Skip to main content
SpringerLink
Log in

A QoS Aware Learning Automata Based Channel Assignment Method in Cognitive Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

With the rapid growth of wireless services and technologies, and as a result, increasing demand for the spectrum, cognitive network (CN) has been proposed as a promising solution for accomplishing the problem of spectrum scarcity. Channel assignment (CA) problem in CN is NP-complete and hence, in terms of scalability it should be solved through heuristic or meta-heuristic approaches. The main goal of dynamic CA in CN environment is to improve the QoS provisioning for SUs as well as protecting the Primary Users (PUs) from interference. To achieve this goal, a Secondary User may have to change its transmission channel several times during the established communication. Channel switching is a costly task due to the time overhead and interruptions that imposes on the given communication. To overcome these problems, two learning based dynamic CA methods are introduced; In the first method, by proposing a channel allocation scheme based on learning automata a trade-off between different QoS parameters will be made. In the second method, it is trying to decrease the overhead and interruptions because of switching channels of the first algorithm. Simulation results demonstrate the superiority of the proposed method in terms of delay, data delivery ratio, throughput, and data loss rate in comparison with other representative methods.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

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
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  1. Marcus, M., Burtle, J., Franca, B., Lahjouji, A., & McNeil, N. (2002). Federal communications commission spectrum policy task force. Report of the unlicensed devices and experimental licenses working group.

  2. Mitola, J., & Maguire, G. Q., Jr. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6, 13–18.

    Article  Google Scholar 

  3. Thomas, R. (2007). Cognitive networks. Ph.D. Dissertation, Computer Engineering, Virginia Polytechnic Institute and State University.

  4. Karp, R. M. (1972). Reducibility among combinatorial problems (pp. 85–103). New York: Springer.

    Google Scholar 

  5. Ren, P., Wang, Y., Du, Q., & Xu, J. (2012). A survey on dynamic spectrum access protocols for distributed cognitive wireless networks. EURASIP Journal on Wireless Communications and Networking, 2012, 60.

    Article  Google Scholar 

  6. Plummer, A., & Biswas, S. (2011). Distributed spectrum assignment for cognitive networks with heterogeneous spectrum opportunities. Wireless Communications and Mobile Computing, 11, 1239–1253.

    Article  Google Scholar 

  7. Hoang, A. T., & Liang, Y.-C. (2008). Downlink channel assignment and power control for cognitive radio networks. IEEE Transactions on Wireless Communications, 7, 3106–3117.

    Article  Google Scholar 

  8. Su, X., Yuan, C., & Shen, S. (2009). A new mechanism of dynamic spectrum allocation in the cognitive network. In 5th international conference on wireless communications, networking and mobile computing (WiCom’09) (pp. 1–4).

  9. Zhang, T., Wang, B., & Wu, Z. (2009). Spectrum assignment in infrastructure based cognitive radio networks. In Proceedings of the IEEE national aerospace and electronics conference (NAECON) (pp. 69–74).

  10. Yang, L., Xie, X., & Zheng, Y. (2009). A historical-information-based algorithm in dynamic spectrum allocation. In International conference on communication software and networks (ICCSN’09) (pp. 731–736).

  11. Bkassiny, M., & Jayaweera, S. K. (2010). Optimal channel and power allocation for secondary users in cooperative cognitive radio networks. In P. Chatzimisios, C. Verikoukis, I. Santamaría, M. Laddomada, O. Hoffmann (Eds.) Mobile lightweight wireless systems, vol 45, (pp. 180–191). Berlin, Heidelberg: Springer.

    Chapter  Google Scholar 

  12. Hoang, A. T., Liang, Y.-C., & Islam, M. H. (2007). Maximizing throughput of cognitive radio networks with limited primary users’ cooperation. In ICC’07. IEEE international conference on communications, 2007 (pp. 5177–5182).

  13. Chen, S., Huang, Y., & Namuduri, K. (2011). A factor graph based dynamic spectrum allocation approach for cognitive network. In Wireless communications and networking conference (WCNC), 2011 IEEE (pp. 850–855).

