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Wireless Personal Communications

, Volume 104, Issue 2, pp 753–769 | Cite as

Evaluation of Random Physical Cell Id Assignment to Femtocells Under Dense Cell Deployment

  • Marek SedlacekEmail author
  • Robert Bestak
Article
  • 24 Downloads

Abstract

The paper discusses femtocell identification aspects in mobile networks such as long-term evolution (LTE) and LTE-advanced. Femtocells, or femto access points (FAPs), are new-class of base stations in addition to existing macro, microcells. Unlike these cells, femtocells implement automatic configuration principles. One of the main parameters in the automatic configuration process is among others an physical cell identifier. By considering two FAP deployment models, we discuss collision and confusion issues, which affect the proper physical cell id allocation. The first model represents a random deployment of FAPs within a (rural) macrocell area, whereas the second one, called dense urban model, constitutes placement of FAPs in a built-up area. The given study serves for the better understanding of interrelations between differently placed FAPs in term of collision and confusion events, and the obtained results can be used as a basis when designing an algorithm for automated assignment of physical cell identifier.

Keywords

Mobile networks Small cells SON Femtocells Femto access points Collision Confusion Physical ID 

Notes

References

  1. 1.
    IEEE Comsoc. (2015). Ten trends that tell where communication technologies are headed in 2015. January 2015. Available at www.comsoc.org.
  2. 2.
    UMTS Forum. (2015). 3G/4G subscriptions pass 3 billion milestone. In UMTS forum.Google Scholar
  3. 3.
    GSMA. (2014). Understanding the internet of things. In GSMA.Google Scholar
  4. 4.
    UMTS Forum. (2011). Mobile traffic forecasts 20102020 report. Report 44, UMTS Forum.Google Scholar
  5. 5.
    CISCO. Indoor small cells: A guide to mission critical communication. Available at http://www.cisco.com/c/dam/en/us/solutions/collateral/service-provider/small-cell-solutions/smallcells-infographic.pdf.
  6. 6.
    Small Cells Forum. Small cells: Elevator pitch. Available at http://www.smallcellforum.org/about/about-small-cells/elevator-pitch/.
  7. 7.
    Small Cells Forum. Small cells: Definition. Available at http://www.smallcellforum.org/about/about-small-cells/small-cell-definition/.
  8. 8.
    3GPP TR 36.300 V13.1.0. (2015). Evolved universal terrestrial radio access (E-UTRA) and evolved universal terrestrial radio access network (E-UTRAN) overall description; stage 2. In 3GPP TSG RAN.Google Scholar
  9. 9.
    3GPP TR 32.816. Study on management of evolved universal terrestrial radio access network (E-UTRAN) and evolved packet core (EPC). In 3GPP TSG RAN.Google Scholar
  10. 10.
    Feng, S., & Seidel, E. (2008). Self-organizing networks (SON) in 3GPP long term evolution. Germany: Nomor Research GmbH.Google Scholar
  11. 11.
    3GPP TS 36.211 V12.7.0. (2015). Physical channels and modulation. In 3rd Generation partnership project; technical specification group radio ccess network; evolved universal terrestrial radio access (E-UTRA).Google Scholar
  12. 12.
    3GPP TS 36.133. (2014). 3GPP technical specification group radio access network. In Evolved universal terrestrial radio access (E-UTRA), 3rd generation project partnership on requirements for support of radio resource management (release 12).Google Scholar
  13. 13.
    3GPP TR 36.902. (2010). Self-configuring and self-optimizing network (SON) use cases and solutions. In 3GPP TSG RAN.Google Scholar
  14. 14.
    Mathar, R., & Niessen, T. (2000). Optimum positioning of base stations for cellular radio networks. Wireless Networks, 6(6), 421–428.CrossRefzbMATHGoogle Scholar
  15. 15.
    Fewell, M. P. (2006). Area of common overlap of three circles. Technical Report DSTO-TN-0722. Maritime Operations Division, Australian Government, Department of Defence.Google Scholar
  16. 16.
    Librino, F., Levorato, M., & Zorzi, M. (2009). An algorithmic solution for computing circle intersection areas and its applications to wireless communications. In 7th International symposium on modeling and optimization in mobile, ad hoc, and wireless networks (pp. 1–10).Google Scholar
  17. 17.
    Nourani, F., & Jamali, M. (2010). Improved circles intersection algorithm for localization in wireless sensor networks. In 2010 11th ACIS international conference on software engineering artificial intelligence networking and parallel/distributed computing (SNPD) (pp. 129–133).Google Scholar
  18. 18.
    Lei, F., Wenliang, D., & Peng, N. (2005). A beacon-less location discovery scheme for wireless sensor networks. In INFOCOM 2005, Proceedings IEEE on 24th annual joint conference of the IEEE computer and communications societies. (Vol. 1, pp. 161–171).Google Scholar
  19. 19.
    Zaidi, M., Tourki, R., & Ouni, R. (2010). A new geometric approach to mobile position in wireless LAN reducing complex computations. In 2010 5th International conference on design and technology of integrated systems in nanoscale era (DTIS) (pp. 1–7).Google Scholar
  20. 20.
    3GPP. (2008). 3GPP R3-080376, SON use case: Cell Phy ID automated configuration. In 3GPP.Google Scholar
  21. 21.
    3GPP. (2008). 3GPP R1-082747, summary of options to extend the PCI space. In 3GPP.Google Scholar
  22. 22.
    Sungoh, K., & Neung-Hyung, L. (2011). Virtual extension of cell IDs in a femtocell environment. In 2011 IEEE on wireless communications and networking conference (WCNC) (pp. 428, 433, 28–31).Google Scholar
  23. 23.
    Bandh, T., Carle, G., & Sanneck, H. (2009). Graph coloring based physical-cell-ID assignment for LTE networks. In IWCMC (pp. 116–120).Google Scholar
  24. 24.
    Bandh, T., Carle, G., Sanneck, H., Schmelz, L. C., Romeikat, R., & Bauer, B. (2010). Optimized network configuration parameter assignment based on graph coloring. In 2010 IEEE on network operations and management symposium (NOMS) (pp. 19–23).Google Scholar
  25. 25.
    Furqan, A., Olav, T., Matti, P., Juha-Matti, K., Chia-Hao, Y., & Miko, A. (2010). Distributed graph coloring for self-organization in LTE networks. Journal of Electrical and Computer Engineering, 2010, 1–10.Google Scholar
  26. 26.
    Yanguang, L., Wenjing, L., Heng, Z., & Weihao, L. (2010). Graph based automatic centralized PCI assignment in LTE. In 2010 IEEE symposium on computers and communications (ISCC) (pp. 919–921).Google Scholar
  27. 27.
    Yi, W., Jiang, H., Ye, W., & Dongmei, Z. (2010). Physical cell identity self-organization for home eNodeB deployment in LTE. In 6th International conference on wireless communications networking and mobile computing (WiCOM) (p. 1).Google Scholar
  28. 28.
    3GPP. (2008). 3GPP R2-084563. In New solution for CSG-cell identification. 3GPP.Google Scholar
  29. 29.
    Qualcomm Research. (2013). Neighborhood small cells for hyperdense deployments: Taking HetNets to the next level. February 8 2013. Available at https://www.qualcomm.com/media/documents/files/qualcomm-research-neighborhood-small-cell-deployment-model.pdf.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Telecommunication EngineeringCzech Technical University in PraguePragueCzech Republic

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