Skip to main content
SpringerLink
Log in

Congestion probabilities in the X2 link of LTE networks

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

In this paper, first we review two multirate loss models, whereby we can assess the call-level QoS of the Long Term Evolution X2 link supporting calls of different service-classes with fixed bandwidth requirements. The X2 interface directly connects two neighboring evolved NodeBs and is mainly responsible for the transfer of user-plane and control-plane data during a handover. In both models, the X2 interface is modelled as a link of fixed capacity. Handover calls are accepted in the X2 link whenever there exists available bandwidth, i.e., no QoS guarantee is achieved for high-speed calls. Secondly, we propose three multirate loss models where calls arrive in the X2 link according to a quasi-random process and compete for the available bandwidth under the Multiple Fractional Channel Reservation (MFCR) policy, the Bandwidth Reservation (BR) policy and the Complete Sharing (CS) policy. The MFCR/BR policies allow the reservation of real/integer number of channels, respectively, in order to benefit high-speed calls. The CS policy allows calls to enter the system when there exists available bandwidth (no reservation is allowed). We propose approximate but recursive formulas for the calculation of time and call congestion probabilities as well as link utilization for all three policies. The accuracy of the proposed formulas is verified through simulation and found to be highly satisfactory.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Holma, H., & Toskala, A. (2011). LTE for UMTS: Evolution to LTE advanced. New York: Wiley.

    Book  Google Scholar 

  2. Ahmad, R., Sundararajan, E., & Othman, N. (2017). Handover in LTE-advanced wireless networks: state of art and survey of decision algorithms. Telecommunication Systems, 66(3), 533–558.

    Article  Google Scholar 

  3. Blogowski, A., Klopfenstein, O. & Renard, B. (2012). Dimensioning X2 backhaul link in LTE networks. In Proceedings of IEEE ICC, Ottawa, Canada (pp. 2768–2773).

  4. Peng, M., Liang, D., Wei, Y., Li, J., & Chen, H. (2013). Self-configuration and self-optimization in LTE-advanced heterogeneous networks. IEEE Communications Magazine, 51(5), 36–45.

    Article  Google Scholar 

  5. Widjaja, I, & Roche, H. (2009). Sizing X2 bandwidth for Inter-connected eNBs. In Proceedings of IEEE VTC Fall, Anchorage, Alaska, USA (pp. 1–5).

  6. Renard, B., Elayoubi, S., & Simonian, A. (2012). A dimensioning method for the LTE X2 interface. In Proceedings of IEEE WCNC, Shanghai, China (pp. 2718–2723).

  7. Akimaru, H., & Kawashima, K. (1999). Teletraffic—Theory and applications (2nd ed.). Berlin: Springer.

    Book  Google Scholar 

  8. Frost, V., & Melamed, B. (1994). Traffic modeling for telecommunications networks. IEEE Communications Magazine, 32(3), 70–81.

    Article  Google Scholar 

  9. Lam, D., Cox, D., & Widom, J. (1997). Teletraffic modeling for personal communications services. IEEE Communications Magazine, 35(2), 79–87.

    Article  Google Scholar 

  10. Kaufman, J. (1981). Blocking in a shared resource environment. IEEE Transactions on Communications, 29(10), 1474–1481.

    Article  Google Scholar 

  11. Roberts, J. (1981). A service system with heterogeneous user requirements. In G. Pujolle (Ed.), Performance of data communications systems and their applications (pp. 423–431). Amsterdam: North Holland.

    Google Scholar 

  12. Panagoulias, P., & Moscholios, I. (2016). Evaluation of multirate loss models for the X2 link of LTE networks. In Proceedings of IEICE ICTF, Patras, Greece.

  13. Roberts, J. (1983). Teletraffic models for the telecom 1 integrated services network. In Proceedings of 10th ITC, paper 1.1-2, Montreal, Canada.

  14. Rahman, M., & Alfa, A. (2009). Computationally efficient method for analyzing guard channel schemes. Telecommunication Systems, 41(1), 1–11.

    Article  Google Scholar 

  15. Stasiak, M., Glabowski, M., Wisniewski, A., & Zwierzykowski, P. (2011). Modeling and dimensioning of mobile networks. New York: Wiley.

    Google Scholar 

  16. Moscholios, I., Vardakas, J., Logothetis, M., & Boucouvalas, A. (2011). A batched Poisson multirate loss model supporting elastic traffic under the bandwidth reservation policy. In Proceedings of IEEE ICC, Kyoto, Japan (pp. 1–6).

  17. Moscholios, I., Vardakas, J., Logothetis, M., & Koukias, M. (2013). A quasi-random multirate loss model supporting elastic and adaptive traffic under the bandwidth reservation policy. International Journal on Advances in Networks and Services, 6(3&4), 163–174.

    Google Scholar 

  18. Abdulova, V., & Aybay, I. (2014). Performance evaluation of non-prioritized and prioritized call admission control schemes in wireless cellular networks. Wireless Personal Communications, 78(1), 69–84.

