Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Energy and cost implications of a traffic aware and quality-of-service constrained sleep mode mechanism

  • Author(s): Siyi Wang 1  and  Weisi Guo 2
    • View affiliations
    • Affiliations: 1: Institute for Telecommunications Research, University of South Australia, Adelaide, Australia;
      2: School of Engineering, University of Warwick, Coventry, Warwickshire, UK
  • Source: Volume 7, Issue 18, 17 December 2013, p. 2092 – 2101
    DOI:  10.1049/iet-com.2013.0011 , Print ISSN 1751-8628, Online ISSN 1751-8636
© The Institution of Engineering and Technology
Received 16/01/2013, Accepted 03/08/2013, Revised 27/06/2013, Published

This study considers the theoretical and realistic performance of a traffic aware sleep mode mechanism in the cellular network. The study devises a sleep mode mechanism that maximises the energy saving of the network, while maintaining both the user throughput and reliability performance. The analysis combines recent developments in stochastic geometry and packet data modelling, as well as a simulation of a real cellular network. The main contribution is to show that accurate theoretical modelling of realistic network data can allow deterministic sleep mode triggers to be devised. This is shown to be highly applicable to a real network, reducing energy consumption by 15–60% throughout a day and the annual operational expenditure by 4%.

Inspec keywords: geometry; telecommunication traffic; quality of service; telecommunication power management; cellular radio

Other keywords: cost implications; packet data modelling; cellular network; quality-of-service constrained sleep mode mechanism; reliability performance; stochastic geometry; traffic aware sleep mode mechanism; energy consumption; user throughput; annual operational expenditure

Subjects: Mobile radio systems; Combinatorial mathematics

References

    1. 1)
      • 14. Laner, M., Svoboda, P., Schwarz, S., Rupp, M.: ‘Users in cells: a data traffic analysis’. IEEE Wireless Communications and Networking Conf. (WCNC), April 2012, pp. 3063–3068.
    2. 2)
      • 10. Guo, W., O'Farrell, T.: ‘Dynamic cell expansion with self-organizing cooperation’, IEEE J. Sel. Areas Commun. (JSAC), 2013, 31, (5), pp. 851–860 (doi: 10.1109/JSAC.2013.130504).
    3. 3)
      • 12. 3GPP: ‘Further advancements for E-UTRA physical layer aspects (Rel.9),’ 3GPP TR36.814v9, Technical report, March2010.
    4. 4)
      • 4. Tombaz, S., Monti, P., Wang, K., Vastberg, A., Forzati, M., Zander, J.: ‘Impact of backhauling power consumption on the deployment of heterogeneous mobile networks’. IEEE Global Telecommunications Conf. (Globecom), December 2011, pp. 1–5.
    5. 5)
      • 5. Wang, R., Thompson, J.S., Haas, H., Grant, P.M.: ‘Sleep mode design for green base stations’, IET Commun., 2011, 5, (18), pp. 2606–2616 (doi: 10.1049/iet-com.2011.0104).
    6. 6)
      • 2. Saker, L., Elayoubi, S., Combes, R., Chahed, T.: ‘Optimal control of wake Up mechanisms of femtocells in heterogeneous networks’, IEEE J. Sel. Areas Commun. (JSAC), 2012, 30, (3), pp. 664–672 (doi: 10.1109/JSAC.2012.120415).
    7. 7)
      • 15. Auer, G., Giannini, V., Godor, I., et al: ‘Cellular energy efficiency evaluation framework’. IEEE Vehicular Technology Conf. (VTC Spring), May 2011, pp. 1–6.
    8. 8)
      • 7. Niu, Z., Wu, Y., Gong, J., Yang, Z.: ‘Cell zooming for cost-efficient green cellular networks’, Commun. Mag., IEEE, 2010, 48, (11), pp. 74–79 (doi: 10.1109/MCOM.2010.5621970).
    9. 9)
      • 6. Conte, A., Feki, A., Chiaraviglio, L., Ciullo, D., Meo, M., Marsan, M.: ‘Cell wilting and blossoming for energy efficiency’. IEEE Wireless Communications, 2011, 18, (5), pp. 50–57.
    10. 10)
      • 17. Oh, E., Krishnamachari, B.: ‘Energy savings through dynamic base station switching in cellular wireless access networks’. IEEE Global Telecommunications Conf. (GLOBECOM), December 2010, pp. 1–5.
    11. 11)
      • 9. Wang, S., Guo, W., O'Farrell, T.: ‘Two tier networks with frequency selective surface’. IEEE Int. Conf. High Performance Computing and Communications (HPCC), June 2012.
    12. 12)
      • 8. Haenggi, M., Andrews, J.G., Baccelli, F., Dousse, O., Franceschetti, M.: ‘Stochastic geometry and random graphs for the analysis and design of wireless networks’, IEEE J. Sel. Areas Commun. (JSAC), 2009, 27, (7), pp. 1029–1046 (doi: 10.1109/JSAC.2009.090902).
    13. 13)
      • 13. Guo, W., Wang, S., Chu, X., Chen, Y., Song, H., Zhang, J.: ‘Automated small-cell deployment for heterogeneous cellular networks’, IEEE Commun. Mag., 2013, 51, (5), pp. 46–53 (doi: 10.1109/MCOM.2013.6515046).
    14. 14)
      • 1. Xiong, C., Li, Y., Zhang, S., Chen, Y., Xu, S.: ‘Energy- and spectral- efficiency tradeoff in downlink OFDMA networks’, IEEE Trans. Wirel. Commun., 2011, 10, (11), pp. 3874–3885 (doi: 10.1109/TWC.2011.091411.110249).
    15. 15)
      • 3. Guo, W., O'Farrell, T.: ‘Capacity-energy-cost tradeoff for small-cell networks’. IEEE Vehicular Technology Conf., May 2012, pp. 1–5.
    16. 16)
      • 16. Furuskar, A., Almgren, M., Johansson, K.: ‘An infrastructure cost evaluation of single- and multi-access networks with heterogeneous traffic density’. IEEE Vehicular Technology Conf., May 2005, pp. 3166–3170.
    17. 17)
      • 11. Haenggi, M.: ‘Stochastic geometry for wireless networks’ (England, UK, Cambridge University Press, 2012).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2013.0011
Loading

Related content

content/journals/10.1049/iet-com.2013.0011
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address