Matching game-based hierarchical spectrum sharing in cooperative cognitive radio networks

Abstract

In a cooperative cognitive radio network (CCRN), primary users (PUs) select secondary users (SUs) as cooperative relays for increasing their transmission rates, while SUs gain spectrum usage opportunities for transmitting their own traffic. In this paper, we particularly focus on the problems of cooperative relays selection as well as resource allocation between multiple PUs and multiple SUs in a CCRN. We first propose a distributed algorithm to form the matched pairings between PUs and SUs, such that the PUs and SUs can achieve their utilities in terms of capacity and power consumption. In addition, we propose a matching game-based power control approach to achieve the stable matching between PUs and SUs. Then, the matched pairings are shown to be stable with the existence of two stability conditions, the one-sided exchange stability (1ES) and the two-sided exchange stability (2ES), respectively. Finally, simulation results show the benefits of our proposed matching game-based approach comparing with other ones.

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

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

References

  1. 1.

    Han Z, Gu Y, Saad W (2017) Matching theory for wireless networks. Springer, New York

    Google Scholar 

  2. 2.

    Chen M, Challita U, Saad W, Yin C, Debbah M (2017) Machine learning for wireless networks with artificial intelligence: A tutorial on neural networks. arXiv preprint arXiv:1710.02913

  3. 3.

    Gu Y, Saad W, Bennis M, Debbah M, Han Z (2015) Matching theory for future wireless networks: fundamentals and applications. IEEE Commun Mag 53(5):52–59

    Article  Google Scholar 

  4. 4.

    Namvar N, Afghah F (2015) Spectrum sharing in cooperative cognitive radio networks: a matching game framework. In: Proceedings of IEEE 49th Annual Conference on Information Sciences and Systems (CISS), March, 2015

  5. 5.

    Xu H, Li B (2011) Seen as stable marriages. In: Proceedings of IEEE INFOCOM’11, April, 2011

  6. 6.

    Wang X, Li Z, Xu P, Xu Y, Gao X, Chen HH (2010) Spectrum sharing in cognitive radio networks—an auction-based approach. IEEE Trans Syst Man Cybern Part B (Cybern) 40(3):587–596

    Article  Google Scholar 

  7. 7.

    Akyildiz IF, Lee WY, Vuran MC, Mohanty S (2006) NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput Netw 50(13):2127–2159

    Article  Google Scholar 

  8. 8.

    Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Sel Areas Commun 23(2):201–220

    Article  Google Scholar 

  9. 9.

    Simeone O, Stanojev I, Savazzi S, Bar-Ness Y, Spagnolini U, Pickholtz R (2008) Spectrum leasing to cooperating secondary ad hoc networks. IEEE J Sel Areas Commun 26(1):203–213

    Article  Google Scholar 

  10. 10.

    Zhang J, Zhang Q (2009) Stackelberg game for utility-based cooperative cognitive radio networks. In: Proceedings of the Tenth ACM International Symposium on Mobile Ad hoc Networking and Computing (MobiHoc ’08), May, 2009

  11. 11.

    Chan YW, Chien FT, Chang RY, Chang MK, Chung YC (2013) Spectrum sharing in multi-channel cooperative cognitive radio networks: a coalitional game approach. Wirel Netw 19(7):1553–1562

    Article  Google Scholar 

  12. 12.

    Bayat S, Louie RH, Li Y, Vucetic B (2011) Cognitive radio relay networks with multiple primary and secondary users: distributed stable matching algorithms for spectrum access. In: Proceedings of the 2011 IEEE International Conference on Communications (ICC ’11), June, 2011

  13. 13.

    Jorswieck EA (2011) Stable matchings for resource allocation in wireless networks. In: Proceedings of the 17th International Conference on Digital Signal Processing (DSP’11), July, 2011

  14. 14.

    Yaffe Y, Leshem A, Zehavi E (2010) Stable matching for channel access control in cognitive radio systems. In: Proceedings of the 2nd International Workshop on Cognitive Information Processing (CIP’10), June, 2010

  15. 15.

