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The small cell network based Heterogeneous Network (HetNet) is featured as the promising way to meet the higher capacity improvement requirements for future. But how to effectively solve the upcoming heavy load and low Energy Efficiency (EE) problem in densely deployment scenario are still the key challenges for the small cell HetNet. In order to solve above problems, we implement the offloading strategy to make the load flow within the network tiers of the HetNet and provide better EE performances. Based on the auction theory, we propose the Optimal Energy Efficient Offloading (OEEO) scheme to maximize the system EE performance under the constraints of guaranteed requirements for the offloading processes. The Karush-Kuhn-Tucker (KKT) condition is utilized to find the optimal solutions. According to the observation of system-level simulation results, the proposed OEEO scheme has better performances over previous work.

In order to fully explore the merits of the multi-tier heterogeneous network (HetNet) and ultra-dense small cell deployments, the evolution of the cellular network architecture is on the way. Based on the frameless network architecture, this paper proposes the control plane (CP) and user plane (UP) adaptation strategy to improve the system energy efficiency (EE). In this paper, we give a three-step system EE optimization with constraints on the CP/UP adaptation. We optimize the system EE via CP and UP construction and adaptation while guaranteeing the user quality of service (QoS). In the first step, the CP construction and adaptation scheme is proposed through the Voronoi Diagram with EE improvements. In the second step, by jointly allocating the AE and subchannel resources, we construct the on-demand user-centric UP. In the last step, based on the UP construction from the second step, we adjust each UP to optimize the EE performance. This is achieved by employing game theory. Furthermore, we verify the existence and uniqueness of the Nash Equilibrium for the non-cooperative game model with pricing. Finally, the system-level simulation results show that, with constraints on the QoS of the users, the system EE performances are improved.

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