  14. Xu, Y., Lui, J. C., & Chiu, D.-M. (2010). On oligopoly spectrum allocation game in cognitive radio networks with capacity constraints. Computer Networks, 54, 925–943.

    Article  MATH  Google Scholar 

  15. Chen, L., Iellamo, S., Coupechoux, M., Godlewski, P. (2010). An auction framework for spectrum allocation with interference constraint in cognitive radio networks. In INFOCOM, 2010 proceedings IEEE (pp. 1–9).

  16. Teng, Y., Yu, F. R., Han, K., Wei, Y., & Zhang, Y. (2013). Reinforcement-learning-based double auction design for dynamic spectrum access in cognitive radio networks. Wireless Personal Communications, 69, 771–791.

    Article  Google Scholar 

  17. Saad, W., Han, Z., Zheng, R., Hjørungnes, A., Başar, T., & Poor, H. V. (2012). Coalitional games in partition form for joint spectrum sensing and access in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing, 6, 195–209.

    Article  Google Scholar 

  18. Salameh, B., & Ahmad, H. (2011). Throughput-oriented channel assignment for opportunistic spectrum access networks. Mathematical and Computer Modelling, 53, 2108–2118.

    Article  Google Scholar 

  19. Salameh, H. B. (2010). Rate-maximization channel assignment scheme for cognitive radio networks. In Global telecommunications conference (GLOBECOM 2010), 2010 IEEE (pp. 1–5).

  20. Tragos, E. Z., Zeadally, S., Fragkiadakis, A. G., & Siris, V. A. (2013). Spectrum assignment in cognitive radio networks: A comprehensive survey. IEEE Communications Surveys and Tutorials, 15, 1108–1135.

    Article  Google Scholar 

  21. Lee, D. H., Jeon, W. S., & Jeong, D. G. (2010). Joint channel assignment and routing in cognitive radio-based wireless mesh networks. In 2010 IEEE 71st vehicular technology conference (VTC) (pp 1–5).

  22. Wang, W., Kasiri, B., Cai, J., & Alfa, A. S. (2011). Channel assignment of cooperative spectrum sensing in multi-channel cognitive radio networks. In 2011 IEEE international conference on communications (ICC) (pp. 1–5).

  23. Salameh, H. B., Krunz, M., & Younis, O. (2008). Distance-and traffic-aware channel assignment in cognitive radio networks. In 5th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks, 2008. SECON’08 (pp. 10–18).

  24. Kaur, P., Uddin, M., & Khosla, A. (2010). Adaptive bandwidth allocation scheme for cognitive radios. International Journal of Advancements in Computing Technology, 2, 35–41.

    Article  Google Scholar 

  25. Wenzhu, Z., & Xuchen, L. (2011). Centralized dynamic spectrum allocation in cognitive radio networks based on fuzzy logic and Q-learning. China Communications, 8, 46–54.

    Google Scholar 

  26. Ye, F., Yang, R., & Li, Y. (2011). Genetic spectrum assignment model with constraints in cognitive radio networks. International Journal of Computer Network and Information Security (IJCNIS), 3, 39–45.

    Article  Google Scholar 

  27. Zhao, Z., Peng, Z., Zheng, S., & Shang, J. (2009). Cognitive radio spectrum allocation using evolutionary algorithms. IEEE Transactions on Wireless Communications, 8, 4421–4425.

    Article  Google Scholar 

  28. Ye, F., Yang, R., & Li, Y. (2010). Genetic algorithm based spectrum assignment model in cognitive radio networks. In 2nd international conference on information engineering and computer science (ICIECS) (pp. 1–4).

  29. Del Ser, J., Matinmikko, M., Gil-López, S., & Mustonen, M. (2012). Centralized and distributed spectrum channel assignment in cognitive wireless networks: A harmony search approach. Applied Soft Computing, 12, 921–930.

    Article  Google Scholar 

  30. Cheng, X., & Jiang, M. (2011). Cognitive radio spectrum assignment based on artificial bee colony algorithm. In 13th IEEE international conference on communication technology (ICCT) (pp. 161–164).

