Load-Aware Energy Efficiency Optimization in Dense Small Cell Networks

Energy efficiency (EE) has become a crucial metric in dense small cell networks (DSCNs) due to the tremendous escalation of energy consumption. Since small cell base stations (SBSs) are randomly deployed, loads of them are usually different. In this letter, we aim to maximize the load-aware weighted sum of EEs (LWSEEs) across all subchannels in DSCNs jointly considering SBSs' loads and users' signal processing power through power allocation. First, we design the EE weight as a function of load factor (LF). Then, the LWSEE optimization problem is formulated as a non-concave sum-of-ratios optimization and we present the optimal LWSEE algorithm to tackle the problem based on the concave-convex procedure method. Furthermore, a simplified LWSEE (LWSEE-simp) algorithm where SBSs form interference groups is developed to reduce the signaling overhead in DSCNs. Simulation results show that SBSs' sum-EEs can be optimized according to their LFs and the optimal interference group size exists in the LWSEE-simp algorithm.