Encyclopedia of Wireless Networks

Living Edition
| Editors: Xuemin (Sherman) Shen, Xiaodong Lin, Kuan Zhang

Cognitive Radio-Based Non-orthogonal Multiple Access

  • Zhenyu Na
  • Mengshu Zhang
  • Yuyao Wang
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-32903-1_207-1

Synonyms

Definition

Cognitive Radio-based Non-orthogonal Multiple Access (CR-NOMA) is a derivation of NOMA. In CR-NOMA, a user with bad channel condition is viewed as the primary user (PU), while a user with good channel condition is regarded as the secondary user (SU), which is squeezed into the spectrum occupied by PU (Ding et al. 2016). CR-NOMA opportunistically serves one user on the condition that other users’ Quality of Service (QoS) is guaranteed.

Historical Background

The advent of CR-NOMA is driven by the advantages of NOMA and CR. Recently, NOMA has attracted increasing attention because of its high spectral utilization. At the transmitter side, multiple users’ signals can be transmitted simultaneously in time domain, frequency domain, or code domain by utilizing power domain multiplexing. At the receiver side, the multiplexed signals can be separated by using Successive Interference Cancellation (SIC). Thus, the resource block...

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

References

  1. Agiwal M, Roy A, Saxena N (2016) Next generation 5G wireless networks: a comprehensive survey. IEEE Commun Surv Tutorials 18(3):1617–1655CrossRefGoogle Scholar
  2. Boccardi F, Heath RW, Lozano A et al (2014) Five disruptive technology directions for 5G. IEEE Commun Mag 52(2):74–80CrossRefGoogle Scholar
  3. Ding Z, Fan P, Poor HV (2016) Impact of user pairing on 5G nonorthogonal multiple-access downlink transmissions. IEEE Trans Veh Technol 65(8):6010–6023CrossRefGoogle Scholar
  4. Ding Z, Lei X, Karagiannidis GK, Schober R, Yuan J and Bhargava VK (2017) A survey on non-orthogonal multiple access for 5G networks: research challenges and future trends. IEEE J Sel Areas Commun 35(10):2181–2195CrossRefGoogle Scholar
  5. Han S, Chih-Lin I, Xu Z et al. (2014) Energy efficiency and spectrum efficiency co-design: from NOMA to network NOMA. IEEE COMSOC MMTC E-Letter 9(5):21–24Google Scholar
  6. Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Sel Areas Commun 23(2):201–220CrossRefGoogle Scholar
  7. Higuchi K, Kishiyama Y (2013) Non-orthogonal access with random beamforming and intra-beam SIC for cellular MIMO downlink. In: Vehicular technology conference (VTC Fall), 2013 IEEE 78th. IEEE, pp 1–5Google Scholar
  8. Hu F, Chen B, Zhu K (2018) Full spectrum sharing in cognitive radio networks toward 5G: a survey. IEEE Access 6:15754–15776CrossRefGoogle Scholar
  9. Islam SMR, Avazov N, Dobre OA, Kwak K et al. (2016) Power-domain non-orthogonal multiple access (NOMA) in 5G systems: potentials and challenges. IEEE Commun Surv & Tutorials 19(2):721–742CrossRefGoogle Scholar
  10. Kolodzy P, Avoidance I (2002) Spectrum policy task force. Federal Commun Comm, Washington, DC, Rep. ET Docket, 40(4): 147–158Google Scholar
  11. Lv L, Yang L, Jiang H et al. (2015) When NOMA meets multiuser cognitive radio: opportunistic cooperation and user schedulingGoogle Scholar
  12. Lv L, Yang L, Jiang H, Luan T.H, Chen J et al. (2018) When NOMA meets multiuser cognitive radio: opportunistic cooperation and user scheduling. IEEE Trans Veh Technol 67(7):6679–6684CrossRefGoogle Scholar
  13. Mitola J, Maguire GQ (1999) Cognitive radio: making software radios more personal. IEEE Pers Commun 6(4):13–18CrossRefGoogle Scholar
  14. Rawat P, Singh KD, Bonnin JM (2016) Cognitive radio for M2M and internet of things: a survey. Comput Commun 94:1–29CrossRefGoogle Scholar
  15. Razavi R, Dianati M, Imran MA (2017) Non-orthogonal multiple access (NOMA) for future radio access. In: 5G mobile communications. Springer, Cham, pp 135–163CrossRefGoogle Scholar
  16. Tragos EZ, Zeadally S, Fragkiadakis AG et al (2013) Spectrum assignment in cognitive radio networks: a comprehensive survey. IEEE Commun Surv Tutorials 15(3):1108–1135CrossRefGoogle Scholar
  17. Wang B, Liu KJR (2011) Advances in cognitive radio networks: a survey. IEEE J Sel Top Sign Proces 5(1):5–23CrossRefGoogle Scholar
  18. Zabetian N, Baghani M, Mohammadi A (2017) Rate optimization in NOMA cognitive radio networks. In: International symposium on telecommunications. IEEE, pp 62–65Google Scholar
  19. Zheng G, Ma S, Wong KK et al (2010) Robust beamforming in cognitive radio. IEEE Trans Wirel Commun 9(2):570–576CrossRefGoogle Scholar
  20. Zhou Z, Guo D, Honig ML (2017) Licensed and unlicensed spectrum allocation in heterogeneous networks. IEEE Trans Commun 65(4):1815–1827CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of Information Science and TechnologyDalian Maritime UniversityDalianChina

Section editors and affiliations

  • Ning Zhang
    • 1
  1. 1.Texas A&M University at Corpus ChristiCorpus ChristiUSA