DocumentCode :
1788751
Title :
Two-tier cellular random network planning for minimum deployment cost
Author :
Mekikis, Prodromos-Vasileios ; Kartsakli, Elli ; Antonopoulos, Antonios ; Lalos, Aris ; Alonso, Luis ; Verikoukis, Christos
Author_Institution :
Signal Theor. & Commun. Dept., Tech. Univ. of Catalonia, Barcelona, Spain
fYear :
2014
fDate :
10-14 June 2014
Firstpage :
1248
Lastpage :
1253
Abstract :
Random dense deployment of heterogeneous networks (HetNets), consisting of macro base stations (BS) and small cells (SC), can provide higher quality of service (QoS) while increasing the energy efficiency of the cellular network. In addition, it is possible to achieve lower deployment cost and, therefore, maximize the benefits for the network providers. In this paper, we propose a novel method to determine the minimum deployment cost of a two-tier heterogeneous cellular network using random deployment. After deriving the coverage probability of the two-tier deployment by using stochastic geometry tools, we identify the tier intensities that provide the minimum deployment cost for a given coverage probability. Extensive simulations verify the existence of a unique set of intensities for different coverage constraints.
Keywords :
cellular radio; geometry; probability; quality of service; random processes; stochastic processes; telecommunication network planning; BS; HetNets; QoS; SC; coverage probability; energy efficiency; macrobase station; minimum random deployment cost; quality of service; small cell; stochastic geometry tool; two-tier heterogeneous cellular random network planning; Equations; Fading; Interference; Mathematical model; Numerical models; Quality of service; Signal to noise ratio; Cost minimization; Coverage probability; Heterogeneous networks; Random deployment; Stochastic geometry;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2014 IEEE International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/ICC.2014.6883492
Filename :
6883492
Link To Document :
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