Modelling green HetNets in dynamic ultra large-scale applications: A case-study for femtocells in smart-cities

Date

2017-12-09

Author

Ever, Enver
Al-Turjman, Fadi M.
Zahmatkesh, Hadi
Riza, Mustafa

Metadata

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In recent years, with the rapid increase in the number of mobile connected devices and data traffic, mobile operators have been trying to find solutions to provide better coverage and capacity for mobile users. In this respect, deployment of femtocells is a promising solution. This paper presents performability analysis of femtocells. Unlike the existing studies, the potential reduction of the service capacity due to failures are considered as well as various performance metrics such as throughput, mean queue length, response time, and energy consumption. In other words, the femtocells are modelled as fault tolerant wireless communication systems, considering factors such as mobility of the mobile users, multiple channels for the femtocells, and failure/repair behaviour of the channels for more realistic performance measures. A typical scenario is considered for smart-city applications as case study where a set of femtocells are deployed within the coverage area of a macrocell. The numerical results presented show the accuracy of the proposed model as an abstraction of a femtocell system. The results also reveal that the computational efficiency of the analytical model is significantly better than simulation.

Subject Keywords

Femtocells, Fault tolerance, Queuing theory, LTE, Smart-cities, Cellular radio

URI

https://hdl.handle.net/11511/67568

Journal

COMPUTER NETWORKS

DOI

https://doi.org/10.1016/j.comnet.2017.03.016

Collections

Engineering, Article

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Citation Formats

E. Ever, F. M. Al-Turjman, H. Zahmatkesh, and M. Riza, “Modelling green HetNets in dynamic ultra large-scale applications: A case-study for femtocells in smart-cities,” COMPUTER NETWORKS, pp. 78–93, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67568.