Optimization of Base-Station Density for High Energy-Efficient Cellular Networks With Sleeping Strategies

Abstract

The base station (BS) density configuration is a crucial factor in improving energy efficiency (EE) in cellular networks, particularly when the sleeping strategy is used to reduce energy consumption. In this paper, the optimization of BS density for enhancing EE through traffic-aware sleeping strategies in both one- and two-tier cellular networks is researched, where the BS location is modeled as a Poisson point process. In the one-tier scenario, the EE optimization objective function is proved to be quasi-concave, and the optimal BS density solution is derived, where the maximum achievable EE is demonstrated to be independent of user density. In the two-tier scenario, both the activation probability of BSs and the coverage probability are analyzed, where the EE optimization objective function is proved to be not necessarily quasi-concave. To handle this nonconvex issue, an equivalent optimization problem that jointly optimizes the ratio and weighted sum of BS densities is proposed and solved by a dynamic gradient iterative algorithm. Meanwhile, a data fitting method is utilized to quantitatively analyze EE performances, in which the relationship between the optimal BS density and the user density is approximately linear when the user density is sufficiently high. Simulation results verify the relevant derivations and reflect that the sleeping strategy can not only save energy but improve the quality of radio links as well.