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ESE Fall Seminar – “Stochastic Geometry for Networks”
November 17, 2023 at 11:00 AM - 12:00 PM
Stochastic geometry is a branch of probability theory that deals with the study of random spatial patterns. Random point patterns, termed point processes, are the most basic such objects that appear in numerous applications. After presenting a brief introduction to point processes, we will present our work on the stochastic modeling and analysis of wireless cellular networks, which departs from the conventional approaches based on deterministic models. In addition to results related to key wireless metrics, such as coverage and rate, we will also discuss new results related to Poisson point processes that were inspired by this work. Building on this discussion, we will introduce line processes, which along with point processes, allow us to model networks on the lines (such as transportation networks). After providing a brief historical perspective and the construction of line processes, we will define a doubly stochastic point process by placing an independent Poisson point process on each line of the Poisson line process, which we term the Poisson Line Cox Process. We will discuss key properties and applications of this point process to vehicular and transportation networks. We will also briefly discuss new contributions related to path distance distributions that were inspired by this work. In the last segment, we will discuss our ongoing work on developing a new mathematical framework to study landmark-based geolocation by modeling generic landmarks (such as trees and lampposts) as point processes. In addition to presenting our early results, we will also discuss possible connections of this approach to information and coding theory.
If you are interested in more details, please refer to the following monographs. They are accessible free of cost from most university campuses. Monograph [M1] summarizes our work on cellular networks and is written to be the first introduction to this area. Monograph [M2] summarizes our work on line processes and their applications to vehicular networks.
[M1] An Introduction to Cellular Network Analysis Using Stochastic Geometry: https://link.springer.com/book/10.1007/978-3-031-29743-4
[M2] Poisson Line Cox Process: Foundations and Applications to Vehicular Networks: https://link.springer.com/book/10.1007/978-3-031-02379-8
Harpreet Dhillon
Professor of Electrical and Computer Engineering, Virginia Tech
Harpreet S. Dhillon received the B.Tech. degree in electronics and communication engineering from IIT Guwahati in 2008, the M.S. degree in electrical engineering from Virginia Tech in 2010, and the Ph.D. degree in electrical engineering from the University of Texas at Austin in 2013. After serving as a Viterbi Postdoctoral Fellow at the University of Southern California for a year, he joined Virginia Tech in 2014, where he is currently a Professor of electrical and computer engineering, a Professor of Mathematics (by courtesy), the chair of the communications area, the Associate Director of Wireless@VT research group, and the Elizabeth and James E. Turner Jr. ’56 Faculty Fellow. His research interests include communication theory, wireless networks, stochastic geometry, geolocation, and machine learning. He has received six best paper awards including the 2014 IEEE Leonard G. Abraham Prize, the 2015 IEEE ComSoc Young Author Best Paper Award, and the 2016 IEEE Heinrich Hertz Award. He has also received Early Achievement Awards from three IEEE ComSoc Technical Committees, namely, the Communication Theory Technical Committee (CTTC) in 2020, the Radio Communications Committee (RCC) in 2020, and the Wireless Communications Technical Committee (WTC) in 2021. He was named the 2017 Outstanding New Assistant Professor, the 2018 Steven O. Lane Junior Faculty Fellow, the 2018 College of Engineering Faculty Fellow, and the recipient of the 2020 Dean’s Award for Excellence in Research by Virginia Tech. He has served as the TPC Co-chair for IEEE WCNC 2022 and as a symposium TPC Co-chair for many IEEE ComSoc conferences. He has also served on the Editorial boards of several IEEE journals with his current appointments being on the Executive Editorial Committee for IEEE Transactions on Wireless Communications and as a Senior Editor for IEEE Wireless Communications Letters. He is an IEEE Fellow, an AAIA Fellow, and a Clarivate Analytics (Web of Science) Highly Cited Researcher.