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A Cooperative Skip HO Scheme Based on Dwell-Time in Dense Small Cell Networks

  • Han Yan
  • Gang Chuai
  • Weidong Gao
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)

Abstract

In order to meet the growing demand for traffic, in the next generation (5G) mobile communication network, the network densification is adopted to achieve greater spatial spectral utilization rate. Thus it can improve the overall network capacity. However, the network densification brings a series of challenges, especially for the mobility management in UDN. The dense deployment of base station (BS) makes the handover (HO) rate too high, which in turn leads to too much HO signaling delay and cost. Thus it may offset the throughput gain that benefit from intensive. In order to solve this problem, this paper proposed a cooperative Skip HO scheme based on estimated dwell time. In this scenario, when the predicted dwell time is less than the threshold, a skip HO will be triggered to enter the cooperative transmission phase. Moreover, in this paper, the method of stochastic geometry was used to derive the triggering probability of the skip handover, the outage probability of the entire network, and the average user throughput. The simulation results show that the proposed method has improved the throughput performance compared with the traditional best connection method and the alternate skip handover method proposed in other literatures.

Notes

Acknowledgment

This work described in this paper was supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China (Grant No. 2016ZX03001009-003).

References

  1. 1.
    Hoang, N.D., Nguyen, N.H., Sripimanwat, K.: Cell selection schemes for femtocell-to-femtocell handover deploying mobility prediction and downlink capacity monitoring in cognitive femtocell networks. In: TENCON 2014-2014 IEEE Region 10 Conference, pp. 1–5. IEEE (2014)Google Scholar
  2. 2.
    Lee, C.H., Kim, J.H.: Time-of-stay estimation-based cell selection scheme in multitier heterogeneous mobile networks. IEEE Commun. Lett. 19(9), 1596–1599 (2015)Google Scholar
  3. 3.
    Arshad, R., Elsawy, H., Sorour, S., et al.: Cooperative Handover Management in Dense Cellular Networks (2017)Google Scholar
  4. 4.
    Andrews, J.G., Baccelli, F., Ganti, R.K.: A tractable approach to coverage and rate in cellular networks. IEEE Trans. Commun. 59(11), 3122–3134 (2011)Google Scholar
  5. 5.
    Guo, A., Haenggi, M.: Spatial stochastic models and metrics for the structure of base stations in cellular networks. IEEE Trans. Wireless Commun. 12(11), 5800–5812 (2013)Google Scholar
  6. 6.
    Lu, W., Renzo, M.D.: Stochastic geometry modeling of cellular networks: analysis, simulation and experimental validation. In: ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, pp. 179–188. ACM (2015)Google Scholar
  7. 7.
    Jo, H.S., Sang, Y.J., Xia, P., et al.: Heterogeneous cellular networks with flexible cell association: a comprehensive downlink SINR analysis. IEEE Trans. Wireless Commun. 11(10), 3484–3495 (2011)Google Scholar
  8. 8.
    Hong, Y., Xu, X., Tao, M., et al.: Cross-tier handover analyses in small cell networks: a stochastic geometry approach. In: 2015 IEEE International Conference on Communications (ICC), pp. 3429–3434. IEEE (2015)Google Scholar
  9. 9.
    Arshad, R., Elsawy, H., Sorour, S., et al.: Velocity-aware handover management in two-tier cellular networks. IEEE Trans. Wireless Commun. PP(99), 1 (2016)Google Scholar
  10. 10.
    Romanous, B., Bitar, N., Imran, A., et al.: Network densification: challenges and opportunities in enabling 5G. In: IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks, pp. 129–134. IEEE (2015)Google Scholar
  11. 11.
    Ge, X., Tu, S., Mao, G., et al.: 5G ultra-dense cellular networks. IEEE Wirel. Commun. 23(1), 72–79 (2015)Google Scholar
  12. 12.
    Bao, W., Liang, B.: Stochastic geometric analysis of user mobility in heterogeneous wireless networks. IEEE J. Sel. Areas Commun. 33(10), 2212–2225 (2015)Google Scholar
  13. 13.
    Dhillon, H.S., Ganti, R.K., Baccelli, F., et al.: Modeling and analysis of K-tier downlink heterogeneous cellular networks. IEEE J. Sel. Areas Commun. 30(3), 550–560 (2012)Google Scholar
  14. 14.
    Jansen, T., Balan, I., Turk, J., et al.: Handover parameter optimization in LTE self-organizing networks. In: Vehicular Technology Conference Fall, pp. 1–5. IEEE (2010)Google Scholar
  15. 15.
    Munoz, P., Barco, R., Fortes, S.: Conflict resolution between load balancing and handover optimization in LTE networks. IEEE Commun. Lett. 18(10), 1795–1798 (2014)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Key Laboratory of Universal Wireless Communications, Ministry of EducationBeijing University of Posts and TelecommunicationsBeijingChina

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