    Article  Google Scholar 

  19. Omheni, N., Gharsallah, A., & Zarai, F. (2018). An enhanced radio resource management based MIH policies in heterogeneous wireless networks. Telecommunication Systems, 67(4), 577–592.

    Article  Google Scholar 

  20. Cruz-Prez, F., Vazquez-Avila, J., & Ortigoza-Guerrero, L. (2004). Recurrent formulas for the multiple fractional channel reservation strategy in multi-service mobile cellular networks. IEEE Communications Letters, 8(10), 629–631.

    Article  Google Scholar 

  21. Vazquez-Avila, J., Cruz-Prez, F., & Ortigoza-Guerrero, L. (2006). Performance analysis of fractional guard channel policies in mobile cellular networks. IEEE Transactions on Wireless Communications, 5(2), 301–305.

    Article  Google Scholar 

  22. Tsang, D., & Ross, K. (1990). Algorithms to determine exact blocking probabilities for multirate tree networks. IEEE Transactions on Communications, 38(8), 1266–1271.

    Article  Google Scholar 

  23. Ni, J., Tsang, D., Tatikonda, S., & Bensaou, B. (2007). Optimal and structured call admission control policies for resource-sharing systems. IEEE Transactions on Communications, 55(1), 158–170.

    Article  Google Scholar 

  24. Moscholios, I., Logothetis, M., Vardakas, J., & Boucouvalas, A. (2015). Performance metrics of a multirate resource sharing teletraffic model with finite sources under the threshold and bandwidth reservation policies. IET Networks, 4(3), 195–208.

    Article  Google Scholar 

  25. Abdulova, V., & Aybay, I. (2015). Prioritized new call threshold policy for wireless cellular networks. Wireless Personal Communications, 85(4), 2549–2563.

    Article  Google Scholar 

  26. Moscholios, I., Vassilakis, V., Logothetis, M., & Boucouvalas, A. (2016). A probabilistic threshold-based bandwidth sharing policy for wireless multirate loss networks. IEEE Wireless Communications Letters, 5(3), 304–307.

    Article  Google Scholar 

  27. Moscholios, I., Logothetis, M., & Boucouvalas, A. (2016). Blocking probabilities of elastic and adaptive calls in the Erlang multirate loss model under the threshold policy. Telecommunication Systems, 62(1), 245–262.

    Article  Google Scholar 

  28. Moscholios, I., Logothetis, M., & Shioda, S. (2017). Performance evaluation of multirate loss systems supporting cooperative users with a probabilistic behavior. IEICE Transactions on Communications, E100-B(10), 1778–1788.

  29. Kaufman, J., & Rege, K. (1996). Blocking in a shared resource environment with batched Poisson arrival processes. Performance Evaluation, 24(4), 249–263.

    Article  Google Scholar 

  30. Moscholios, I., Kallos, G., Vassilakis, V., & Logothetis, M. (2014). Congestion probabilities in CDMA-based networks supporting batched Poisson input traffic. Wireless Personal Communications, 79(2), 1163–1186.

    Article  Google Scholar 

  31. Moscholios, I., Vassilakis, V., & Sarigiannidis, P. (2018). Performance modelling of a multirate loss system with batched Poisson arrivals under a probabilistic threshold policy. IET Networks, 7(4), 242–247.

    Article  Google Scholar 

  32. Mehmet-Ali, M. (1999). Call-burst blocking and call admission control in a broadband network with bursty sources. Performance Evaluation, 38(1), 1–19.

    Article  Google Scholar 

  33. Moscholios, I., Nikolaropoulos, P., & Logothetis, M. (2003). Call level blocking of ON–OFF traffic sources with retrials under the complete sharing policy. In Proceedings of 18th ITC, Berlin, Germany (pp. 811–820).

  34. Moscholios, I., Logothetis, M., & Koukias, M. (2007). An ON–OFF multirate loss model of finite sources. IEICE Transactions on Communications, E90-B(7), 1608–1619.

  35. Yashkov, S., & Yashkova, A. (2007). Processor sharing: A survey of the mathematical theory. Automation and Remote Control, 68(9), 1662–1731.

    Article  Google Scholar 

  36. Lei, L., Lin, C., Cai, J., & Shen, X. (2008). Flow-level performance of opportunistic OFDM-TDMA and OFDMA networks. IEEE Transactions on Wireless Communications, 7(12), 5461–5472.

    Article  Google Scholar 

  37. Yong, S., Song, W., & Zhong, Z. (2013). Resource allocation for aggregate multimedia and healthcare services over heterogeneous multi-hop wireless networks. Wireless Personal Communications, 69(1), 229–251.

    Article  Google Scholar 

  38. Moscholios, I., Vardakas, J., Logothetis, M., & Boucouvalas, A. (2013). Congestion probabilities in a batched Poisson multirate loss model supporting elastic and adaptive traffic. Annals of Telecommunications, 68(5), 327–344.

    Article  Google Scholar 

  39. Moscholios I., Logothetis M., Boucouvalas A., & Vassilakis V. (2015). An Erlang multirate loss model supporting elastic traffic under the threshold policy. In Proceedings of IEEE ICC, London, U.K.

