Performance Analysis of Cellular Radio System Using Artificial Neural Networks

Kriti Priya Gupta; Madhu Jain

doi:doi:10.11648/j.ajnna.20170301.12

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Performance Analysis of Cellular Radio System Using Artificial Neural Networks

Kriti Priya Gupta, Madhu Jain

Published in American Journal of Neural Networks and Applications (Volume 3, Issue 1)

Received: 26 December 2016 Accepted: 6 January 2017 Published: 17 March 2017

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Abstract

In this paper, we exploit one of the fastest growing techniques of Soft Computing, i.e. Artificial Neural Networks (ANNs) for obtaining various performance measures of a cellular radio system. A prioritized channel scheme with subrating is considered in which a fixed number of channels are reserved for handoff calls and in case of heavy traffic, these reserved channels are subrated into two channels of equal frequency to deal with more handoff calls. Two models dealing with infinite and finite number of subscribers are considered and the blocking probabilities of new and handoff calls are computed analytically as well as by using ANNs. A feedforward two-layer ANN is considered for obtaining the blocking probabilities. The backpropagation algorithm is used for training the ANN. The analytical and ANN results are compared by taking the numerical illustrations.

Published in	American Journal of Neural Networks and Applications (Volume 3, Issue 1)
DOI	10.11648/j.ajnna.20170301.12
Page(s)	5-13
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), 2017. Published by Science Publishing Group

Keywords

Artificial Neural Networks, Cellular Radio System, Handoff, Reserved Channels, Subrating, Backpropagation

References

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APA Style

Kriti Priya Gupta, Madhu Jain. (2017). Performance Analysis of Cellular Radio System Using Artificial Neural Networks. American Journal of Neural Networks and Applications, 3(1), 5-13. https://doi.org/10.11648/j.ajnna.20170301.12

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ACS Style

Kriti Priya Gupta; Madhu Jain. Performance Analysis of Cellular Radio System Using Artificial Neural Networks. Am. J. Neural Netw. Appl. 2017, 3(1), 5-13. doi: 10.11648/j.ajnna.20170301.12

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AMA Style

Kriti Priya Gupta, Madhu Jain. Performance Analysis of Cellular Radio System Using Artificial Neural Networks. Am J Neural Netw Appl. 2017;3(1):5-13. doi: 10.11648/j.ajnna.20170301.12

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@article{10.11648/j.ajnna.20170301.12,
  author = {Kriti Priya Gupta and Madhu Jain},
  title = {Performance Analysis of Cellular Radio System Using Artificial Neural Networks},
  journal = {American Journal of Neural Networks and Applications},
  volume = {3},
  number = {1},
  pages = {5-13},
  doi = {10.11648/j.ajnna.20170301.12},
  url = {https://doi.org/10.11648/j.ajnna.20170301.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20170301.12},
  abstract = {In this paper, we exploit one of the fastest growing techniques of Soft Computing, i.e. Artificial Neural Networks (ANNs) for obtaining various performance measures of a cellular radio system. A prioritized channel scheme with subrating is considered in which a fixed number of channels are reserved for handoff calls and in case of heavy traffic, these reserved channels are subrated into two channels of equal frequency to deal with more handoff calls. Two models dealing with infinite and finite number of subscribers are considered and the blocking probabilities of new and handoff calls are computed analytically as well as by using ANNs. A feedforward two-layer ANN is considered for obtaining the blocking probabilities. The backpropagation algorithm is used for training the ANN. The analytical and ANN results are compared by taking the numerical illustrations.},
 year = {2017}
}

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TY  - JOUR
T1  - Performance Analysis of Cellular Radio System Using Artificial Neural Networks
AU  - Kriti Priya Gupta
AU  - Madhu Jain
Y1  - 2017/03/17
PY  - 2017
N1  - https://doi.org/10.11648/j.ajnna.20170301.12
DO  - 10.11648/j.ajnna.20170301.12
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
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PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20170301.12
AB  - In this paper, we exploit one of the fastest growing techniques of Soft Computing, i.e. Artificial Neural Networks (ANNs) for obtaining various performance measures of a cellular radio system. A prioritized channel scheme with subrating is considered in which a fixed number of channels are reserved for handoff calls and in case of heavy traffic, these reserved channels are subrated into two channels of equal frequency to deal with more handoff calls. Two models dealing with infinite and finite number of subscribers are considered and the blocking probabilities of new and handoff calls are computed analytically as well as by using ANNs. A feedforward two-layer ANN is considered for obtaining the blocking probabilities. The backpropagation algorithm is used for training the ANN. The analytical and ANN results are compared by taking the numerical illustrations.
VL  - 3
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Author Information

