Heterogeneity-aware energy saving and energy efficiency optimization in dense small cell networks

Abstract

In dense small cell networks (DSCNs), small cells are heterogeneous due to the unplanned deployment and various traffic loads, resulting in different energy efficiency (EE) preferences. In this paper, taking into account the heterogeneity of small cells, energy saving (ES) and EE are jointly optimized through subchannel allocation, subframe configuration and power allocation. In order to quantify the effects of small cells' heterogeneous information on EE, an EE preference function is first defined. Then, the joint ES and EE optimization problem is formulated as a multi-objective optimization problem. Due to the coupling of ES and EE, obtaining the solution is non-trivial. Therefore, we propose a heterogeneity-aware ES and EE (HESEE) optimization algorithm, where subchannel allocation is optimized to ensure the fairness of active subframes required by the users in the same small cell base stations (SBSs). Then subframe configuration is conducted via group formation sleep mechanism. Particularly, address the non-concave sum-of-ratios optimization for system EE, the concave-convex procedure (CCCP) method is adopted. Simulation results show that the proposed HESEE algorithm can optimize the SBSs' EEs according to their EE preferences. In addition, the HESEE algorithm can achieve good performance in reducing energy consumption as well as improving the system EE.