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Stochastic Geometry Modeling and Optimization of Cellular Networks – Bridging Accuracy and Complexity

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Friday, 5. October 2018, 13:30
Category: Lectures & Presentations | created by This email address is being protected from spambots. You need JavaScript enabled to view it.

In the past few years, there have been many efforts to develop analytical methodologies for optimizing very ultra-dense networks, especially by using the mathematical tools of stochastic geometry and point processes. At the time of writing, however, we have understood that many proposed approaches have (at least one of the) two main limitations that
make them unsuitable for optimizing cellular networks:

  • Limitation 1: Due to the analytical complexity of the problem at hand, key system approximations need to be applied, which make the resulting analytical frameworks unsuitable for system optimization (relevant design
    parameters are not taken into account).
  • Limitation 2: Realistic network models result in analytical frameworks that are too complex to gain any insights on the fundamental properties of the networks and to perform large-scale optimization (the objective functions are non-convex and have multiple integrals).

In this talk, I will describe two recent approaches that I have recently
proposed to overcome the two limitations mentioned above:

  • M. Di Renzo et al., “System-Level Modeling and Optimization of the Energy Efficiency in Cellular Networks - A Stochastic Geometry Framework”, IEEE Transactions on Wireless Communications, Vol. 17, No. 4, pp. 2539-2556, April 2018.
  • M. Di Renzo et al., “Inhomogeneous Double Thinning - Modeling and
    Analysis of Cellular Networks by Using Inhomogeneous Poisson Point
    Processes”, IEEE Transactions on Wireless Communications, Vol. 17,
    No. 8, pp. 5162-5182, August 2018.

In the first paper, I have introduced a new analytical formulation of the coverage probability that I proved to be accurate and suitable for systemlevel optimization. In the second paper, I have introduced a new approach based on the theory of inhomogeneous Poisson point processes for modeling and analyzing communication networks with spatial correlations (either attractive or repulsive).


Marco Di Renzo (S’05–AM’07–M’09–SM’14) received the Laurea degree (cum laude) and the Ph.D. degree in electrical engineering from the University of L’Aquila, Italy, in 2003 and 2007, respectively, and the D.Sc.
degree (Habilitation à diriger des recherches) from the University of Paris-Sud, France, in 2013. Since 2010, he has been a CNRS Associate Professor (Chargé de Recherche Titulaire CNRS) with the Laboratory of Signals and Systems, Paris-Saclay University-CNRS, CentraleSupélec, University of Paris-Sud, Paris, France. His research interests include wireless communications, communication theory, and stochastic geometry. He currently serves as an Editor of the IEEE  Communications Letters and the IEEE Trans. on Communications. He is a Distinguished Lecturer of the Communications Society and the IEEE Vehicular Technology Society. He is a recipient of several research distinctions, which include the 2013 Network of Excellence NEWCOM# Best Paper Award, the 2013 IEEE-COMSOC Best Young Researcher Award for Europe, Middle East and Africa (EMEA Region), the 2015 IEEE Jack Neubauer Memorial Best System Paper Award, the 2015 Distinguished Visiting Fellow of the Royal Academy of Engineering, U.K., the 2015-2018 CNRS Award for Excellence in Research and in Advising Doctoral Students, the 2016 MSCA Global Fellowship, as well as 6 Best Paper Awards at IEEE conferences. He is the project coordinator of two EU-funded multi-partner projects (ETN-5Gwireless and ETN-5Gaura).

Location Science Park 2, S2 048, JKU Linz
Contact Andreas Springer: This email address is being protected from spambots. You need JavaScript enabled to view it.