Sleep mode mechanisms in dense small cell networks

Data traffic continues to increase exponentially and operators are continuously upgrading their networks to meet this demand. The resulting capital and operational expenditures have limited revenues and the associated energy costs and CO2 emissions have raised economic and ecological concerns. In this paper, we use the stochastic geometry approach to investigate different sleep mode mechanisms that can address both capacity and energy efficiency (EE) objectives in dense small cell networks. We derive a multi-user connectivity model that facilitates the study of sleep mode mechanisms and manages the blocking rate of the network. We formulate an optimization framework that minimizes area power consumption using appropriate constraints. Numerical results show that sleep mode mechanisms enhance the EE of dense small cell networks and that the selection criterion of sleep mode candidate base stations is very important.