  31. Ghasemi, A., Masnadi-shirazi, M., Biguesh, M., Jahromi, A. F., & Ghasemi, F. (2012). Spectrum allocation based on artificial bee colony in cognitive radio networks. In 2012 sixth international symposium on telecommunications (IST) (pp. 182–187).

  32. Jiang, T., Grace, D., & Mitchell, P. D. (2011). Efficient exploration in reinforcement learning-based cognitive radio spectrum sharing. IET Communications, 5, 1309–1317.

    Article  Google Scholar 

  33. Faganello, L. R., Kunst, R., Both, C. B., Granville, L. Z., & Rochol, J. (2013). Improving reinforcement learning algorithms for dynamic spectrum allocation in cognitive sensor networks. In IEEE wireless communications and networking conference (WCNC) (pp. 35–40).

  34. Vucevic, N., Akyildiz, I. F., & Pérez-Romero, J. (2010). Cooperation reliability based on reinforcement learning for cognitive radio networks. In Fifth IEEE workshop on networking technologies for software defined radio (SDR) networks (pp. 1–6).

  35. Jiang, T., Grace, D., & Liu, Y. (2011). Two-stage reinforcement-learning-based cognitive radio with exploration control. IET Communications, 5, 644–651.

    Article  Google Scholar 

  36. Song, Y., Fang, Y., & Zhang, Y. (2007). Stochastic channel selection in cognitive radio networks. In IEEE global telecommunications conference (GLOBECOM’07) (pp. 4878–4882).

  37. Li, H., Zhu, G., Jian, L., Liang, Z., & Wang, D. (2009). Stochastic spectrum access based on learning automata in cognitive radio network. In IEEE international conference on intelligent computing and intelligent systems (ICIS) (pp. 294–298).

  38. Tuan, T. A., Tong, L. C., & Premkumar, A. (2010). An adaptive learning automata algorithm for channel selection in cognitive radio network. In International conference on communications and mobile computing (CMC) (pp. 159–163).

  39. Liu, L., Hu, G., Xu, M., & Peng, Y. (2010). Learning automata based spectrum allocation in cognitive networks. In IEEE international conference on wireless communications, networking and information security (WCNIS) (pp. 503–508).

  40. Bizhani, H., & Ghasemi, A. (2013). Joint admission control and channel selection based on multi response learning automata (MRLA) in cognitive radio networks. Wireless Personal Communications, 71, 629–649.

    Article  Google Scholar 

  41. Narendra, K. S., & Thathachar, M. A. (2012). Learning automata: An introduction. North Chelmsford: Courier Corporation.

    MATH  Google Scholar 

  42. Torkestani, J. A., & Meybodi, M. R. (2011). A learning automata-based cognitive radio for clustered wireless ad-hoc networks. Journal of Network and Systems Management, 19, 278–297.

    Article  Google Scholar 

  43. Narendra, K. S., & Thathachar, M. (1974). Learning automata–A survey. IEEE Transactions on Systems, Man and Cybernetics, 4, 323–334.

    Article  MATH  MathSciNet  Google Scholar 

  44. Maulik, S., Roy, R., De, A., & Bhatttacharya, A. (2012). Online dynamic resource allocation in interference temperature constrained cognitive radio network using reinforcement learning. In International conference on signal processing and communications (SPCOM) (pp. 1–5).

  45. Zhang, W., & Yeo, C. K. (2014). Sequential sensing based spectrum handoff in cognitive radio networks with multiple users. Computer Networks, 58, 87–98.

    Article  Google Scholar 

  46. http://www.omnetpp.org.

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran

    Setareh Rasaneh

  2. Young Researchers and Elite club, Central Tehran Branch, Islamic Azad University, Tehran, Iran

    Mohsen Jahanshahi

Authors
  1. Setareh Rasaneh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohsen Jahanshahi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohsen Jahanshahi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rasaneh, S., Jahanshahi, M. A QoS Aware Learning Automata Based Channel Assignment Method in Cognitive Network. Wireless Pers Commun 97, 495–519 (2017). https://doi.org/10.1007/s11277-017-4516-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4516-5

Keywords

Search

Navigation