Skip to main content
SpringerLink
Log in

Perceptual service-level QoE and network-level QoS control model for mobile video transmission

  • Published:
Telecommunication Systems Aims and scope Submit manuscript

Abstract

The cumulative effects of network transmission link imperfections and real-time limitations of video data result in multiple challenges for mobile video transmission. The challenges, together with the increasing expectations of users for well-displayed videos, further extend the complexity particularly in dense areas. To address the issues and provide efficient mobile video transmission, this work proposes a model with two phases: network-related settings (NRS) and video-related settings (VRS). The NRS is related to the mobile transmission link limits and develops four separate mobile networks, including long term evolution, 802.11 ax dual-band, and 802.11 ac. The VRS, on the other hand, is related to the video real-time constraints and covers five well-known compression algorithms used in the reference video preparation process. With comprehensibility in mind, the model comprises different factors that have a profound impact on the mobile video transmission process. The model is implemented and the results determine the video delivery efficiency in terms of the network-level quality of service and service-level quality of experience. To further validate the model, a testbed is set up and the measured experimental results are compared with those of the simulation. The results establish a baseline for efficient mobile video transmission on resource constraint devices.

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
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Similar content being viewed by others

Data availability

All the required data is in the manuscript.

Code availability

The required code is available in the manuscript itself.

References

  1. Uhrina, M., Bienik, J., & Vaculik, M. (2016). Procedure for mapping of objective video quality metrics to subjective MOS scale of VP9 compression standard for full HD resolution. In IEEE international conference on information and digital technologies (IDT) Rzeszow, Poland.

  2. Li, J., Yang, Q., Yang, J., Qin, M., & Kwak, K. S. (2018). User perceived QoS provisioning for video streaming in wireless OFDMA systems: Admission control and resource allocation. IEEE Access, 6, 44747–44762.

    Article  Google Scholar 

  3. Khorov, K., Kiryanov, A., Lyakhov, A., & Bianchi, G. (2019). A tutorial on IEEE 802.11 ax high efficiency WLANs. IEEE Communications Surveys and Tutorials, 21(1), 197–216.

    Article  Google Scholar 

  4. Sangkla, N., Sangkhapat, K., Rattanachai, T., Nguyen, T. G., Rujirakul, K., Soomlek, C., & Soin, C. (2016). Performance analysis of video transmission over IEEE 802.11 n wireless networks. Journal of Telecommunication, Electronic and Computer Engineering, 9(2–2), 35–40.

    Google Scholar 

  5. Zhang, Z., Jing, T., Han, J., Xu, Y., & Zhang, F. (2017). A new rate control scheme for video coding based on region of interest. IEEE Access, 5, 13677–13688.

    Article  Google Scholar 

  6. Ruiz, D., Escribano, G. F., Martínez, J. L., & Cuenca, P. (2016). Fast intra mode decision algorithm based on texture orientation detection in HEVC. Signal Processing: Image Communication, 44, 12–28.

    Google Scholar 

  7. Zhang, T., & Mao, S. (2018). An overview of emerging video coding standards. GetMobile: Mobile Computing and Communications, 22(4), 13–20.

    Article  Google Scholar 

  8. Zheng, K., Zhang, X., Zheng, Q., Xiang, W., & Hanzo, L. (2015). Quality-of-experience assessment and its application to video services in LTE networks. IEEE Wireless Communications, 22(1), 70–78.

    Article  Google Scholar 

  9. Solera, M., Toril, M., Palomo, I., Gomez, G., & Poncela, J. (2017). A testbed for evaluating video streaming services in LTE. Wireless Personal Communications, 98, 2753–2773.

    Article  Google Scholar 

  10. Ibrahim, S. K. and Khamiss N. N. (2019). A new wireless generation technology for video streaming. Journal of Computer Networks and Communications, 2019, 1–9.

  11. Yuan, H., Guo, C., Liu, J., Wang, X., & Kwong, S. (2017). Motion-homogeneous-based fast transcoding method from H.264/AVC to HEVC. IEEE Transactions on Multimedia, 19(7), 1416–1430.

    Article  Google Scholar 

  12. Bienik, J., Uhrina, M., & Kortis, P. (2017). Impact of constant rate factor on objective video quality assessment. Digital Image Processing and Computer Graphics, 15(4), 673–682.

  13. Laude, T., Adhisantoso, Y. G., Voges, J., Munderloh, M., & Ostermann, J. (2019). A comprehensive video codec comparison. APSIPA Transactions on Signal and Information Processing, 8, e30.

    Article  Google Scholar 

  14. Nasrallaa, M. M. (2020). Hybrid downlink scheduling approach for multi-traffic classes in LTE wireless systems. IEEE Access, 8, 82173–82186.

    Article  Google Scholar 

  15. Lonkar, S. A. and Reddy, K. V. (2020). Analysis of audio and video quality of voice over LTE (VoLTE) call. International Journal of Information Technology, 12(2), 1–14.

  16. Deng, D. J., Lien, S. Y., Lee, J., & Chen, K. C. (2016). On quality-of-service provisioning in IEEE 802.11 ax WLANs. IEEE Access, 4, 6086–6104.

