Your browser does not support JavaScript!

Transmit power optimisation in cellular networks with nomadic base stations

Transmit power optimisation in cellular networks with nomadic base stations

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The increasing demand for cellular network capacity can be mitigated through the installation of nomadic eNodeB, which serve a temporal increase of traffic volume in specific area. When nomadic cells are deployed, the transmission power of neighbour base stations needs to be optimised to limit the inter-cell interferences. The authors analyse the problem of neighbourhood selection for the optimisation, to define what part of the networks needs to be reconfigured when new base station is added. They evaluate the iterative approach, with increasing range of neighbouring cells being reconfigured and propose a novel, sampling-based local TX power reconfiguration method, which is evaluated by a numerical model in both regular (honeycomb) topology and in realistic topology reflecting locations of cells in a city. The analysis confirms that the proposed algorithm allows to select small subset of neighbouring cells to be reconfigured (in majority of the cases cells), and achieve similar efficacy as global optimisation, with total network throughput different by comparing to the global optimisation.


    1. 1)
      • 4. Słabicki, M., Grochla, K.: ‘Local approach to power management in LTE networks’. 2015 38th Int. Conf. on Telecommunications and Signal Processing (TSP), Prague, Czechia, 2015, pp. 139143.
    2. 2)
      • 11. Xu, S., Hou, M., Niu, K., et al: ‘Coverage and capacity optimization in LTE network based on non-cooperative games’, J. China Univ. Posts Telecommun., 2012, 19, (4), pp. 1442.
    3. 3)
      • 28. Izzo, D.: ‘PyGMO and pyKEP: open source tools for massively parallel optimization in astrodynamics (the case of interplanetary trajectory optimization)’. Proc. Fifth Int. Conf. Astrodynamics Tools and Techniques (ICATT), Noordwijk, Netherlands, 2012.
    4. 4)
      • 21. Ge, X., Jin, H., Leung, V.C.M.: ‘Joint opportunistic user scheduling and power allocation: throughput optimisation and fair resource sharing’, IET Commun., 2017, 12, (5), pp. 634640.
    5. 5)
      • 2. Liu, L., Zhou, Y., Vasilakos, A.V., et al: ‘Time-domain ICIC and optimized designs for 5G and beyond: a survey’, Sci. China Inf. Sci., 2019, 62, (2), p. 21302.
    6. 6)
      • 10. Fan, S., Tian, H., Sengul, C.: ‘Self-optimization of coverage and capacity based on a fuzzy neural network with cooperative reinforcement learning’, EURASIP J. Wirel. Commun. Netw., 2014, 2014, (1), p. 57.
    7. 7)
      • 22. Wang, Z., Shen, C.: ‘Small cell power assignment with unimodal continuum-armed bandit learning’. 2018 IEEE Int. Conf. on Communications Workshops (ICC Workshops), Kansas City, MO, USA, May 2018, pp. 16.
    8. 8)
      • 9. Lopez-Perez, D., Ladanyi, A., Jüttner, A., et al: ‘Optimization method for the joint allocation of modulation schemes, coding rates, resource blocks and power in self-organizing LTE networks’. INFOCOM 2011, 2011.
    9. 9)
      • 20. Sanneck, H., Bouwen, Y., Troch, E.: ‘Context based configuration management of plug & play LTE base stations’. IEEE Network Operations and Management Symp. (NOMS), Osaka, Japan, 2010.
    10. 10)
      • 7. Balasubramanya, N.M., Lampe, L.: ‘Simulated annealing based joint coverage and capacity optimization in LTE’. IEEE Conf. on Electrical and Computer Engineering (CCECE), Vancouver, Canada, 2016, pp. 15.
    11. 11)
      • 25. Erceg, V., Greenstein, L.J., Tjandra, S.Y., et al: ‘An empirically based path loss model for wireless channels in suburban environments’, IEEE J. Sel. Areas Commun., 1999, 17, (7), pp. 12051211.
