Dual Band UMTS Network Energy Saving using Base Station Sleeping Mode: The Case of ethio telecom
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Date
2019-12
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Addis Ababa University
Abstract
Base stations represent the core contributor to the energy consumption of a mobile
network. Since traffic load in mobile networks significantly fluctuates during a day and
night time, it is important to quantify the influence of these variations on the base station
energy consumption. Therefore, this thesis proposes energy-saving technique to reduce
energy consumption at the base station level. One of the approaches is the base station
sleeping technique which takes advantage of varying traffic patterns on a daily or weekly
basis and selectively switches some lightly loaded base stations to the sleep mode.
Various literatures have investigated the potential of energy-saving technique. However,
those studies have made a simplifying assumptions that leads to inaccuracy in overall
results. This thesis considers the effect of traffic load on energy consumption instead of
making assumptions. Ethio telecom deployed UMTS network on two separate frequency
bands: 900MHz and 2100 MHz. While applying energy-saving techniques, data service
and radio coverages provided by the remaining active base stations need to guarantee
the requirement over the whole area at all times. To this end, optimization of the SINR
value of the coverage area is carried out by considering received signals of the base
stations using genetic algorithms. As input data, real traffic statistics are used on a fully
operated base station traffic load along with its power consumption. The tools utilized for
analysis include MATLAB, MapInfo and WinProp.
Performance results show that the proposed energy saving technique and algorithm can
achieve energy savings of up to 25%, corresponding to the annual reduction of over 2,520
KWh per-site. Considering the selected case study area of ethio telecom mobile network,
the use of energy-saving solutions allowed annual savings of more than 73,990.00 Birr
per 12 square kilometers.
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Keywords
Energy Saving, Base Station sleep modes, Dual-band UMTS network, Genetic Algorithms