    Article  Google Scholar 

  17. Carmona, J. V. C., Matos, E. M. C. D., Castro, B. S. L., Barros, F. J. B., Neto, M. C. D. A., & Pelaes, E. G. (2019). Video loss prediction model in wireless networks. PLOS ONE, 14(3), e0212407.

    Article  Google Scholar 

  18. Fernandes, P., Bernardo, M. V., Pinheiro, A. M. G., Fiadeiro, P. T., & Pereira, M. (2016). Quality comparison of the HEVC and VP9 encoders performance. Multimedia Tools and Applications, 76, 13633–13649.

    Article  Google Scholar 

  19. Chen, Y., Mukherjee, D., Han, J., Grange, A., Xu, Y., Parker, S., Chen, C., Su, H., Joshi, U., Chiang, C. H., Wang, Y., Wilkins, P., Bankoski, J., Trudeau, L., Egge, N., Valin, J. M., Davies, T., Midtskogen, S., Norkin, A., … Liu, Z. (2010). An overview of coding tools in AV1: the first video codec from the alliance for open media. APSIPA Transactions on Signal and Information Processing, 9, e6.

    Article  Google Scholar 

  20. Karim, S., He, H., Junejo, A. R., & Sattar, M. (2010). Measurement of objective video quality in social cloud based on reference metric. Wireless Communications and Mobile Computing, 2020, 1–13.

  21. Frnda, J., Nedoma, J., Vanus, J., & Martinek, R. (2019). A hybrid QoS–QoE estimation system for IPTV service. MDPI Electronics, 8(5), 585.

    Article  Google Scholar 

  22. Naveed, M., Qazi, S., Atif, S. M., Khawaja, B. A., & Mustaqim, M. (2019). SCRAS server-based cross layer rate-adaptive video streaming over 4G-LTE for UAV-based surveillance applications. MDPI Electronics, 8(5), 910.

    Article  Google Scholar 

  23. Uhrina, M., Frnda, J., Sevcik, L., & Vaculik, M. (2014). Impact of H.264/AVC and H.265/HEVC compression standards on the video quality for 4K resolution. Digital Image Processing and Computer Graphics, 12(4). https://doi.org/10.15598/aeee.v12i4.1216.

  24. Uhrina, M., Bienik, J., & Vaculik, M. (2016). Impact of GoP on the video quality of VP9 compression standard for full HD resolution. Digital Image Processing and Computer Graphics, 14(4), 445–452.

  25. Mallik, B., Akbar, A. S., & Kor, A. L. (2019). Mixed-resolution HEVC based multiview video codec for low bitrate transmission. Multimedia Tools and Applications, 78, 6701–6720.

    Article  Google Scholar 

  26. Salama, A., & Saatchi, R. (2019). Evaluation of wirelessly transmitted video quality using a modular fuzzy logic system. MDPI Technologies, 7(3), 67.

    Article  Google Scholar 

  27. Osmanovic, I., Husic, J. B., & Barakovic, S. A. (2018). Impact of media-related SIFs on QoE for H.265/HEVC video streaming. Journal of Communications Software and Systems, 14(2), 157–170.

    Article  Google Scholar 

  28. Kiwoli, L., Sam, A., & Manasseh, E. (2017). Performance analysis of carrier aggregation for various mobile network implementations scenario based on spectrum allocated. International Journal of Wireless and Mobile Networks, 9(5), 41–53.

  29. Nagin, K., Kassis, A., Lorenz, D. H., Barabash, K., & Raichstein, E. (2019). Estimating client QoE from measured network QoS. In Proceedings of the 12th ACM international conference on systems and storage (SYSTOR '19), Haifa, Israel.

  30. Wu, C. B., Wang, L. H., & Chou, Y. L. (2017). Hardware-and-memory-sharing architecture of deblocking filter for VP8 and H.264/AVC. IEEE Transactions on Consumer Electronics, 63(3), 216–224.

    Article  Google Scholar 

  31. Janabi, M. H. A., Ali, N. T. I., Sabti, K. D. M. A., Dhalimi, M. A. A., & Wahid, S. N. A. (2017). A new imaging technique for assessment of the effectiveness of long pulse Nd:YAG 532 nm laser in treatment of facial port wine stain. Journal of Cosmetic and Laser Therapy, 19(7), 418–421.

    Article  Google Scholar 

  32. Chakraborty, D., Saha, S., & Mukherjee, T. (2015). Near lossless image compression using block division byte compression and block optimization. In Emerging research in computing, information, communication and applications, Vol. 3.

Download references

Funding

The authors have no affiliation with any organization with a direct or indirect financial interest in the subject matter discussed in the manuscript.

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering Faculty, Hakim Sabzevari University, 9617976487, Sabzevar, Iran

    Mina Malekzadeh

Authors
  1. Mina Malekzadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mina Malekzadeh.

Ethics declarations

Conflict of interest

This manuscript has not been published in another journal or other publishing venue.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Malekzadeh, M. Perceptual service-level QoE and network-level QoS control model for mobile video transmission. Telecommun Syst 77, 523–541 (2021). https://doi.org/10.1007/s11235-021-00777-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11235-021-00777-y

Keywords

Search

Navigation