Heterogeneity-based Energy-efficient Transmission in Dense Small Cell Networks

Abstract

Green communications in dense small cell network (DSCNs) has attracted much attention. Energy saving (ES) and energy efficiency (EE) are two main goals and they are usually optimized separately. In this paper, taking into account the heterogeneity and cooperation opportunities among small cells, EE and ES are jointly optimized through subframe configuration and power allocation in the DSCNs. To quantize the heterogeneity, we define an EE preference function. Accordingly, a multi-objective optimization problem is formulated while considering the EE and ES optimization simultaneously. Due to the coupling of EE and ES, obtaining the solution is non-trivial. A heterogeneity-based ES and EE (HESEE) optimization algorithm is proposed, where the sleep mechanism is adopted via the subframe configuration. Particularly, the concave-convex procedure (CCCP) method is applied to solve the non-concave sum-of-ratios optimization for system EE. Simulation results show that the proposed HESEE algorithm can optimize the EE of small cell base stations (SBSs) according to their EE preference weights. In addition, compared with the base scheme, the HESEE algorithm can save energy by over 35.2% while improving system EE by up to 23%.