Skip to main content

Advertisement

SpringerLink
Log in

CATECAS: a content-aware transmission efficiency based channel allocation scheme for cognitive radio users with improved QoE

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

Cognitive radio (CR) is a promising technology for the upcoming 5G communication which addresses opportunistic channel usage for enhanced spectrum utilization. However, Quality of Service (QoS) provisioning is a major challenge for CR Network due to the service interruption and packet error caused by random primary activities. In addition to this, periodic spectrum sensing for primary user protection reduces the effective throughput of the secondary users (SUs). However, to ensure QoS of SUs especially for video application, throughput enhancement is necessary which can be achieved by efficient spectrum sensing and channel allocation policy. As the QoS requirements are different for different secondary applications, we propose a novel content aware channel allocation scheme that enhances the Quality of Experience (QoE) of SUs. At first, the proposed scheme analyzes the QoS requirements of different SUs and prioritizes them. Consequently, the optimum sensing duration is determined to maximize the transmission efficiency and throughput of SUs. Finally, a novel content aware transmission efficiency-based channel assignment scheme (CATECAS) is proposed for SUs, considering the estimated channel quality and QoS requirements concurrently. Extensive performance analysis of CATESCAS on real-time video and file download applications confirms significant QoE improvement for SUs especially for rapid movement type of video application, which is considered as the most critical among different secondary applications.

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
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Federal Communications Commission et al. (2002). Spectrum policy task force report, FCC 02-155.

  2. 5G Infrastructure PPP Association et al. (2015). 5G vision-the 5G infrastructure public private partnership: The next generation of communication networks and services. White Paper, February.

  3. Langtry, C. (2016). ITU-R activities on 5G. In IEEE World Forum on the Internet of Things, (pp. 14–16).

  4. Jiang, W., & Cao, H. (2015). SIG on cognitive radio for 5G. Retrieved December 2015, from http://cn.committees.comsoc.org/.

  5. Zhang, N., Zhou, H., Zheng, K., Cheng, N., Mark, J. W., & Shen, X. (2015). Cooperative heterogeneous framework for spectrum harvesting in cognitive cellular network. IEEE Communications Magazine, 53(5), 60–67.

    Article  Google Scholar 

  6. VNI CISCO. (2014). Cisco visual networking index: Forecast and methodology, 2013–2018: Visual networking index (VNI).

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  10. Chair, Z., & Varshney, P. K. (1986). Optimal data fusion in multiple sensor detection systems. IEEE Transactions on Aerospace and Electronic Systems, 1, 98–101.

    Article  Google Scholar 

  11. Gardner, W. A. (1991). Exploitation of spectral redundancy in cyclostationary signals. IEEE Signal Processing Magazine, 8(2), 14–36.

    Article  Google Scholar 

  12. Hillenbrand, J., Weiss, T. A., & Jondral, F. K. (2005). Calculation of detection and false alarm probabilities in spectrum pooling systems. IEEE Communications Letters, 9(4), 349–351.

    Article  Google Scholar 

  13. Ganesan, G., & Li, Y. (2005). Cooperative spectrum sensing in cognitive radio networks. In First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005, (pp. 137–143). IEEE.

  14. Ghasemi, A., & Sousa, E. S. (2005). Collaborative spectrum sensing for opportunistic access in fading environments. In First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005., (pp. 131–136). IEEE.

  15. 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 

  16. 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 

  17. Hassan, M., & Krunz, M. (2005). A playback-adaptive approach for video streaming over wireless networks. In GLOBECOM’05. IEEE Global Telecommunications Conference, 2005., (Vol. 6, p. 5). IEEE.

  18. 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(6), 841–851.

    Article  Google Scholar 

  19. Wang, Y., & Zhu, Q.-F. (1998). Error control and concealment for video communication: A review. Proceedings of the IEEE, 86(5), 974–997.

    Article  Google Scholar 

  20. Hassan, M., El-Taruni, M., & Zrae, R. (2015). A joint adaptive modulation and channel coding scheme for multimedia communications over wireless channels. International Journal of Wireless and Mobile Computing, 9(1), 99–114.

    Article  Google Scholar 

  21. 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 

  22. Yi, X., Donglin, H., & 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 

  23. Bourdena, A., Pallis, E., Kormentzas, G., & Mastorakis, G. (2014). Efficient radio resource management algorithms in opportunistic cognitive radio networks. Transactions on Emerging Telecommunications Technologies, 25(8), 785–797.

    Article  Google Scholar 

  24. Bayrakdar, M. E., Atmaca, S., & Karahan, A. (2016). A slotted aloha-based cognitive radio network under capture effect in Rayleigh fading channels. Turkish Journal of Electrical Engineering and Computer Sciences, 24(3), 1955–1966.

    Article  Google Scholar 

  25. He, Z., Mao, S., & Kompella, S. (2016). Quality of experience driven multi-user video streaming in cellular cognitive radio networks with single channel access. IEEE Transactions on Multimedia, 18(7), 1401–1413.

    Article  Google Scholar 

  26. Zhang, N., Zhang, S., Zheng, J., Fang, X., Mark, J. W., & Shen, X. (2017). QOE driven decentralized spectrum sharing in 5G networks: Potential game approach. IEEE Transactions on Vehicular Technology, 66(9), 7797–7808.

