Call for Paper - May 2019 Edition
IJCA solicits original research papers for the May 2019 Edition. Last date of manuscript submission is April 20, 2019. Read More

Enhanced Resource Reservation Technique for Reduced Call Blocking in Femtocell Networks

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Amit Kumar Vishwakarma, Akhilesh Jain, Swapnil Jain
10.5120/ijca2016910086

Amit Kumar Vishwakarma, Akhilesh Jain and Swapnil Jain. Enhanced Resource Reservation Technique for Reduced Call Blocking in Femtocell Networks. International Journal of Computer Applications 144(1):1-7, June 2016. BibTeX

@article{10.5120/ijca2016910086,
	author = {Amit Kumar Vishwakarma and Akhilesh Jain and Swapnil Jain},
	title = {Enhanced Resource Reservation Technique for Reduced Call Blocking in Femtocell Networks},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2016},
	volume = {144},
	number = {1},
	month = {Jun},
	year = {2016},
	issn = {0975-8887},
	pages = {1-7},
	numpages = {7},
	url = {http://www.ijcaonline.org/archives/volume144/number1/25140-2016910086},
	doi = {10.5120/ijca2016910086},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Femtocell has proved to be a promising technology to enhance indoor coverage and network throughput. Dense deployment of femtocells facilitates efficient offloading of data traffic from the macrocell network to the femtocell network. However, this dense deployment may result in serious inter-femtocell interference. Considering limited coverage radius of the femtocell, frequent handovers is another challenge which may result in excessive call dropping. In order to improve QoS of mobiles users in terms of call blocking ratio, we suggest a predictive resource reservation technique. Our proposed technique first calculates the probability distribution of UEs’ locations in order to optimally deploy femtocells using Active LeZi Algorithm. Then, we use regression-based prediction algorithm (Box-Jenkins Model) to forecast the inter-call arrival and call duration distribution. Finally, we reserve the resources for users in multiple femtocells as to reduce the chances of call dropping. Our proposed technique has shown significantly improve the performance of the network in terms of call blocking, system throughput, and energy efficiency.

References

  1. A. K. Vishwakarma, A. Jain, and S. Jain, “Present and future research directions for cell selection in femtocell networks,” International Journal of Research in Technology, vol. 2, no. 2, pp. 5–10, April 2016.
  2. A. K. Sharma, P. N. Suman, and A. Jain, “Improving energy efficiency of femtocell network by joint estimation of downlink throughput and uplink power,” in Proceedings of the International Conference on Advanced Computing and Communication Systems, Jan 2015, pp. 1–5.
  3. H. Abu-Ghazaleh and A. Alfa, “Mobility prediction and spatial-temporal traffic estimation in wireless networks,” in Proceedings of the IEEE Vehicular Technology Conference, May 2008, pp. 2203–2207.
  4. J. Song, L. Li, and J. Han, “A fair scheduling algorithm combined with reservation resource compensation for wireless networks,” in Proceedings of the Personal, Indoor and Mobile Radio Communications, vol. 3, Sept 2003, pp. 2338–2342.
  5. M. Chowdhury, S. H. Chae, and Y. M. Jang, “Group handover management in mobile femtocellular network deployment,” in Proceedings of the Fourth International Conference on Ubiquitous and Future Networks, July 2012, pp. 162–165.
  6. N. Cai, J. Meng, W. Yan, Z. Bao, and P. Li, “Modeling and short-term forecasting of the electricity price based on fuzzy box-jenkins,” in Proceedings of the 8thWorld Congress on Intelligent Control and Automation, July 2010, pp. 4619–4622.
  7. W. Tang, M. Wong, Y. Wong, and T. Chung, “Load forecasting by fuzzy neural network in box-jenkins models,” in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, vol. 2, Oct 1998, pp. 1738–1743.
  8. H. El Hag and S. Sharif, “An adjusted arima model for internet traffic,” in Proceedings of the AFRICON, Sept 2007, pp. 1–6.
  9. S. Kang, S. Lee, Y. Won, and B. Seong, “On-line prediction of nonstationary variable-bit-rate video traffic,” IEEE Transactions on Signal Processing, vol. 58, no. 3, pp. 1219–1237, March 2010.
  10. B. Sklar, “Rayleigh fading channels in mobile digital communication systems .I. characterization,” IEEE Communications Magazine, vol. 35, no. 7, pp. 90–100, July 1997.
  11. E. C. Cherry, “A history of the theory of information,” Proceedings of the IEE - Part III: Radio and Communication Engineering, vol. 98, no. 55, pp. 383–393, Sept 1951.
  12. M. Deruyck, D. De Vulder,W. Joseph, and L. Martens, “Modelling the power consumption in femtocell networks,” in Proceedings of the IEEE Wireless Communications and Networking Conference Workshops (WCNCW), Apr 2012, pp. 30–35.
  13. X. Wang, A. V. Vasilakos, M. Chen, Y. Liu, and T. T. Kwon, “A Survey of Green Mobile Networks: Opportunities and Challenges,” ACM Mobile Networks and Applications, vol. 17, no. 1, pp. 4–20, Feb 2012.
  14. M. Z. Chowdhury and Y. M. Jang, “Handover management in highly dense femtocellular networks,” EURASIP Journal on Wireless Communications and Networking, pp. 1–21, Jan 2013.

Keywords

Femtocell, Resource Reservation, Throughput, Energy Efficiency