Design Optimization of Tracking Area List in Lte Using 2D Markov Model

Mohammed Daffalla Elradi; Lamia Osman Widaa

doi:doi:10.11648/j.awcn.20190502.12

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Design Optimization of Tracking Area List in Lte Using 2D Markov Model

Mohammed Daffalla Elradi, Lamia Osman Widaa

Published in Advances in Wireless Communications and Networks (Volume 5, Issue 2)

Received: 27 July 2019 Accepted: 5 November 2019 Published: 13 November 2019

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Abstract

In LTE there is a logical grouping of cells called Tracking Area (TA) and TAs are further grouped into Tracking Area List (TAL). Signaling overhead is greatly affected by the size of the TA and TAL respectively. Designing an optimum TAL would greatly reduce signaling overhead resulting from Tracking Area Update (TAU) and Paging procedures, which in return maximizes the network performance. This paper adopts a 2D Markov model that can be used for design optimization of TAL in LTE system by estimating the number of users in a cell within a time slot and the probability of the next location they might move to, as users move from and into cells periodically. The model was simulated in Matlab simulation software. The 2D Markov model was used to calculate TAU overhead, paging overhead and the total signaling overheads. The numerical results show that our model probably reduces the signaling overhead by about an average of 56% than that of the conventional TA scheme.

Published in	Advances in Wireless Communications and Networks (Volume 5, Issue 2)
DOI	10.11648/j.awcn.20190502.12
Page(s)	52-56
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

2D Markov Model, Signaling Overhead, Tracking Area, Tracking Area List

References

[1]	Vincent W.-S. Wong and Victor C. M. Leung, “Location management for next-generation personal communications networks,” IEEE Network, vol. 14, no. 5, pp. 18-24, September/October 2000.
[2]	Lamia Osman Widaa, Sami Mohamed Sharif,”Design Optimization of Tracking Area List for Reducing Total Signaling Overhead in LTE Systems”, In Research gate, 2014.
[3]	Jaime FerragutMartínez-Vara de Rey, “Traffic and Mobility Management in Large-Scale Networks of Small Cells”, June 2014.
[4]	Razavi, S. Modarres, Di Yuan, Fredrik Gunnarsson, and Johan Moe. "Dynamic tracking area list configuration and performance evaluation in LTE." In GLOBECOM Workshops (GC Wkshps), 2010 IEEE, pp. 49-53. IEEE, 2010.
[5]	Tao Deng, PingzhiFan,”Modeling and Performance Analysis of a Tracking-Area-List-Based Location Management Scheme in LTE Networks” IEEE-TVT-2016.
[6]	Razavi, S. Modarres, “Planning and Optimization of Tracking Areas for Long Term Evolution Networks” Linkoping, Sweden, 2014.
[7]	Q. Zhang et al.,”A 2-D random walk mobility model forWiMAX location update”, Computer Communications (2015).
[8]	Xian Wang, XianfuLei, Rose Qingyang Hu, Yi Qian,”Modeling of Tracking Area List-Based Location Update Scheme in Long Term Evolution”.
[9]	Liou, R., & Lin, Y. (2013). Mobility management with the central-based location area policy. Computer Networks, 57, 847-857.
[10]	Razavi, Sara Modarres. “Tracking Area Planning in Cellular Networks - Optimization and Performance Evaluation.” (2011).
[11]	Razavi, Sara Modarres, and Di Yuan. "Performance improvement of LTE tracking area design: a re-optimization approach." In Proceedings of the 6th ACM international symposium on Mobility management and wireless access, pp. 77-84. ACM, 2008.
[12]	Liou, R., Y. Lin, and S. Tsai. " An investigation on LTE mobility management." IEEE Transaction on mobile computing(2011), vol 12, no. 1, pp 166-176,2011.
[13]	Szalka, Tamas, Sandor Szabo, and PÉTER FÜLÖP. "Markov model based location prediction in wireless cellular networks." Infocommunications Journal (2009): 40.
[14]	Razavi, Sara Modarres, Di Yuan, Fredrik Gunnarsson, and Johan Moe. "Exploiting tracking area list for improving signalling overhead in LTE." In Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st, pp. 1-5. IEEE, 2010.
[15]	Karandikar, Abhay & Akhtar, Nadeem & Mehta, Mahima. (2017). Mobility Management in LTE Heterogeneous Networks. 10.1007/978-981-10-4355-0.