    Article  Google Scholar 

  27. Piran, M. J., Tran, N. H., Suh, D. Y., Song, J. B., Hong, C. S., & Han, Z. (2016). QOE-driven channel allocation and handoff management for seamless multimedia in cognitive 5G cellular networks. IEEE Transactions on Vehicular Technology, 66(7), 6569–6585.

    Article  Google Scholar 

  28. Lin, S., Kong, L., Gao, Q., Khan, M. K., Zhong, Z., Jin, X., et al. (2017). Advanced dynamic channel access strategy in spectrum sharing 5G systems. IEEE Wireless Communications, 24(5), 74–80.

    Article  Google Scholar 

  29. Fan, S., & Zhao, H. (2018). Delay-based cross-layer QOS scheme for video streaming in wireless ad hoc networks. China Communications, 15(9), 215–234.

    Article  Google Scholar 

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

    Article  Google Scholar 

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

  32. Li, S., Luan, T. H., & Shen, X. (2010). Channel allocation for smooth video delivery over cognitive radio networks. In 2010 IEEE Global Telecommunications Conference GLOBECOM 2010, (pp. 1–5). IEEE.

  33. Bhattacharya, A., Ghosh, R., Sinha, K., & Sinha, B. P. (2011). Multimedia communication in cognitive radio networks based on sample division multiplexing. In 2011 Third International Conference on Communication Systems and Networks (COMSNETS 2011), (pp. 1–8). IEEE.

  34. Hassan, M. S., Abusara, A., Din, M. S. E., & Ismail, M. H. (2016). On efficient channel modeling for video transmission over cognitive radio networks. Wireless Personal Communications, 91(2), 919–932.

    Article  Google Scholar 

  35. Khan, A., Sun, L., & Ifeachor, E. (2009). Content clustering based video quality prediction model for MPEG4 video streaming over wireless networks. In 2009 IEEE International Conference on Communications, (pp. 1–5). IEEE.

  36. Zhou, X., Ma, J., Li, G. Y., Kwon, Y. H., & Soong, A. C. K. (2009). Probability-based optimization of inter-sensing duration and power control in cognitive radio. IEEE Transactions on Wireless Communications, 8(10), 4922–4927.

    Article  Google Scholar 

  37. Yang, L., Cao, L., & Zheng, H. (2008). Proactive channel access in dynamic spectrum networks. Physical Communication, 1(2), 103–111.

    Article  Google Scholar 

  38. Liang, Y., Zeng, Y., Peh, E. C. Y., & Hoang, A. T. (2008). Sensing-throughput tradeoff for cognitive radio networks. IEEE Transactions on Wireless Communications, 7(4), 1326–1337.

    Article  Google Scholar 

  39. Ghasemi, A., & Sousa, E. S. (2007). Optimization of spectrum sensing for opportunistic spectrum access in cognitive radio networks. In 2007 4th IEEE Consumer Communications and Networking Conference, (pp. 1022–1026). IEEE.

  40. Khan, S., Duhovnikov, S., Steinbach, E., & Kellerer, W. (2007). MOS-based multiuser multiapplication cross-layer optimization for mobile multimedia communication. Advances in Multimedia, 2007(1), 6–6.

    Google Scholar 

  41. Lincke, T. R. (2002) Exploring the computational limits of large exhaustive search problems. PhD thesis, ETH Zurich.

  42. Cormen, T. H., Leiserson, C. E., Rivest, R. L., Stein, C., et al. (2001). Introduction to algorithms, chapter 11. Cambridge: MIT press.

    Google Scholar 

  43. Oto, M. C., & Akan, O. B. (2012). Energy-efficient packet size optimization for cognitive radio sensor networks. IEEE Transactions on Wireless Communications, 11(4), 1544–1553.

    Article  Google Scholar 

  44. Pitrey, Y., Barkowsky, M., Le Callet, P., & Pépion, R. (2010). Subjective quality assessment of MPEG-4 scalable video coding in a mobile scenario. In 2010 2nd European Workshop on Visual Information Processing (EUVIP), (pp. 86–91). IEEE.

  45. Lee, J.-S., De Simone, F., Ebrahimi, T., Ramzan, N., & Izquierdo, E. (2012). Quality assessment of multidimensional video scalability. IEEE Communications Magazine, 50(4), 38–46.

    Article  Google Scholar 

  46. Wang, D., Speranza, F., Vincent, A., Martin, T., & Blanchfield, P. (2003). Toward optimal rate control: A study of the impact of spatial resolution, frame rate, and quantization on subjective video quality and bit rate. In Visual Communications and Image Processing 2003, (Vol. 5150, pp. 198–210). International Society for Optics and Photonics.

Download references

Acknowledgements

The authors deeply acknowledge the support from Visvesvaraya Ph.D. 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. CATECAS: a content-aware transmission efficiency based channel allocation scheme for cognitive radio users with improved QoE. Telecommun Syst 74, 157–171 (2020). https://doi.org/10.1007/s11235-019-00648-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-019-00648-7

Keywords

Search

Navigation