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Measurement-driven capability modeling for mobile data networks in large-scale urban environment

Measurement-driven capability modeling for mobile data networks in large-scale urban environment
Measurement-driven capability modeling for mobile data networks in large-scale urban environment
For mobile networks diverse usage scenarios have different capability requirements on connection density and user experienced data rate, and modeling such capability diversity is crucial to the strategy evaluation in addressing the problem of high traffic load and scalability of network resources. Therefore, it is necessary to build a capability model in two dimensions of connection density and user experienced data rate. This paper aims at addressing this challenge based on an investigation of network capability in large-scale urban environment. First, our statistical study shows that the spatial distribution of these two parameters can be accurately fitted by log-normal mixture model. Second, we find that only six basic capability patterns exist among the 9,000 cellular base stations. Their connections with the urban functions of geographical locations are also explored in our work. Based on these two discoveries, we build a network capability model which can generate synthetic base stations with diverse connection density and user experienced data rate. We believe that this flexible and powerful model can help telecommunication operators to design and standardize mobile network in the future.
Ding, Jingtao
b21a417a-c75e-4f3b-b3e9-02c5d7494454
Liu, Xihui
cf748cd2-1a7b-4b0b-8d6d-49e4f57926cf
Li, Yong
0817e950-114f-47f3-aefe-74bf9ec0e2a3
Wu, Di
91a701bd-7ae2-4c61-af89-1d300e3671fd
Jin, Depeng
d5ef5d7e-82a7-4950-85cf-800fe7794cc5
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Ding, Jingtao
b21a417a-c75e-4f3b-b3e9-02c5d7494454
Liu, Xihui
cf748cd2-1a7b-4b0b-8d6d-49e4f57926cf
Li, Yong
0817e950-114f-47f3-aefe-74bf9ec0e2a3
Wu, Di
91a701bd-7ae2-4c61-af89-1d300e3671fd
Jin, Depeng
d5ef5d7e-82a7-4950-85cf-800fe7794cc5
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Ding, Jingtao, Liu, Xihui, Li, Yong, Wu, Di, Jin, Depeng and Chen, Sheng (2016) Measurement-driven capability modeling for mobile data networks in large-scale urban environment. 13th IEEE International Conference on Mobile Ad Hoc and Sensor systems (IEEE MASS 2016), Brazil. 10 - 13 Oct 2016. 9 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

For mobile networks diverse usage scenarios have different capability requirements on connection density and user experienced data rate, and modeling such capability diversity is crucial to the strategy evaluation in addressing the problem of high traffic load and scalability of network resources. Therefore, it is necessary to build a capability model in two dimensions of connection density and user experienced data rate. This paper aims at addressing this challenge based on an investigation of network capability in large-scale urban environment. First, our statistical study shows that the spatial distribution of these two parameters can be accurately fitted by log-normal mixture model. Second, we find that only six basic capability patterns exist among the 9,000 cellular base stations. Their connections with the urban functions of geographical locations are also explored in our work. Based on these two discoveries, we build a network capability model which can generate synthetic base stations with diverse connection density and user experienced data rate. We believe that this flexible and powerful model can help telecommunication operators to design and standardize mobile network in the future.

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More information

Accepted/In Press date: 17 June 2016
e-pub ahead of print date: 11 October 2016
Venue - Dates: 13th IEEE International Conference on Mobile Ad Hoc and Sensor systems (IEEE MASS 2016), Brazil, 2016-10-10 - 2016-10-13
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 401877
URI: http://eprints.soton.ac.uk/id/eprint/401877
PURE UUID: e04e32d9-afba-48ca-92b5-2bcab285a735

Catalogue record

Date deposited: 25 Oct 2016 09:18
Last modified: 13 Dec 2018 12:29

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Contributors

Author: Jingtao Ding
Author: Xihui Liu
Author: Yong Li
Author: Di Wu
Author: Depeng Jin
Author: Sheng Chen

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