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2013.03.04

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Stochastic Geometry for Heterogeneous Wireless Networks: Theory & Applicationsv

 

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With the increase in data traffic driven by a new generation of wireless devices, data is expected to overwhelm cellular network capacity in the future. Heterogeneous cellular networks are a comprehensive approach to provide high cellular network capacity by overlaying conventional macrocell cellular architecture with heterogeneous architectural features such as small cellular access points (picocells and femtocells), low-power fixed relays, and distributed antennas. Heterogeneous cellular networks are expected to achieve higher data rates and better coverage by exploiting spatial reuse, while retaining at the same time the seamless connectivity and mobility of cellular networks. Inspired by the attractive features and potential advantages of heterogeneous cellular networks, their development and deployment is gaining momentum in the wireless industry and research communities during the last few years. It has also attracted the attention of standardization bodies such as 3GPP LTE-Advanced. However, heterogeneous cellular networks also come with their own challenges due to the presence of cross-tier and inter-tier interference, and there are significant technical issues that still need to be addressed for successful rollout and operation of these networks. As the spatial locations and interactions play a key role in such networks, mathematical techniques that incorporate and explicitly model the network geometry and the resulting aggregate interference have emerged as essential analytical tools.

This three-day tutorial course provides an overview of the theory and practical approaches for heterogeneous networks. We discuss how stochastic geometry can be used in order to provide key insights on the performance (such as coverage, area spectral efficiency, average rate) of such networks. After presenting the basic concepts and theoretical foundation from stochastic geometry and point process theory, we show how these mathematical tools can be used to analyze and design wireless networks with spatial randomness. Then, a brief overview of recent results on energy efficiency, multi-antenna communication, resource allocations, and cognitive access is provided.

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Marios Kountouris received the Dipl.-Ing. in Electrical and Computer Engineering from the National Technical University of Athens, Greece in 2002 and the M.S. and Ph.D. degrees in Electrical Engineering from the Ecole Nationale Supérieure des Télécommunications (ENST) Paris, France in 2004 and 2008, respectively. His doctoral research was carried out at Eurecom Institute, France, and it was funded by Orange Labs, France. From February 2008 to May 2009, he has been with the Department of ECE at The University of Texas at Austin as a research associate, working on wireless ad hoc networks under DARPAfs IT-MANET program. Since June 2009, he has been an Assistant Professor at the Department of Telecommunications at Supélec (Ecole Supérieure dfElectricité), France. Dr. Kountouris has published several papers and patents, all in the area of communications, wireless networking, and signal processing. He has served as technical program committee member for several top international conferences and has organized several workshops on heterogeneous and small cell networks. He is currently an Editor for the EURASIP Journal on Wireless Communications and Networking. He also received the Best Paper Award in Communication Theory Symposium at the IEEE Globecom conference in 2009. He is a Member of the IEEE and a Professional Engineer of the Technical Chamber of Greece.