A Tele-Traffic-Aware Optimal Base-Station Deployment Strategy for Energy-Efficient Large-Scale Cellular Networks

• Published in: IEEE access Vol. 4; pp. 2083 - 2095
• Main Authors: Zhao, Guogang, Chen, Sheng, Zhao, Liqiang, Hanzo, Lajos
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cellular communication; Cellular networks; Density; Driving conditions; Electronic devices; Energy conservation; Energy dissipation; Energy efficiency; energy saving performance; Large-scale cellular networks; Large-scale systems; Mobile communication; Mobile handsets; Networks; Optimization; Parameters; Quality of service; Radio equipment; Strategy; tele-traffic-aware deployment; Telecommunication traffic; Traffic; User satisfaction; energy saving performance; tele-traffic-aware deployment; Large-scale cellular networks; energy efficiency
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2016.2543210

With the explosive proliferation of mobile devices and services, the user density of large-scale cellular networks continues to increase, which results in further escalating traffic generation. Yet, there is an urging demand for reducing the network's energy dissipation. Hence, we model the energy efficiency of large-scale cellular networks for characterizing its dependence on the base station (BS) density as well as for quantifying the impact of tele-traffic on the achievable energy efficiency under specific quality of service requirements. This allows us to match the BS deployment to the network's tele-traffic while conserving precious energy. More specifically, we formulate a practical tele-traffic-aware BS deployment problem for optimizing the network's energy efficiency while satisfying the users' maximum tolerable outage probability. This is achieved by analyzing the optimal BS-density under specific tele-traffic conditions. Furthermore, we study the energy saving potential of our optimal BS deployment strategy under diverse practical parameters and provide insights into the attainable energy savings in dense random cellular networks. Our simulation results confirm the accuracy of our analysis and verify the impact of the parameters considered on the network's energy efficiency. Our results also demonstrate that the proposed tele-traffic-aware optimal BS deployment strategy significantly outperforms the existing approaches in terms of its energy efficiency.