|Speaker :||Paul Keeler|
|Time:||2:00 pm - 3:00 pm|
|Location:||LINCS Meeting Room 40|
The steady rise of user-traffic in wireless cellularÂ networks has resulted inÂ the need for developing robust and accurateÂ models of various performance metrics. A key metric of these networksÂ is theÂ signal-to-interference-and-noise-ratio (SINR) experienced by aÂ typical user.Â For tractability, often the positions of base stationsÂ in such networks areÂ modelled by Poisson point processes whereasÂ actual deployments often moreÂ resemble lattices (e.g. hexagonal).Â Strikingly, under log-normal shadowing itÂ has been observed that theÂ SINR experienced by a typical user is more accurate in a Poisson modelÂ than a hexagonal model. In this talk we seek toÂ explain thisÂ interesting observation by way of a convergence result.Â Furthermore,Â we present numerically tractable, explicit integral expressionsÂ forÂ the distribution of SINR of a cellular network modelled byÂ PoissonÂ process. Our model incorporates a power-law path-loss modelÂ withÂ arbitrarily distributed shadowing. The results are valid in theÂ wholeÂ domain of SINR and, unlike previous methods, do not requireÂ theÂ inversion of Laplace transforms.Based on joint work inÂ collaborationÂ with B. Blaszczyszyn and M.K. Karray.