum of independent lognormal random variables is analytically intractable. The problem is more challenging for a sum of correlated lognormal random variables with non-identical parameters. In 1934, Wilkinson from Bell Telephone Labs first studied this problem in an unpublished work. Since then, various approximations have been proposed in the literature. All these approximations fail to accurately quantify the left tail (or right tail) behavior of the distribution function of a sum of lognormal random variables. In this talk, in the context of diversity receptions over lognormal fading channels, we first present that a Marcum Q-function can accurately represent the left tail distribution of the sum of independent lognormal random variables. The proposed analytical result outperforms all existing well-known sums of lognormal approximations. Using a different approach, we extend the problem to a sum of correlated and non-identically lognormal random variables and show that another Marcum Q-function can again represent its left-tail distribution. Our study reveals several new and surprising engineering insights into the transmission characteristics over the lognormal fading channels. For example, for the dual-branch case, we show that the outage performance of negatively correlated lognormal channels is better than that of independent lognormal channels. We also show that one of the two lognormal channels can contribute no performance gain to the diversity reception systems under certain parameter conditions. This implies that one link can be discarded without causing asymptotic performance loss. These new findings can guide communication engineers to design better systems for transmission over the lognormal fading channels.

简介：Julian Cheng received his Ph.D. in electrical engineering from the University of Alberta, Edmonton, AB, Canada. He is a Full Professor in the School of Engineering, Faculty of Applied Science, at The University of British Columbia, Okanagan campus in Kelowna, BC, Canada. His research interests include applications of deep learning for wireless communication systems and wireless networks, and optical wireless communications. Dr. Cheng has been a technical program committee member for many IEEE conferences and workshops. He co-chaired the 12th Canadian Workshop on Information Theory (CWIT 2011) in Kelowna, Canada. He also co-chaired the 2021 Communication Theory Workshop. He served as an Area Editor forIEEE Transactions on Communications(2018-2023). Previously, he was an Associate Editor forIEEE Transactions on Communications,IEEE Transactions on Wireless Communications, andIEEE Communications Letters. He was a past Guest Editor for a special issue of the IEEE Journal on Selected Areas in Communications on optical wireless communications. He also served as the President of the Canadian Society of Information Theory (2017-2021). From 2022 to 2023, he was a Visiting Professor in the Department of Electrical Engineering at Stanford University. Dr. Cheng has recently been elected to serve as the Chair of the Radio Communication Committee of the IEEE Communication Society. He is also a Fellow of IEEE.