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Mohammed Daffalla Elradi, Lamia Osman Widaa. (2019). Design Optimization of Tracking Area List in Lte Using 2D Markov Model. Advances in Wireless Communications and Networks, 5(2), 52-56. https://doi.org/10.11648/j.awcn.20190502.12

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Mohammed Daffalla Elradi; Lamia Osman Widaa. Design Optimization of Tracking Area List in Lte Using 2D Markov Model. Adv. Wirel. Commun. Netw. 2019, 5(2), 52-56. doi: 10.11648/j.awcn.20190502.12

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AMA Style

Mohammed Daffalla Elradi, Lamia Osman Widaa. Design Optimization of Tracking Area List in Lte Using 2D Markov Model. Adv Wirel Commun Netw. 2019;5(2):52-56. doi: 10.11648/j.awcn.20190502.12

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@article{10.11648/j.awcn.20190502.12,
  author = {Mohammed Daffalla Elradi and Lamia Osman Widaa},
  title = {Design Optimization of Tracking Area List in Lte Using 2D Markov Model},
  journal = {Advances in Wireless Communications and Networks},
  volume = {5},
  number = {2},
  pages = {52-56},
  doi = {10.11648/j.awcn.20190502.12},
  url = {https://doi.org/10.11648/j.awcn.20190502.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.awcn.20190502.12},
  abstract = {In LTE there is a logical grouping of cells called Tracking Area (TA) and TAs are further grouped into Tracking Area List (TAL). Signaling overhead is greatly affected by the size of the TA and TAL respectively. Designing an optimum TAL would greatly reduce signaling overhead resulting from Tracking Area Update (TAU) and Paging procedures, which in return maximizes the network performance. This paper adopts a 2D Markov model that can be used for design optimization of TAL in LTE system by estimating the number of users in a cell within a time slot and the probability of the next location they might move to, as users move from and into cells periodically. The model was simulated in Matlab simulation software. The 2D Markov model was used to calculate TAU overhead, paging overhead and the total signaling overheads. The numerical results show that our model probably reduces the signaling overhead by about an average of 56% than that of the conventional TA scheme.},
 year = {2019}
}

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TY  - JOUR
T1  - Design Optimization of Tracking Area List in Lte Using 2D Markov Model
AU  - Mohammed Daffalla Elradi
AU  - Lamia Osman Widaa
Y1  - 2019/11/13
PY  - 2019
N1  - https://doi.org/10.11648/j.awcn.20190502.12
DO  - 10.11648/j.awcn.20190502.12
T2  - Advances in Wireless Communications and Networks
JF  - Advances in Wireless Communications and Networks
JO  - Advances in Wireless Communications and Networks
SP  - 52
EP  - 56
PB  - Science Publishing Group
SN  - 2575-596X
UR  - https://doi.org/10.11648/j.awcn.20190502.12
AB  - In LTE there is a logical grouping of cells called Tracking Area (TA) and TAs are further grouped into Tracking Area List (TAL). Signaling overhead is greatly affected by the size of the TA and TAL respectively. Designing an optimum TAL would greatly reduce signaling overhead resulting from Tracking Area Update (TAU) and Paging procedures, which in return maximizes the network performance. This paper adopts a 2D Markov model that can be used for design optimization of TAL in LTE system by estimating the number of users in a cell within a time slot and the probability of the next location they might move to, as users move from and into cells periodically. The model was simulated in Matlab simulation software. The 2D Markov model was used to calculate TAU overhead, paging overhead and the total signaling overheads. The numerical results show that our model probably reduces the signaling overhead by about an average of 56% than that of the conventional TA scheme.
VL  - 5
IS  - 2
ER  -

