Cache-enabled Software Defined Heterogeneous Networks for Green and Flexible 5G Networks

Abstract
The network densification of small cells (SCs) is a promising way to cope with the explosive growth of future traffic demands in 5G networks. However, the overall power consumption and the backhaul limitation of the network have become the key factors affecting the network performance and users' quality-of-experience, which have great importance in 5G wireless networks. Due to the complexity of 5G networks and the variety of user behaviors, the combination of software-defined networks and content delivery strategy could be a more efficient way to manage such networks. In this paper, a cache-enabled wireless heterogeneous network with the control-plane (C-plane) and user-plane (U-plane) split is proposed, where the macro cell and SCs with different cache abilities are overlaid and cooperated together in the backhaul scenario. Using an evaluation tool composed of stochastic processes and classical power consumption model, key performance indicators, e.g., the coverage probability, throughput, and energy efficiency (EE), are derived as closed-form expressions or the functions of the signal-to-interference-plus-noise ratio threshold, path loss exponent, transmission power and density of macro and SCs, cache ability, file popularity, and backhaul capacity. Fundamental trade-offs are illustrated between EE and transmission power, EE and SC density, as well as the throughput and density of SCs. Numerical results show that the proposed cache-enabled software-defined networks have much higher throughput and improved EE than current LTE networks, which shows a promising solution for future cellular networks.
Funding Information
  • National Science Foundation of China NSFC (61372114, 61571054 and 61471062)
  • National 973 Program (2012CB316005)
  • China Scholarship Council.

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