Self-optimization in LTE: An Approach to Reduce Call Drops in Mobile Network

  • Divya Mishra
  • Anuranjan Mishra
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 958)


Unwanted terminations of an on-going wireless conversation become the biggest issue of the whole world. Call drop degrades the voice call quality and impacted the quality of service of the network. Researchers, industries, and telecom- vendors are bothered to improve the call quality in existing telecom infrastructure and already proposed many valuable solutions which have own pros and cons but still there is no optimized reliable solution to reduce call drop has been deployed till now. This research paper focuses on some background reasons for call drop in existing wireless infrastructure and proposed the self-optimization concept to handle the overall network issue automatically in perspective of call drops minimization in mobile networks. This Research paper proposed some robust functionality of self-optimizing network such as automatic neighbor list optimization, mobility load balancing optimization and handover optimization approach used to improve voice call quality and make a self-automated mobile network that would be fruitful to reduce call drop rate.


Call drop Long term evolution Self-optimization network Automatic neighbor list optimization Handover optimization Mobility Robustness Optimization 


  1. 1.
    Telecom Regulatory Authority of India: Technical Paper on Call Drop in Cellular Networks (2016).
  2. 2.
    Feng, S., Seidel, E.: Self-organizing networks (SON) in 3GPP long term evolution. Nomor Research GmbH, Munich, Germany, 20 May 2008Google Scholar
  3. 3.
    NGMN Alliance: Next generation mobile networks use cases related to self organising network, overall description, 31 May 2007Google Scholar
  4. 4.
    Nohrborg, M.: Self-organizing network (2017).
  5. 5.
    Cisco: SON and the LTE Challenge: How to Get More for Less White Paper (2015).
  6. 6.
    Hämäläinen, S., Sanneck, H., Sartori, C.: LTE Self-Organizing Networks (SON). ISBN 9781119970675Google Scholar
  7. 7.
    Nokia Siemens Networks: Self-Organizing Network (SON) Introducing the Nokia Siemens Networks SON Suite – an efficient, future-proof platform for SON.
  8. 8.
    Dahlén, A., Johansson, A., Gunnarsson, F., Moe, J., Rimhagen, T., Kallin, H.: Evaluations of LTE automatic neighbor relations (2011). 978-1-4244-8331-0/11/$26.00 ©2011 IEEE9Google Scholar
  9. 9.
    Sauter, M.: From GSM to LTE an Introduction to Mobile Networks and Mobile Broadband. Wireless Moves, Germany. ISBN 978-0-470-66711-8Google Scholar
  10. 10.
    3GPP: Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access (E-UTRAN); Overall description; Stage 2, 3rd Generation Partnership Project (3GPP), TS 36.300, September 2008.
  11. 11.
    NEC Corporation: Self Organizing Network: “NEC’s proposals for next-generation radio network management”. White paper, February 2009Google Scholar
  12. 12.
    Balapuwaduge, I.A.M., Jiao, L., Pla, V.: Channel assembling with priority-based queues in cognitive radio networks: strategies and performance evaluation. IEEE Trans. Wireless Commun. 13, 630–645 (2014)CrossRefGoogle Scholar
  13. 13.
    Li, X.J., Chong, P.H.J.: A dynamic channel assignment scheme for TDMA-based multihop cellular networks. IEEE Trans. Wireless Commun. 7 (2008)Google Scholar
  14. 14.
    Nokia buys Eden Rock for self-organizing networks (German).
  15. 15.
    Monica, C.H., Bhavani, K.V.L.: A bandwidth degradation technique to reduce call dropping probability in mobile network systems. Telkomnika Indones. J. Electr. Eng. 16, 303–307 (2015)Google Scholar
  16. 16.
    Shiokawa, S., Ishizaka, M.: Call admission scheme based on estimation of call dropping probability in wireless network (2002). 0-7803-7589-0/02/$17.00 ©2002 IEEEGoogle Scholar
  17. 17.
    Khara, S., Saha, S., Mukhopadhyay, A.K., Ghosh, C.K.: Call dropping analysis in a UMTS/WLAN integrated cell. Int. J. Inf. Technol. Knowl. Manag. 2, 411–415 (2010)Google Scholar
  18. 18.
    Lin, Y.-B., Mohan, S., Noerpel, A.: Queuing priority channel assignment strategies for pcs handoff and initial access. IEEE Trans. Veh. Technol. 43, 704–712 (1994)CrossRefGoogle Scholar
  19. 19.
    Iraqi, Y., Boutaba, R.: Handoff and call dropping probabilities in wireless cellular networks. In: International Conference on Wireless Networks, Communications and Mobile Computing (2005)Google Scholar
  20. 20.
    Döttling, M., Viering, I.: Challenges in mobile network operation: towards self-optimizing networks (2009). 978-1-4244-2354-5/09/$25.00 ©2009 IEEEGoogle Scholar
  21. 21.
    Hu, H., Zhang, J., Zheng, X., Yang, Y., Wu, P.: Self-configuration and self-optimization for LTE networks. IEEE Commun. Mag. 48, 94–100 (2010)CrossRefGoogle Scholar
  22. 22.
    Moysen, J., Giupponi, L.: From 4G to 5G: self-organized network management meets machine learning. arXiv:1707.09300v1 [cs.NI], 28 July 2017
  23. 23.
    Gacanin, H., Ligata, A.: Wi-Fi self-organizing networks: challenges and use cases. IEEE Commun. Mag. 55, 158–164 (2017)CrossRefGoogle Scholar
  24. 24.
  25. 25.
    Oliveira, C., Kim, J.B., Suda, T.: An adaptive bandwidth reservation scheme for high-speed multimedia wireless networks. IEEE J. Sel. Areas Commun. 16, 858–874 (1998)CrossRefGoogle Scholar
  26. 26.
    Lobinger, A., Stefanski, S., Jansen, T.: Coordinating handover parameter optimization and load balancing in LTE self-optimizing networks. In: 73rd IEEE Vehicular Technology Conference (VTC Spring) (2011)Google Scholar
  27. 27.
    The Big Difference in Cell Phone Technology: CDMA vs. GSM.
  28. 28.
  29. 29.

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Noida International UniversityNoidaIndia

Personalised recommendations