A traffic aware sleep mode strategy for energy efficient dense HETNETS.

Abstract

Data traffic demand has been increasing exponentially and this trend is expected to continue over the foreseeable future. This has forced operators to upgrade and densify their mobile networks to enhance their capacity. Future networks will be characterized by dense deployment of different kinds of base stations (BSs) in a hierarchical cellular structure. However, network densification requires extensive capital and operational investment which limits operator revenues and raises ecological concerns over greenhouse gas emissions. Although networks are planned to support peak traffic, traffic demand is actually highly variable in both space and time which makes it necessary to adapt network energy consumption to inevitable variations in traffic demand. In this Project, actual network traffic was collected from a cluster of six sites in an urban area and used to formulate a long-term traffic profile that can be used to adapt energy consumption to the prevailing traffic conditions. An adoptive approach that determines the required BS density in response to the variable long-term traffic profile in Heterogeneous Networks (HetNets) was designed. Analysis and formulation of energy-efficient sleep mode strategies for a two-tier heterogeneous network was done. Furthermore, a novel sleep mode mechanism called strategic sleep mode was analyzed to determine its ability to adapt energy consumption to variable user density. Our analysis shows that significant energy savings are achieved when sleep mode schemes are made traffic-aware.