Base station density optimization for high energy efficiency in two-tier cellular networks

Abstract

The base station (BS) density configuration is a key factor to improve energy efficiency (EE) performances. In this paper, BS density configurations for achieving optimal EE performance in two-tier cellular networks are analyzed, where Poisson point process (PPP) is used to model BS spatial distribution. To make EE performances trackable and analyzable, BS density optimization in each tier is transformed into an equivalent problem that jointly optimizes the sum and ratio of BS densities. This equivalent optimization problem is not necessarily convex, while its monotonicity with different power consumptions of BSs is analyzable. Considering optimal BS density configuration is not unique and closed-form solution for achieving best EE performance is extremely difficult to be derived, a dynamic gradient based iterative algorithm by solving quadratic functions is proposed. Furthermore, quantitative analysis of EE performances based on data fitting method shows that approximately linear relationship between optimal BS density and user density holds only under specific conditions. Simulation results have demonstrated effectiveness of proposed algorithm and verified relevant conclusions.