On the Application of Stochastic Geometry for Spectral Efficiency Analysis in Wireless Networks

Stochastic geometry is quickly becoming an indispensable instrument in wireless network analysis. We show how the application of stochastic geometry to the spectral efficiency analysis is greatly facilitated by (i) a clear separation of time scales, (ii) abstraction of small-scale effects via ergodicity, and (iii) an interference model that reflects the receiver’s lack of knowledge of how each individual interference term is faded. These procedures render the analysis both more manageable and precise, as well as more amenable to the incorporation of subsequent features. To demonstrate the potency of our approach, we present analytical characterizations of the ergodic spectral efficiency of cellular networks with single-user multiple-input multiple-output (MIMO) and sectorization. These characterizations, in the form of easy-to-evaluate expressions, encompass the coverage probability, the distribution of spectral efficiency over the network locations, and the average thereof. 

Ratheesh K. Mungara received his B.Tech. Degree in Electronics and Communications Engineering from Jawaharlal Nehru Technological University, Hyderabad, India, in 2005, M.Tech. Degree in communication systems from the National Institute of Technology, Tiruchirappalli, India, in 2007, and Ph.D. Degree in Information and Communication Technologies from Universitat Pompeu Fabra (UPF), Barcelona, Spain, in 2016. Between January 2017 and April 2017, he has been a postdoctoral member of the Wireless Communications Research Group at UPF. Previously, He was a modem software engineer at Qualcomm India Private Limited, Hyderabad, from 2007-2010, and worked as a research scientist at the Centre for Wireless Communications (CWC), University of Oulu, Finland, during 2010-2011. His research interests include communication-theoretic analysis of wireless networks using stochastic geometry tools.