Capturing the SINR in cellular networks with Poisson processes

Speaker : Paul Keeler
Date: 20/03/2013
Time: 2:00 pm - 3:00 pm
Location: LINCS Meeting Room 40


The steady rise of user-traffic in wireless cellular networks has resulted in the need for developing robust and accurate models of various performance metrics. A key metric of these networks is the signal-to-interference-and-noise-ratio (SINR) experienced by a typical user. For tractability, often the positions of base stations in such networks are modelled by Poisson point processes whereas actual deployments often more resemble lattices (e.g. hexagonal). Strikingly, under log-normal shadowing it has been observed that the SINR experienced by a typical user is more accurate in a Poisson model than a hexagonal model. In this talk we seek to explain this interesting observation by way of a convergence result. Furthermore, we present numerically tractable, explicit integral expressions for the distribution of SINR of a cellular network modelled by Poisson process. Our model incorporates a power-law path-loss model with arbitrarily distributed shadowing. The results are valid in the whole domain of SINR and, unlike previous methods, do not require the inversion of Laplace transforms.Based on joint work in collaboration with B. Blaszczyszyn and M.K. Karray.