  40. Stasiak M. (2016). Queuing systems for the internet. IEICE Transactions on Communications, E99-B(6), 1234–1242.

  41. Hanczewski, S., Stasiak, M., & Weissenberg, J. (2018). Queueing model of a multiservice system with elastic and adaptive traffic. Computer Networks, 147, 146–161.

    Article  Google Scholar 

  42. Li, X., Toseef, U., Dulas, D., Bigos, W., Gorg, C., Timm-Giel, A., et al. (2013). Dimensioning of the LTE access network. Telecommunication Systems, 52(4), 2637–2654.

    Article  Google Scholar 

  43. Glabowski, M., Kaliszan, A., & Stasiak, M. (2008). Asymmetric convolution algorithm for blocking probability calculation in full-availability group with bandwidth reservation. IET Circuits, Devices & Systems, 2(1), 87–94.

    Article  Google Scholar 

  44. Huang, Q., Ko, K., & Iversen, V. (2011). A new convolution algorithm for loss probability analysis in multiservice networks. Performance Evaluation, 68(1), 7687.

    Article  Google Scholar 

  45. Stasiak, M., Parniewicz, D., & Zwierzykowski, P. (2013). Traffic engineering for multicast connections in multiservice cellular network. IEEE Transactions on Industrial Informatics, 9(1), 262–270.

    Article  Google Scholar 

  46. Moscholios, I., Logothetis, M., Vardakas, J., & Boucouvalas, A. (2015). Congestion probabilities of elastic and adaptive calls in Erlang–Engset multirate loss models under the threshold and bandwidth reservation policies. Computer Networks, 92(1), 1–23.

    Article  Google Scholar 

  47. Ge, X., Tu, S., Han, T., Li, Q., & Mao, G. (2015). Energy efficiency of small cell backhaul networks based on Gauss Markov mobile models. IET Networks, 4(2), 158–167.

    Article  Google Scholar 

  48. Malila, B., Falowo, O., & Ventura, N. (2017). An energy efficiency analysis for outdoor wireless small cell backhaul. In Proceedings of IEEE WCNC, San Francisco, USA.

  49. Ge, X., Cheng, H., Mao, G., Yang, Y., & Tu, S. (2016). Vehicular communications for 5G cooperative small cell networks. IEEE Transactions on Vehicular Technology, 65(10), 7882–7894.

    Article  Google Scholar 

  50. Assefa, T., Hoque, R., Tragos, E., & Dimitropoulos, X. (2017). SDN-based local mobility management with X2-interface in femtocell networks. In Proceedings of IEEE CAMAD, Lund, Sweden.

  51. Celebi, H., & Gvenc, I. (2017). Load analysis and sleep mode optimization for energy-efficient 5G small cell networks. In Proceedings of IEEE ICC Workshop on 5G ultra dense networks, Paris, France.

  52. Ren, Y., Chen, J., & Chin, J. (2018). Impacts of S1 and X2 Interfaces on eMBMS handover failure: Solution and performance analysis. IEEE Transactions on Vehicular Technology, 67(7), 6599–6614.

    Article  Google Scholar 

  53. Park G., & Song H. (2018). Cooperative base station caching and X2 link traffic offloading system for video streaming over SDN-enabled networks. IEEE Transactions on Mobile Computing. https://doi.org/10.1109/TMC.2018.2869756.

  54. Zonoozi, M., & Dassanayake, P. (1997). User mobility modeling and characterization of mobility patterns. IEEE Journal on Selected Areas in Communications, 15(7), 1239–1252.

    Article  Google Scholar 

  55. Yeung, K., & Nanda, S. (1996). Channel management in microcell/macrocell cellular radio systems. IEEE Transactions on Vehicular Technology, 45(4), 601–612.

    Article  Google Scholar 

  56. Thomas, R., Gilbert, H., & Mazziotto, G. (1988). Influence of the movement of the mobile station on the performance of a radio cellular network. In Proceedings of 3rd nordic seminar, paper 9.4, Copenhagen, Denmark.

  57. Xie, H., & Goodman, D. (1993). Mobility models and biased sampling problem. In Proceedings of 2nd International Conference on Universal Personal Communications, Ottawa, Canada.

  58. Roy, R. (2011). Handbook of mobile ad hoc networks for mobility models. Berlin: Springer.

    Book  Google Scholar 

  59. Stamatelos, G., & Hayes, J. (1994). Admission control techniques with application to broadband networks. Computer Communications, 17(9), 663–673.

    Article  Google Scholar 

  60. Simscript III. http://www.simscript.com. Last accessed November, 2018

Download references

Author information

Authors and Affiliations

  1. Department of Informatics and Telecommunications, University of Peloponnese, Tripolis, Greece

    P. I. Panagoulias & I. D. Moscholios

Authors
  1. P. I. Panagoulias
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. I. D. Moscholios
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to I. D. Moscholios.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Panagoulias, P.I., Moscholios, I.D. Congestion probabilities in the X2 link of LTE networks. Telecommun Syst 71, 585–599 (2019). https://doi.org/10.1007/s11235-018-00537-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-018-00537-5

Keywords

Search

Navigation