DocumentCode :
713804
Title :
Optimal base station density in ultra-densification heterogeneous network
Author :
Jianyuan Feng ; Zhiyong Feng ; Zhiqing Wei ; Wei Li ; Sumit Roy
Author_Institution :
Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2015
fDate :
9-12 March 2015
Firstpage :
1452
Lastpage :
1457
Abstract :
In this paper, we study the relation between network capacity and the density of micro base stations in heterogeneous networks (HetNets) scenario consisting of macro base station (MaBS) and micro base station (MiBS) tiers. First, the distribution of the distance between a typical user and its serving base station (BS) is derived in a stochastic geometry model. Assuming users access the BS with the strongest received signal, we obtain the probability of users´ association with the MiBS tier as a function of MiBS density. Then the impact of BS density on the interference inside the MiBS tier is also achieved in closed form. Finally, we derive the closed form solution of the network capacity as a function of BS density. We find that although there are more available channels with higher MiBS density, the rate of each channel is degraded because of stronger interference. Therefore the problem of maximizing network capacity with respect to MiBS density is formulated and the optimal MiBS density is obtained. Simulations are provided to verify the correctness of our analysis. One interesting finding is that network capacity doesn´t increase monotonously with BS density. Thus deploying more MiBS may not always be a good choice1.
Keywords :
densification; probability; radiofrequency interference; stochastic processes; wireless channels; HetNets scenario; MaBS density; MiBS density; macro base station; micro base station; network capacity maximization; optimal microbase station density; radio channel; stochastic geometry model; ultra densification heterogeneous network; user association probability; Base stations; Conferences; Interference; Mobile communication; Mobile computing; Monte Carlo methods; Wireless networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications and Networking Conference (WCNC), 2015 IEEE
Conference_Location :
New Orleans, LA
Type :
conf
DOI :
10.1109/WCNC.2015.7127682
Filename :
7127682
Link To Document :
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