    Bodine-Baron E, Lee C, Chong A, Hassibi B, Wierman A (2011) Peer effects and stability in matching markets. In: Proceedings of the International Symposium on algorithmic game theory, October, 2011

  16. 16.

    Leshem A, Zehavi E, Yaffe Y (2012) Multichannel opportunistic carrier sensing for stable channel access control in cognitive radio systems. IEEE J Sel Areas Commun 30(1):82–95

    Article  Google Scholar 

  17. 17.

    Yang C-T, Liu J-C, Huang K-L, Jiang F-C (2014) A method for managing green power of a virtual machine cluster in cloud. Future Gener Comput Syst 37:26–36

    Article  Google Scholar 

  18. 18.

    Liang W, Ng SX, Hanzo L (2017) Cooperative overlay spectrum access in cognitive radio networks. IEEE Commun Surv Tutor 19(3):1924–1944

    Article  Google Scholar 

  19. 19.

    Karmokar A, Naeem M, Anpalagan A (2018) Green metric optimization in cooperative cognitive radio networks with statistical interference parameters. IEEE Syst J 12(1):1034–1037

    Article  Google Scholar 

  20. 20.

    Huo Y, Liu L, Ma L, Zhou W, Cheng X, Jing T, Jiang X (2017) A coalition formation game based relay selection scheme for cooperative cognitive radio networks. Wirel Netw 23(8):2533–2544

    Article  Google Scholar 

  21. 21.

    Wang L, Wu H, Han Z, Zhang P, Poor HV (2018) Multi-hop cooperative caching in social IoT using matching theory. IEEE Trans Wirel Commun 17(4):2127–2145

    Article  Google Scholar 

  22. 22.

    Liu T, Li J, Shu F, Guan H, Yan S, Jayakody DNK (2018) On the incentive mechanisms for commercial edge caching in 5G Wireless networks. IEEE Wirel Commun 25(3):72–78

    Article  Google Scholar 

  23. 23.

    Pham QV, Leanh T, Tran NH, Park BJ, Hong CS (2018) Decentralized computation offloading and resource allocation for mobile-edge computing: a matching game approach. IEEE Access 6:75868–75885

    Article  Google Scholar 

  24. 24.

    Jiang F, Lin C, Huang D, Yang C (2012) Dual paths node-disjoint routing for data salvation in mobile ad hoc. J Supercomput 59(1):268–296

    Article  Google Scholar 

  25. 25.

    Abdar M, Yen NY (2017) Sharing economy and its effect on human behaviour changes in accommodation: a survey on AirBnb. Int J Soc Humanist Comput 2(34):203218

    Google Scholar 

  26. 26.

    Iwama K, Miyazaki S (2008) A survey of the stable marriage problem and its variants. In: Proceedings of the International Conference on Informatics Education and Research for Knowledge-Circulating Society (ICKS 2008), January, 2008

  27. 27.

    Gale D, Shapley LS (1962) College admissions and the stability of marriage. Am Math Mon 69(1):9–15

    MathSciNet  Article  Google Scholar 

  28. 28.

    Yang C-T, Chen C-H, Yang M-F (2010) Implementation of a medical image file accessing system in co-allocation data grids. Future Gener Comput Syst 26(8):1127–1140

    Article  Google Scholar 

  29. 29.

    Roth AE (1984) The evolution of the labor market for medical interns and residents: a case study in game theory. J Polit Econ 92(6):991–1016

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Yu-Wei Chan.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chang, M., Mei, Y., Chan, Y. et al. Matching game-based hierarchical spectrum sharing in cooperative cognitive radio networks. J Supercomput 76, 6195–6218 (2020). https://doi.org/10.1007/s11227-019-02757-1

Download citation

Keywords

  • Matching theory
  • Stable matching
  • Cooperative cognitive radio networks
  • Peer effects