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Author Information

Mohammed Daffalla Elradi

Communication Systems Engineering Department, University of Science and Technology, Khartoum, Sudan
Lamia Osman Widaa

Communication Systems Engineering Department, University of Science and Technology, Khartoum, Sudan

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Plain Text BibTeX RIS

APA Style

Mohammed Daffalla Elradi, Lamia Osman Widaa. (2019). Design Optimization of Tracking Area List in Lte Using 2D Markov Model. Advances in Wireless Communications and Networks, 5(2), 52-56. https://doi.org/10.11648/j.awcn.20190502.12

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ACS Style

Mohammed Daffalla Elradi; Lamia Osman Widaa. Design Optimization of Tracking Area List in Lte Using 2D Markov Model. Adv. Wirel. Commun. Netw. 2019, 5(2), 52-56. doi: 10.11648/j.awcn.20190502.12

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AMA Style

Mohammed Daffalla Elradi, Lamia Osman Widaa. Design Optimization of Tracking Area List in Lte Using 2D Markov Model. Adv Wirel Commun Netw. 2019;5(2):52-56. doi: 10.11648/j.awcn.20190502.12

Copy | Download

@article{10.11648/j.awcn.20190502.12,
  author = {Mohammed Daffalla Elradi and Lamia Osman Widaa},
  title = {Design Optimization of Tracking Area List in Lte Using 2D Markov Model},
  journal = {Advances in Wireless Communications and Networks},
  volume = {5},
  number = {2},
  pages = {52-56},
  doi = {10.11648/j.awcn.20190502.12},
  url = {https://doi.org/10.11648/j.awcn.20190502.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.awcn.20190502.12},
  abstract = {In LTE there is a logical grouping of cells called Tracking Area (TA) and TAs are further grouped into Tracking Area List (TAL). Signaling overhead is greatly affected by the size of the TA and TAL respectively. Designing an optimum TAL would greatly reduce signaling overhead resulting from Tracking Area Update (TAU) and Paging procedures, which in return maximizes the network performance. This paper adopts a 2D Markov model that can be used for design optimization of TAL in LTE system by estimating the number of users in a cell within a time slot and the probability of the next location they might move to, as users move from and into cells periodically. The model was simulated in Matlab simulation software. The 2D Markov model was used to calculate TAU overhead, paging overhead and the total signaling overheads. The numerical results show that our model probably reduces the signaling overhead by about an average of 56% than that of the conventional TA scheme.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Design Optimization of Tracking Area List in Lte Using 2D Markov Model
AU  - Mohammed Daffalla Elradi
AU  - Lamia Osman Widaa
Y1  - 2019/11/13
PY  - 2019
N1  - https://doi.org/10.11648/j.awcn.20190502.12
DO  - 10.11648/j.awcn.20190502.12
T2  - Advances in Wireless Communications and Networks
JF  - Advances in Wireless Communications and Networks
JO  - Advances in Wireless Communications and Networks
SP  - 52
EP  - 56
PB  - Science Publishing Group
SN  - 2575-596X
UR  - https://doi.org/10.11648/j.awcn.20190502.12
AB  - In LTE there is a logical grouping of cells called Tracking Area (TA) and TAs are further grouped into Tracking Area List (TAL). Signaling overhead is greatly affected by the size of the TA and TAL respectively. Designing an optimum TAL would greatly reduce signaling overhead resulting from Tracking Area Update (TAU) and Paging procedures, which in return maximizes the network performance. This paper adopts a 2D Markov model that can be used for design optimization of TAL in LTE system by estimating the number of users in a cell within a time slot and the probability of the next location they might move to, as users move from and into cells periodically. The model was simulated in Matlab simulation software. The 2D Markov model was used to calculate TAU overhead, paging overhead and the total signaling overheads. The numerical results show that our model probably reduces the signaling overhead by about an average of 56% than that of the conventional TA scheme.
VL  - 5
IS  - 2
ER  -

Copy | Download