Kriti Priya Gupta

Symbiosis Centre for Management Studies, NOIDA Faculty of Management, Symbiosis International University, Pune, India
Madhu Jain

Department of Mathematics, Indian Institute of Technology (IIT), Roorkee, India

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APA Style

Kriti Priya Gupta, Madhu Jain. (2017). Performance Analysis of Cellular Radio System Using Artificial Neural Networks. American Journal of Neural Networks and Applications, 3(1), 5-13. https://doi.org/10.11648/j.ajnna.20170301.12

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ACS Style

Kriti Priya Gupta; Madhu Jain. Performance Analysis of Cellular Radio System Using Artificial Neural Networks. Am. J. Neural Netw. Appl. 2017, 3(1), 5-13. doi: 10.11648/j.ajnna.20170301.12

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AMA Style

Kriti Priya Gupta, Madhu Jain. Performance Analysis of Cellular Radio System Using Artificial Neural Networks. Am J Neural Netw Appl. 2017;3(1):5-13. doi: 10.11648/j.ajnna.20170301.12

Copy | Download

@article{10.11648/j.ajnna.20170301.12,
  author = {Kriti Priya Gupta and Madhu Jain},
  title = {Performance Analysis of Cellular Radio System Using Artificial Neural Networks},
  journal = {American Journal of Neural Networks and Applications},
  volume = {3},
  number = {1},
  pages = {5-13},
  doi = {10.11648/j.ajnna.20170301.12},
  url = {https://doi.org/10.11648/j.ajnna.20170301.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20170301.12},
  abstract = {In this paper, we exploit one of the fastest growing techniques of Soft Computing, i.e. Artificial Neural Networks (ANNs) for obtaining various performance measures of a cellular radio system. A prioritized channel scheme with subrating is considered in which a fixed number of channels are reserved for handoff calls and in case of heavy traffic, these reserved channels are subrated into two channels of equal frequency to deal with more handoff calls. Two models dealing with infinite and finite number of subscribers are considered and the blocking probabilities of new and handoff calls are computed analytically as well as by using ANNs. A feedforward two-layer ANN is considered for obtaining the blocking probabilities. The backpropagation algorithm is used for training the ANN. The analytical and ANN results are compared by taking the numerical illustrations.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Performance Analysis of Cellular Radio System Using Artificial Neural Networks
AU  - Kriti Priya Gupta
AU  - Madhu Jain
Y1  - 2017/03/17
PY  - 2017
N1  - https://doi.org/10.11648/j.ajnna.20170301.12
DO  - 10.11648/j.ajnna.20170301.12
T2  - American Journal of Neural Networks and Applications
JF  - American Journal of Neural Networks and Applications
JO  - American Journal of Neural Networks and Applications
SP  - 5
EP  - 13
PB  - Science Publishing Group
SN  - 2469-7419
UR  - https://doi.org/10.11648/j.ajnna.20170301.12
AB  - In this paper, we exploit one of the fastest growing techniques of Soft Computing, i.e. Artificial Neural Networks (ANNs) for obtaining various performance measures of a cellular radio system. A prioritized channel scheme with subrating is considered in which a fixed number of channels are reserved for handoff calls and in case of heavy traffic, these reserved channels are subrated into two channels of equal frequency to deal with more handoff calls. Two models dealing with infinite and finite number of subscribers are considered and the blocking probabilities of new and handoff calls are computed analytically as well as by using ANNs. A feedforward two-layer ANN is considered for obtaining the blocking probabilities. The backpropagation algorithm is used for training the ANN. The analytical and ANN results are compared by taking the numerical illustrations.
VL  - 3
IS  - 1
ER  -

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