Section: Research Program

Information Theory and Wireless Networks

Classical models of stochastic geometry (SG) are not sufficient for analyzing wireless networks as they ignore the specific nature of radio channels.

Consider a wireless communication network made of a collection of nodes which in turn can be transmitters or receivers. At a given time, some subset of this collection of nodes simultaneously transmit, each toward its own receiver. Each transmitter–receiver pair in this snapshot requires its own wireless link. For each such wireless link, the power of the signal received from the link transmitter is jammed by the powers of the signals received from the other transmitters. Even in the simplest model where the power radiated from a point decays in some isotropic way with Euclidean distance, the geometry of the location of nodes plays a key role within this setting since it determines the signal to interference and noise ratio (SINR) at the receiver of each such link and hence the possibility of establishing simultaneously this collection of links at a given bit rate, as shown by information theory (IT). In this definition, the interference seen by some receiver is the sum of the powers of the signals received from all transmitters excepting its own. The SINR field, which is of an essentially geometric nature, hence determines the connectivity and the capacity of the network in a broad sense. The essential point here is that the characteristics and even the feasibilities of the radio links that are simultaneously active are strongly interdependent and determined by the geometry. Our work is centered on the development of an IT-aware stochastic geometry addressing this interdependence. Dyogene members published in 2009 a two-volume book [1], [2] on Stochastic Geometry and Wireless Networks that became a reference publication in this domain.

In collaboration with Martin Haenggi (University of Notre Dame Notre Dame, IN, USA), Paul Keeler (Weierstrass Institute for Applied Analysis and Stochastics Berlin, Germany) and Sayandev Mukherjee (DOCOMO Innovations, Inc. Palo Alto, CA, USA), B. Blaszczyszyn is currently working on a book project that is intended to bridge a gap between academic and industrial approach to the design of next-generation cellular networks. In fact, simulation-only approach adopted by a majority of industry practitioners does not scale up with the increasing network complexity and analytical treatment is still yet not widely accepted in various bodies working out future standards specifications. The monograph is intended to bridge that gap, and make the methods, tools, approaches, and results of stochastic geometry available to a wide group of researchers (both in academia and in industry), systems engineers, and network designers. We expect that academic researchers and graduate students will appreciate that the book collects and organizes the most recent research results in a convenient way.