Skip to main content
SpringerLink
Log in

Green Resource Allocation in Intelligent Software Defined NOMA Networks

  • Conference paper
  • First Online:
Machine Learning and Intelligent Communications (MLICOM 2017)

  • 1444 Accesses

Abstract

Non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) is a promising technique for fifth generation wireless communications. In NOMA, multiple users can access the same frequency-time resource simultaneously and multi-user signals can be separated successfully with SIC. In this paper, with recent advances in software-defined networking (SDN), an architecture of SDN-NOMA network was proposed and the SDN controller has a global view of the network. We aim to investigate the resource allocation algorithms for the virtual resource blocks (VRB) assignment and power allocation for the downlink SDN-NOMA network. Different from the existing works, here, energy efficient dynamic power allocation in SDN-NOMA networks is investigated with the constraints of QoS requirement and power consumption. The simulation results confirm that the proposed scheme of SDN-NOMA system yields much better sum rate and energy efficiency performance than the conventional orthogonal frequency division multiple access scheme.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ng, D.W.K., Lo, E.S., Schober, R.: Energy-efficient resource allocation in multi-cell OFDMA systems with limited backhaul capacity. IEEE Trans. Wirel. Commun. 11(10), 3618–3631 (2012)

    Article  Google Scholar 

  2. Ding, Z., Adachi, F., Poor, H.V.: The application of MIMO to non-orthogonal multiple access. IEEE Trans. Wirel. Commun. 15(11), 537–552 (2016)

    Article  Google Scholar 

  3. Wei, Z., Yuan, J., Ng, D.W.K., Elkashlan, M., Ding, Z.: A survey of downlink non-orthogonal multiple access for 5G wireless communication networks. ZTE Commun. 14, 17–26 (2016)

    Google Scholar 

  4. Jindal, N., Vishwanath, S., Goldsmith, A.: On the duality of Gaussian multiple-access and broadcast channels. IEEE Trans. Inf. Theory 50(5), 768–783 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  5. Ding, Z., Peng, M., Poor, H.V.: Cooperative non-orthogonal multiple access in 5G systems. IEEE Commun. Lett. 19(8), 1462–1465 (2015)

    Article  Google Scholar 

  6. Higuchi, K., Benjebbour, A.: Non-orthogonal multiple access (NOMA) with successive interference cancellation for future radio access. IEICE Trans. Commun. 98(3), 403–414 (2015)

    Article  Google Scholar 

  7. Ding, Z., Yang, Z., Fan, P., Poor, H.: On the performance of non-orthogonal multiple access in 5G systems with randomly deployed users. IEEE Signal Process. Lett. 21(12), 1501–1505 (2014)

    Article  Google Scholar 

  8. Hanif, M.F., Ding, Z., Ratnarajah, T., Karagiannidis, G.K.: A minorization-maximization method for optimizing sum rate in the downlink of non-orthogonal multiple access systems. IEEE Trans. Signal Process. 64(1), 76–88 (2016)

    Article  MathSciNet  Google Scholar 

  9. Fang, F., Zhang, H., Cheng, J., Leung, V.C.M.: Energy-efficient resource allocation for downlink non-orthogonal multiple access network. IEEE Trans. Commun. 64(9), 3722–3732 (2016)

    Article  Google Scholar 

  10. Fang, F., Zhang, H., Cheng, J., Roy, S., Leung, V.C.M.: Energy-efficient resource scheduling for NOMA systems with imperfect channel state information. IEEE J. Sel. Areas Commun. (accepted 2017)

    Google Scholar 

  11. Chin, W.H., Fan, Z., Haines, R.: Emerging technologies and research challenges for 5G wireless networks. IEEE Wirel. Commun. 21(2), 106–112 (2014)

    Article  Google Scholar 

  12. Hu, F., Hao, Q., Bao, K.: A survey on software-defined network and openflow: from concept to implementation. IEEE Commun. Surv. Tutor. 16(4), 2181–2206 (2014)

    Article  Google Scholar 

  13. Wang, K., Li, H., Yu, F.R., Wei, W.: Virtual resource allocation in software-defined information-centric cellular networks with device-to-device communications and imperfect CSI. IEEE Trans. Veh. Technol. 65(12), 10011–10021 (2016)

    Article  Google Scholar 

  14. Zhang, H., Huang, S., Jiang, C., Long, K., Leung, V.C.M., Vincent Poor, H.: Energy efficient user association and power allocation in millimeter wave based ultra dense networks with energy harvesting base stations. IEEE J. Sel. Areas Commun. 35, 1936–1947 (accepted 2017)

    Google Scholar 

  15. Dinkelbach, W.: On nonlinear fractional programming. Manag. Sci. 13, 492–498 (1967). http://www.jstor.org/stable/2627691

    Article  MathSciNet  MATH  Google Scholar 

  16. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)

    Book  MATH  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (61471025, 61771044), the Young Elite Scientist Sponsorship Program by CAST (2016QNRC001), Research Foundation of Ministry of Education of China & China Mobile (MCM2018-1-8), Beijing Municipal Natural Science Foundation (L172025), and the Fundamental Research Funds for the Central Universities (FRF-GF-17-A6, etc.).

Author information

Authors and Affiliations

  1. Beijing University of Chemical Technology, Beijing, China

    Baobao Wang & Xuebin Li

  2. Beijing Engineering and Technology Research Center for Convergence Networks, University of Science and Technology Beijing, Beijing, China

    Baobao Wang, Haijun Zhang & Keping Long

  3. Harbin Institute of Technology, Weihai, China

    Gongliang Liu

Authors
  1. Baobao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Haijun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Keping Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gongliang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xuebin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Haijun Zhang .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Xuemai Gu

  2. Harbin Institute of Technology, Weihai, Heilongjiang, China

    Gongliang Liu

  3. Shandong University, Weihai, Heilongjiang, China

    Bo Li

Rights and permissions

Reprints and permissions

Copyright information

© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, B., Zhang, H., Long, K., Liu, G., Li, X. (2018). Green Resource Allocation in Intelligent Software Defined NOMA Networks. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73447-7_46

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73446-0

  • Online ISBN: 978-3-319-73447-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation