Skip to main content
Log in

Analysis of Neighbourhood Relations for Femtocell Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Nowadays mobile operators are trying to find an economic solution to improve coverage, mainly indoor, and to meet exponentially growing data traffic demands. A cost-effective means to manage these challenges represent small cells, such as metrocells or femtocells. However, in highly populated areas, a large number of these cells can be deployed and can operate in a network. Thus, to enable smooth and simple deployment of small cells, self-organizing concept has to be employed, including an automatic cell identifier assignment mechanism.Due to limited number of available cell identifiers, Physical Cell Identities (PCI), a de-sign of the PCI assignment algorithm is a challenging task, especially in dense small cell environment. In our work, we focus on neighbour relations of densely deployed femtocells because number of neighbouring cells and their relations have direct impact on the PCI assignment algorithm design. Since femtocells are not conventionally deployed by operator but by users, the cells tend to form cell clusters. We investigate these clusters of cells and their structures under different scenarios such as number of cells or radius of cell. Based on our study, the PCI assignment algorithms can be adapted and can be optimised to actual state of a network.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. LTE vs ARPU Data Takes Over. (2013). Resource document. Network Strategies Limited. http://www.strategies.nzl.com/wpapers/2013014.htm. Accessed at 14 Aug 2015.

  2. Mobile 2014—Highlights and Milestones. (2014). Resource document. Chetan Sharma Consulting. http://www.chetansharma.com/blog/2014/12/29/mobile-2014-highlights-and-milestones/. Accessed at 14 Aug 2015.

  3. Global Mobile Market Update. (2012). Resource document. Chetan Sharma Consulting. http://www.chetansharma.com/GlobalMobileMarketUpdate2012.htm. Accessed 14 Aug 2015.

  4. SCF104, Urban Small Cells: Release Four Overview. (2014). Small cells forum.

  5. 3GPP TS 36.300. (2014). 3rd Generation partnership project; technical specification group radio access network; evolved universal terrestri-al radio access (E-UTRA) and evolved universal terrestrial radio ac-cess network (E-UTRAN); overall description; stage 2 (release 12). 3rd Generation project partnership.

  6. 3GPP R3-080376. (2008). Nokia Siemens Networks and Nokia, SON use case: Cell Phy ID automated configuration. 3rd Generation project part-nership TSG RAN meeting 59.

  7. Liu, Y., Li, W., Zhang, H., & Yu, L. (2010). Distributed PCI assignment in LTE based on consultation mechanism. 6th international conference on wireless communications net-working and mobile computing (WiCOM), pp. 1–4. doi:10.1109/WICOM.2010.5601210

  8. Wu,T., Rui, L., Xiong, A., & Guo, S. (2010). An automation PCI allocation method for eNodeB and home eNodeB cell. 6th international conference on wireless communications networking and mobile computing (WiCOM), pp. 1–4. doi:10.1109/WICOM.2010.5600764

  9. Abdullah, L. M., et al. (2014). New graph colouring algorithm for resource allocation in large-scale wireless networks. IEEE 5th, control and system graduate research colloquium (ICSGRC), pp. 233–238.

  10. Amirijoo, M., et al. (2008). Neighbor cell relation list and physical cell Identity Self-Organization in LTE. IEEE international conference on communications workshops, ICC workshops ’08, pp. 37–41. doi:10.1109/ICCW.2008.12

  11. Diab, A., & Mitschele-Thiel, A. (2012). Comparative evaluation of distribut-ed physical cell identity assignment schemes for LTE-advanced systems. 7th ACM workshop on performance monitoring and measurement of heterogeneous wireless and wired networks (PM2HW2N ’12) (pp. 61–68). New York, USA: ACM. doi:10.1145/2387191.2387201

  12. Yu, J., Peng, M., & Li, Y. (2012). A physical cell identity self-organization algorithm in LTE-advanced systems. 7th International ICST conference on communications and networking in China (CHINACOM), pp. 576–580.

  13. Zhang, X., et al. (2013). Dynamic PCI assignment in two-tier networks based on cell activity prediction. Electronics Letters, 49(24), 1570–1572.

    Article  Google Scholar 

  14. 3GPP R2-084563. (2008). ZTE, new solution for CSG-cell identification. 3rd Generation project partnership, TSG RAN Meeting 63.

  15. 3GPP TS 36.133. (2014). 3GPP technical specification group radio ac-cess network; evolved universal terrestrial radio access (E-UTRA). Requirements for support of radio resource management (release 12). 3rd Generation Project Partnership.

  16. Skiena, S. (1990). Breadth-first and depth-first search. Implementing discrete mathematics: combinatorics and graph theory with mathe-matica (pp. 95–97). Reading, MA: Addison-Wesley.

  17. Lichtblau, B., & Dittrich, A. (2014). Probabilistic breadth-first search—A method for evaluation of network-wide broadcast protocols. 6th International conference on new technologies, mobility and security (NTMS), pp. 1–6. doi:10.1109/NTMS.2014.6814046

  18. Fu, Z., et al. (2014). Parallel breadth first search on GPU clusters. IEEE International Conference on big data (big data), pp. 110–118.

  19. Cormen, T., et al. (2001). Introduction to algorithms (2nd ed.). Cambridge MA: MIT Press.

    MATH  Google Scholar 

  20. Skiena, S. (2008). The algorithm design manual (2nd ed.). New York: Springer.

    Book  MATH  Google Scholar 

  21. Mitzenmacher, M., & Upfal, E. (2005). Probability and computing: Ran-domized algorithms and probabilistic analysis. Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  22. Motwani, R., & Raghavan, P. (1995). Randomized algorithms. New York: Cambridge University Press. ISBN 0-521-47465-5.

    Book  MATH  Google Scholar 

  23. GraphDensity. (2015). Resource document. Wolfram mathematica website. http://reference.wolfram.com/language/ref/GraphDensity.html. Accessed 17 Jan (2015).

  24. Welsh, D. J., & Powell, M. B. (1967). An upper bound for the chromatic number of a graph and its application to timetabling problems. The Computer Journal, 10(1), 85–86.

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marek Sedlacek.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sedlacek, M., Bestak, R. Analysis of Neighbourhood Relations for Femtocell Networks. Wireless Pers Commun 96, 5239–5252 (2017). https://doi.org/10.1007/s11277-016-3738-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3738-2

Keywords

Navigation