Skip to main content
SpringerLink
Log in

A Novel Content Aware Channel Allocation Scheme for Video Applications over CRN

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Cognitive radio (CR) has emerged as an effective solution to spectrum scarcity problem which efficiently utilizes the unused spectrum of licensed primary user (PU). Video applications, as a bandwidth intensive and delay-sensitive application, will surely get benefitted from CR technology due to its ability to provide additional bandwidth to end users. In this article we investigate the challenges of quality of experience (QoE) driven video applications over CR networks due to the random behavior of PUs, dynamic characteristic of the primary channels, packet error rate etc. Generally, all video applications could be categorized into three groups like slight motion, gentle walking and rapid motion (RM) and each group has its own quality of service (QoS) requirements. The aim of this paper is to minimize QoE degradation by estimating the quality of the available channels based on our proposed Channel Quality Index metric and then allocating the channels depending on the QoS requirements of a particular video application. Extensive analysis validates that there is a performance enhancement of different video applications, especially RM type (nearly 66%) which is considered as most critical among all.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Spectrum Policy Task Force Report. (2002). Federal Communications Commission ET Docket 02 (Vol. 155).

  2. Nguyen, V. T., Villain, F., & Guillou, Y. L. (2012). Cognitive radio RF: Overview and challenges. VLSI Design, 3, 1–13.

    Article  Google Scholar 

  3. Haykin, S. (2005). Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 23(2), 201–220.

    Article  Google Scholar 

  4. Amraoui, A., Benmammar, B., Krief, F., & Bendimerad, F. (2012). Intelligent wireless communication system using cognitive radio. International Journal of Distributed and Parallel Systems (IJDPS), 3(2), 91–104.

    Article  Google Scholar 

  5. Cisco. Visual Networking Index (VNI). http://www.cisco.com/. Accessed February 2014.

  6. Lindeberg, M., Kristiansen, S., Plagemann, T., & Goebel, V. (2011). Challenges and techniques for video streaming over mobile ad hoc networks. Multimedia Systems, 17(1), 51–82.

    Article  Google Scholar 

  7. Hassan, M., & Krunz, M. (2007). Video streaming over wireless packet networks: An occupancy-based rate adaptation perspective. IEEE Transactions on Circuits and Systems for Video Technology, 17(8), 1017–1027.

    Article  Google Scholar 

  8. Hassan, M., & Krunz, M. (2005). A playback-adaptive approach for video streaming over wireless networks. In Global telecommunications conference, GLOBECOM’05 (Vol. 6, pp. 3687–3691). IEEE.

  9. Kalman, M., Steinbach, E., & Girod, B. (2004). Adaptive media playout for low-delay video streaming over error-prone channels. IEEE Transactions on Circuits and Systems for Video Technology, 14, 841–851.

    Article  Google Scholar 

  10. Wang, Y., & Zhu, Q. F. (1998). Error control and concealment for video communication: A review. Proceedings of the IEEE, 86(9), 974–997.

    Article  Google Scholar 

  11. Lee, Y. C., Kim, J., Altunbasak, Y., & Mersereau, R. M. (2003). Layered coded vs. multiple description coded video over error-prone networks. Signal Processing: Image Communication, 18(5), 337–356.

    Google Scholar 

  12. Kushwaha, H., Xing, Y., Chandramouli, R., & Heffes, H. (2008). Reliable multimedia transmission over cognitive radio networks using fountain codes. Proceedings of the IEEE, 96(1), 155–165.

    Article  Google Scholar 

  13. Ali, S., & Yu, F. R. (2009, April). Cross-layer QoS provisioning for multimedia transmissions in cognitive radio networks. In Wireless communications and networking conference, 2009. WCNC 2009 (pp. 1–5). IEEE.

  14. Hu, D., & Mao, S. (2010). Streaming scalable videos over multi-hop cognitive radio networks. IEEE Transactions on Wireless Communications, 9(11), 3501–3511.

    Article  Google Scholar 

  15. Hu, D., & Mao, S. (2012). On cooperative relay networks with video applications. arXiv preprint: arXiv:1209.2086.

  16. Li, S., Luan, T. H., & Shen, X. (2010, December). Channel allocation for smooth video delivery over cognitive radio networks. In 2010 IEEE global telecommunications conference (GLOBECOM 2010) (pp. 1–5). IEEE.

  17. Xu, Y., Hu, D., & Mao, S. (2014). Relay-assisted multiuser video streaming in cognitive radio networks. IEEE Transactions on Circuits and Systems for Video Technology, 24(10), 1758–1770.

    Article  Google Scholar 

  18. Bhattacharya, A., Ghosh, R., Sinha, K., & Sinha, B. P. (2011, January). Multimedia communication in cognitive radio networks based on sample division multiplexing. In 2011 Third international conference on communication systems and networks (COMSNETS) (pp. 1–8). IEEE.

  19. Hassan, M. S., Abusara, A., El Din, M. S., & Ismail, M. H. (2016). On efficient channel modeling for video transmission over cognitive radio networks. Wireless Personal Communications. https://doi.org/10.1007/s11277-016-3504-5.

    Google Scholar 

  20. Khan, A., Sun, L., & Ifeachor, E. (2009, June). Content clustering based video quality prediction model for MPEG4 video streaming over wireless networks. In IEEE international conference on communications, 2009. ICC’09 (pp. 1–5). IEEE.

  21. Zeng, Y., Liang, Y. C., Hoang, A. T., & Zhang, R. (2010). A review on spectrum sensing for cognitive radio: Challenges and solutions. EURASIP Journal on Advances in Signal Processing, 2010(1), 1–15.

    Article  Google Scholar 

  22. Vujičić, B., Cackov, N., Vujičić, S., & Trajković, L. (2005). Modeling and characterization of traffic in public safety wireless networks. In Proceedings of SPECTS.

  23. Kim, H., & Shin, K. G. (2008). Efficient discovery of spectrum opportunities with MAC-layer sensing in cognitive radio networks. IEEE Transactions on Mobile Computing, 7(5), 533–545.

    Article  Google Scholar 

  24. He, Z., Mao, S., & Kompella, S. (2014, December). QoE driven video streaming in cognitive radio networks: The case of single channel access. In 2014 IEEE global communications conference (GLOBECOM) (pp. 1388–1393). IEEE.

  25. Ciftci, S., & Torlak, M. (2008, November). A comparison of energy detectability models for spectrum sensing. In Global telecommunications conference, 2008. IEEE GLOBECOM 2008 (pp. 1–5). IEEE.

Download references

Acknowledgements

The authors deeply acknowledge the support from Visvesvaraya PhD Scheme, (DeitY), Govt. of India.

Author information

Authors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, 700032, India

    Sudipta Dey & Iti Saha Misra

Authors
  1. Sudipta Dey
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Iti Saha Misra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sudipta Dey.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dey, S., Misra, I.S. A Novel Content Aware Channel Allocation Scheme for Video Applications over CRN. Wireless Pers Commun 100, 1499–1515 (2018). https://doi.org/10.1007/s11277-018-5650-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5650-4

Keywords

Search

Navigation