    12. 12)
      • 19. Eisenblatter, A., Turke, U, Schmelz, C.: ‘Self-configuration in LTE radio networks: automatic generation of eNodeB parameters’. 73rd Vehicular Technology Conf. (VTC Spring), Budapest, Hungary, 2011.
    13. 13)
      • 17. ‘Study on isolated E-UTRAN operation for public safety; Security aspects: TS 33.897’. 3rd Generation Partnership Project (3GPP), 2015.
    14. 14)
      • 16. Bulakci, Ö., Ren, Z., Zhou, C., et al: ‘Towards flexible network deployment in 5G: nomadic node enhancement to heterogeneous networks’. IEEE Communication Workshop (ICCW 2015), London, UK, 2015, pp. 25722577.
    15. 15)
      • 6. Aliu, O.G., Imran, A., Imran, M.A., et al: ‘A survey of self organisation in future cellular networks’, IEEE Commun. Surv. Tutor., 2013, 15, (1), pp. 336361.
    16. 16)
      • 5. Yilmaz, O.N.C., Hamalainen, S., Hamalainen, J.: ‘Analysis of antenna parameter optimization space for 3GPP LTE’. 70th Vehicular Technology Conf. Fall (VTC 2009-Fall), Anchorage, Alaska, USA, 2009, pp. 15.
    17. 17)
      • 1. Recommendation M ITU-R: 2083-0: ‘IMT Vision-Framework and overall objectives of the future development of IMT for’, 2020.
    18. 18)
      • 8. Temesváry, A.: ‘Self-configuration of antenna tilt and power for plug & play deployed cellular networks’. Wireless Communications and Networking Conf., 2009 (WCNC 2009), Budapest, Hungary, April 2009.
    19. 19)
      • 23. Wang, Z., Shen, C.: ‘Small cell transmit power assignment based on correlated bandit learning’, IEEE J. Sel. Areas Commun., 2017, 35, (5), pp. 10301045.
    20. 20)
      • 12. Aghababaiyan, K., Maham, B.: ‘QoS-aware downlink radio resource management in OFDMA-based small cells networks’, IET Commun., 2017, 12, (4), pp. 441448.
    21. 21)
      • 29. Rose, D.M., Jansen, T., Werthmann, T., et al: ‘The IC 1004 Urban Hannover Scenario–3D Pathloss Predictions and Realistic Traffic and Mobility Patterns’. European Cooperation in the Field of Scientific and Technical Research, COST IC1004 TD (13)8054, 2013.
    22. 22)
      • 24. Ali-Yahiya, T.: ‘Understanding LTE and its performance’ (Springer-Verlag, New York, 2011).
    23. 23)
      • 15. Raheem, R., Lasebae, A., Aiash, M., et al: ‘From fixed to mobile femtocells in LTE systems: issues and challenges’. 2013 2nd Int. Conf. on Future Generation Communication Technology, London, UK, 2013.
    24. 24)
      • 3. ‘Self-configuring and self-optimizing network (SON) use cases and solutions’. TS 36.902, 3rd Generation Partnership Project (3GPP), 2011.
    25. 25)
      • 27. Słabicki, M., Grochla, K.: ‘The automatic configuration of transmit power in LTE networks based on throughput estimation’. Int. Performance Computing and Communications Conf. 2014, Beijing, China, December 2014.
    26. 26)
      • 13. Buenestado, V., Toril, M., Luna-Ramírez, S., et al: ‘Self-planning of base station transmit power for coverage and capacity optimization in LTE’, Mob. Inf. Syst., 2017, 2017, pp. 112.
    27. 27)
      • 18. Bulakci, O., Kaloxylos, A., Eichinger, J., et al: ‘Ran moderation in 5G dynamic radio topology’. 85th IEEE Vehicular Technology Conf. (VTC Spring), Sydney, Australia, 2017, pp. 14.
    28. 28)
      • 14. Chang, Z., Zhang, S., Wang, Z., et al: ‘Energy efficient optimisation for large-scale multiple-antenna system with WPT’, IET Commun., 2017, 12, (5), pp. 552558.
    29. 29)
      • 26. Giambene, G., Yahiya, T.A., Grochla, K., et al: ‘Resource management and cell planning in LTE systems’, in Ganchev, I., Curado, M., Kassler, A. (Eds.): Wireless networking for moving objects (Springer International Publishing, New York, 2014), pp. 177197.

Related content

This is a required field
Please enter a valid email address