DocumentCode
735238
Title
Multi-criteria decision for small cell switch off in ultra-dense LTE networks
Author
Dudnikova, Anna ; Dini, Paolo ; Giupponi, Lorenza ; Panno, Daniela
Author_Institution
Dept. Dept. of Electr., Univ. of Catania, Catania, Italy
fYear
2015
fDate
13-15 July 2015
Firstpage
1
Lastpage
8
Abstract
The concept of a densely deployed heterogeneous network is one of the main approaches of modern wireless networking research to satisfy the growth of the traffic demand. However, such trend leads to a significant network energy consumption increment. One of the effective techniques to save energy is to switch off some underutilized cells during off peak hours. In this line, the focus of this paper is to decide the number of base stations to switch off in order to maximize the energy saving, while maintaining coverage, capacity and Quality of Service. We use a combination of Grey Relational Analysis and Analytic Hierarchy Process tools to trigger the switch off actions, jointly considering multiple decision inputs for each cell. The co-tier interference, typical of small cell networks, is also considered in the decision making by introducing a graph - based technique for dynamic resource allocation.
Keywords
Long Term Evolution; analytic hierarchy process; quality of service; resource allocation; telecommunication power management; telecommunication traffic; analytic hierarchy process tools; base stations; densely deployed heterogeneous network; dynamic resource allocation; graph-based technique; grey relational analysis; multi-criteria decision; multiple decision inputs; network energy consumption; quality of service; small cell switch off; traffic demand; ultra-dense LTE networks; Decision support systems; LTE; cell switch off; energy saving; heterogeneous network; interference mitigation;
fLanguage
English
Publisher
ieee
Conference_Titel
Telecommunications (ConTEL), 2015 13th International Conference on
Conference_Location
Graz
Type
conf
DOI
10.1109/ConTEL.2015.7231191
Filename
7231191
Link To Document