Spatial modeling of Scalable Spatially-correlated Log-normal distributed traffic inhomogeneity and energy-efficient network planning

This paper explores the influence of the inhomogeneous spatial traffic distribution on the performance of energy efficiency and proposes an energy-efficient heterogeneous network planning scheme for cellular networks. We first provide a spatial modeling method of Scalable, Spatially correlated, and Log-normally distributed Traffic (SSLT). Together with the spatial modeling, the measure of inhomogeneity of spatial traffic distributions is introduced which is related to the energy efficiency performance of network planning. Then we propose a network planning scheme which deploys both micro and macro base stations (BSes) adapting to the traffic inhomogeneity. Numerical results show that when the spatial traffic distribution is more inhomogeneous, the proposed scheme improves energy efficiency by deploying more micro BSes. We also found that proportional relationships exist among three values, i.e. the ratio of the number of micro and macro BSes, energy efficiency, and the inhomogeneity.