Energy Efficient Heterogeneous Cellular Networks

By Yong Sheng Soh, Tony Q. S. Quek, Marios Kountouris, Hyundong Shin. IEEE Journal on Selected Areas in Communications, 2013

576 citations recorded by the source corpus.

With the exponential increase in mobile internet traffic driven by a new generation of wireless devices, future cellular networks face a great challenge to meet this overwhelming demand of network capacity. At the same time, the demand for higher data rates and the ever-increasing number of wireless users led to rapid increases in power consumption and operating cost of cellular networks. One potential solution to address these issues is to overlay small cell networks with macrocell networks as a means to provide higher network capacity and better coverage. However, the dense and random deployment of small cells and their uncoordinated operation raise important questions about the energy efficiency implications of such multi-tier networks. Another technique to improve energy efficiency in cellular networks is to introduce active/sleep (on/off) modes in macrocell base stations. In this paper, we investigate the design and the associated tradeoffs of energy efficient cellular networks through the deployment of sleeping strategies and small cells. Using a stochastic geometry based model, we derive the success probability and energy efficiency in homogeneous macrocell (single-tier) and heterogeneous K-tier wireless networks under different sleeping policies. In addition, we formulate the power consumption minimization and energy efficiency maximization problems, and determine the optimal operating regimes for macrocell base stations. Numerical results confirm the effectiveness of switching off base stations in homogeneous macrocell networks. Nevertheless, the gains in terms of energy efficiency depend on the type of sleeping strategy used. In addition, the deployment of small cells generally leads to higher energy efficiency but this gain saturates as the density of small cells increases. In a nutshell, our proposed framework provides an essential understanding on the deployment of future green heterogeneous networks.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/b67bb4099c422a4c7664ff9987f4572caa5aed49

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Citations in the corpus

Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks (2016, methodology): “In [152], an EE optimization framework has been developed for K-tier HetNets.”
A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead (2016, background): “This trade-off has been analyzed in [70], where it is shown that densification has a beneficial impact on energy efficiency, but the gain saturates as the density of the infrastructure nodes”
Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A Survey (2015, background): “[21] particularly addressed inter-tier interference among multi-tier heterogeneous cells.”
User Association in 5G Networks: A Survey and an Outlook (2015, background): “The authors of [112] analyzed the coverage guaranteeing a certain throughput for a two-tier topology and provided insights concerning the most appropriate spectrum partitioning ratio based on numerical investigations.”
Cooperative Caching and Transmission Design in Cluster-Centric Small Cell Networks (2016, background): “The backhauling process increases not only end-to-end delivery delay but also energy consumption, compared to the case of serving user requests using the local caches [21], [22].”
Energy-Efficient Design of MIMO Heterogeneous Networks With Wireless Backhaul (2015, background): “Cognitive sensing and sleep mode strategies were also proposed to turn off inactive access points and enhance the energy efficiency [22], [23].”