TY - GEN
T1 - Base station location optimization for minimal energy consumption in wireless networks
AU - González-Brevis, Pablo
AU - Gondzio, Jacek
AU - Fan, Yijia
AU - Poor, H. Vincent
AU - Thompson, John
AU - Krikidis, Ioannis
AU - Chung, Pei Jung
PY - 2011
Y1 - 2011
N2 - This paper studies the combined problem of base station location and optimal power allocation, in order to optimize the energy efficiency of a cellular wireless network. Recent work has suggested that moving from a network of a small number of high power macrocells to a larger number of smaller microcells may improve the energy efficiency of the network. This paper investigates techniques to optimize the number of base stations and their locations, in order to minimize energy consumption. An important contribution of the paper is that it takes into account non-uniform user distributions across the coverage area, which is likely to be encountered in practice. The problem is solved using approaches from optimization theory that deal with the facility location problem. Stochastic programming techniques are used to deal with the expected user distributions. An example scenario is presented to illustrate how the technique works and the potential performance gains that can be achieved.
AB - This paper studies the combined problem of base station location and optimal power allocation, in order to optimize the energy efficiency of a cellular wireless network. Recent work has suggested that moving from a network of a small number of high power macrocells to a larger number of smaller microcells may improve the energy efficiency of the network. This paper investigates techniques to optimize the number of base stations and their locations, in order to minimize energy consumption. An important contribution of the paper is that it takes into account non-uniform user distributions across the coverage area, which is likely to be encountered in practice. The problem is solved using approaches from optimization theory that deal with the facility location problem. Stochastic programming techniques are used to deal with the expected user distributions. An example scenario is presented to illustrate how the technique works and the potential performance gains that can be achieved.
UR - http://www.scopus.com/inward/record.url?scp=80052003686&partnerID=8YFLogxK
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U2 - 10.1109/VETECS.2011.5956204
DO - 10.1109/VETECS.2011.5956204
M3 - Conference contribution
AN - SCOPUS:80052003686
SN - 9781424483310
T3 - IEEE Vehicular Technology Conference
BT - 2011 IEEE 73rd Vehicular Technology Conference, VTC2011-Spring - Proceedings
T2 - 2011 IEEE 73rd Vehicular Technology Conference, VTC2011-Spring
Y2 - 15 May 2011 through 18 May 2011
ER -