Skip to main content
SpringerLink
Log in

Dynamic Self-Optimization of the Antenna Tilt for Best Trade-off Between Coverage and Capacity in Mobile Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

One major factor influencing the coverage and capacity in mobile networks is related to the configuration of the antennas and especially the antenna tilt angle. By utilizing antenna tilt, signal reception within a cell can be improved and interference radiation towards other cells can be effectively reduced, which leads to a higher signal-to-interference-plus-noise ratio received by the users and increased sum data rate in the network. In this work, a method for capacity and coverage optimization using base station antenna electrical tilt in mobile networks is proposed. It has the potential to improve network performance while reducing operational costs and complexity, and to offer better quality of experience for the mobile users. Our solution is based on the application of reinforcement learning and the simulation results show that the algorithm improves significantly the overall data rate of the network, as compared to no antenna tilt optimization. The analysis in this paper focuses on the downlink of the cellular system. For the simulation experiments a multicellular and sectorized mobile network in an urban environment and randomly distributed user terminals are considered. The main contribution in this work is related to the development of a learning algorithm for automated antenna tilting.

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
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Hamalainen, S., Sanneck, H., & Sartori, C. (2011). LTE self-organising networks (SON): Network management automation for operational efficiency. Wiley.

  2. Cisco (2015). Visual networking index (VNI). http://www.cisco.com/c/en/us/solutions/service-provider/visual-networking-index-vni/index.html. Aaccessed September 2015.

  3. Yilmaz, O., Hamalainen, S., & Hamalainen, J. (2009). Comparison of remote electrical and mechanical antenna downtilt performance for 3GPP LTE. Vehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th. pp. 1–5.

  4. Yilmaz, O., Hamalainen, J., & Hamalainen, S. (2010). Self-optimization of remote electrical tilt. Personal Indoor and Mobile Radio Communications (PIMRC), 2010 IEEE 21st International Symposium on. pp. 1128–1132.

  5. Partov, B., Leith, D. J., & Razavi, R. (2015). Utility fair optimization of antenna tilt angles in LTE networks. IEEE/ACM Transactions on Networking, 23(1), 175–185.

    Article  Google Scholar 

  6. Thampi, A., Kaleshi, D., Randall, P., Featherstone, W., & Armour, S. (2012). A sparse sampling algorithm for self-optimisation of coverage in LTE networks. Wireless Communication Systems (ISWCS), 2012 International Symposium on, pp. 909–913.

  7. Razavi, R., Klein, S., & Claussen, H. (2010). Self-optimization of capacity and coverage in LTE networks using a fuzzy reinforcement learning approach. Personal Indoor and Mobile Radio Communications (PIMRC), 2010 IEEE 21st International Symposium on, pp. 1865, 1870.

  8. Goldsmith, A. (2005). Wireless communications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  9. Balanis, C. A. (2005). Antenna theory: Analysis and design, 3rd Edn. Wiley.

  10. GPP. (2014). TR 36.814, technical specification group radio access network (E-UTRA). Evolved Universal Terrestrial Radio Access (E-UTRA); Further advancements for E-UTRA physical layer aspects, ver. 1.7.0, Release 9. http://www.3gpp.org/ftp/Specs/archive/36_series/36.814/36814-170.zip. Accessed July 2015.

  11. Kathrein (2015). Antenna type 742215 technical specification. https://www.kathrein.de/svg/download/9364238a.pdf. Accessed August 2015.

  12. Gunnarsson, F., Johansson, M. N., Furuskar, A., Lundevall, M., Simonsson, A., Tidestav, C., & Blomgren, M. (2008). Downtilted base station antennas—a simulation model proposal and impact on HSPA and LTE performance. Vehicular Technology Conference, 2008. VTC 2008-Fall. IEEE 68th, pp. 1–5.

  13. Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2012). Foundations of machine learning. The MIT Press.

  14. Sutton, R., & Barto, A. (1998). Introduction to reinforcement learning, 1st edn. MIT Press.

Download references

Author information

Authors and Affiliations

  1. Faculty of Telecommunications, Technical University of Sofia, Sofia, Bulgaria

    Nikolay Dandanov & Vladimir Poulkov

  2. Institute for Telecommunications, Technical University Darmstadt, Darmstadt, Germany

    Hussein Al-Shatri & Anja Klein

Authors
  1. Nikolay Dandanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hussein Al-Shatri
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anja Klein
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vladimir Poulkov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vladimir Poulkov.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dandanov, N., Al-Shatri, H., Klein, A. et al. Dynamic Self-Optimization of the Antenna Tilt for Best Trade-off Between Coverage and Capacity in Mobile Networks. Wireless Pers Commun 92, 251–278 (2017). https://doi.org/10.1007/s11277-016-3849-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3849-9

Keywords

Search

Navigation