A QoE Estimation Model for Video Streaming over 5G Millimeter Wave Network

  • Yanjun HouEmail author
  • Wen’an Zhou
  • Lijun Song
  • Mengyu Gao
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 2)


With the rapid development of mobile communication, human’s demand for communication capacity increasing, a fifth-generation communications network (5G) have gained popularity because of enormous amount of spectrum in the millimeter wave (mmWave) bands. The 5G network is not only to provide people with more high data transfer rates and lower latency, but also to provide users with more meaningful and personalized service based on the users and their understanding of the service required. Nowadays, video streaming service plays an increasing important role in human’s daily life. However, the existing video streaming service application scenarios are mostly in Long Term Evolution network (LTE) and wireless network, there are few articles about studying video streaming service quality evaluation method in 5G network, so we conduct a study on the quality of experience (QoE) of video streaming service under 5G mmWave network scenario with NS-3. Under this scenario, video streaming system is created. By obtaining the quality of service (QoS) parameters of the network scenario, the non-linear regression function is used to predict the QoE of our video streaming service. The fit coefficient of the result shows that our model is powerful.


Packet Loss Video Streaming Mean Opinion Score OFDM Symbol Mobile Traffic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Cisco VNI Forecast, Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2013―2018, Cisco Public Information, Feb. 2014.Google Scholar
  2. 2.
    Sakaguchi, Kei, et al. Millimeter-wave Evolution for 5G Cellular Networks. Ieice Transactions on Communications E98.B.3(2014):388-402.Google Scholar
  3. 3.
    Bae, Jung Sook, et al. Architecture and performance evaluation of Millimeter wave based 5G mobile communication system. International Conference on Information and Communication Technology Convergence 2014:847-851.Google Scholar
  4. 4.
    Pi, Zhouyue, and F. Khan. An introduction to millimeter-wave mobile broadband systems. IEEE Communications Magazine 49.6(2011):101-107.Google Scholar
  5. 5.
    S. Akoum, O. El Ayach,et al, Coverage and capacity in millimeter wave cellular systems, 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), Pacific Grove, CA, 2012, pp. 688-692.Google Scholar
  6. 6.
    T. S. Rappaport, S. Sun,et al. Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!. Access IEEE 1.1(2013):335-349.Google Scholar
  7. 7.
    S. Hur, T. Kim, D. J. Love, et al. Millimeter Wave Beamforming for Wireless Backhaul and Access in Small Cell Networks. IEEE Transactions on Communications 61.10(2013):4391-4403.Google Scholar
  8. 8.
    T. Kim, J. Park, J. Seol, et al. Tens of Gbps support with millimeter wave beamforming systems for next generation communications. GLOBECOM 2013 - 2013 IEEE Global Communications Conference 2013:3685-3690.Google Scholar
  9. 9.
    Niu, Yong, et al. A survey of millimeter wave communications (millimeter wave) for 5G: opportunities and challenges. Wireless Networks 21.8(2015):2657-2676.Google Scholar
  10. 10.
    Zhang, M., Mezzavilla, et al. Transport Layer Performance in 5G millimeter wave Cellular. (2016).Google Scholar
  11. 11.
    Mezzavilla, M., Dutta, et al. 5G Millimeter wave Module for the ns-3 Network Simulator. ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems ACM, 2015:283-290.Google Scholar
  12. 12.
    Pierucci, Laura. The quality of experience perspective toward 5G technology. IEEE Wireless Communications 22.4(2015):10-16.Google Scholar
  13. 13.
    3GPP Technical Specification TS 23.107 V11.0.0, Qualityof Services (QoS) Concept and Architecture, June 2012Google Scholar
  14. 14.
    Mitra, K. Zaslavsky, et al. Context-Aware QoE Modelling, Measurement, and Prediction in Mobile Computing Systems. Mobile Computing, IEEE Transactions on, vol.14, no.5, pp.920,936, May 2015 doi: 10.1109/TMC.2013.155Google Scholar
  15. 15.
    Y. Kang, H. Chen, and L. Xie, An artificial-neural-network-based QoE estimation model for video streaming over wireless networks, in Communications in China (ICCC), 2013 IEEE/CIC International Conference on. IEEE, 2013, pp. 264–269.Google Scholar
  16. 16.
    M. A. Santos, J. Villalón et al. A novel QoE aware multicast mechanism for video communications over IEEE 802.11WLANs, IEEE J. Sel. Areas Commun., vol. 30, no. 7, pp. 1205–1214,Aug. 2012Google Scholar
  17. 17.
    A. U. Mian, Z. Hu, et al. A decision theoretic approach for in-service QoE estimation and prediction of P2P live video streaming systems based on user behavior modeling and context awareness. JICS,vol. 10, no. 11, pp. 3429–3436, 2013.Google Scholar
  18. 18.
    T. De Pessemier,et al.Quantifying the influence of rebuffering interruptions on the user’s quality of experience during mobile video watching. IEEE Trans.Broadcast., vol. 59, no. 1, pp. 47–61, Mar. 2013.Google Scholar
  19. 19.
    S.-O. Lee and D.-G. Sim. Hybrid bitstream-based video quality assessment method for scalable video coding. Opt. Eng., vol. 51, no. 6, pp. 067403-1–067403-9, Jun. 2012.Google Scholar
  20. 20.
    Ns-3 Network Simulator;
  21. 21.
    S. Dutta, M. Mezzavilla, et al. Frame structure design and analysis for millimeter wave cellular systems. in arXiv:1512.05691 [cs.NI], Dec. 2015.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yanjun Hou
    • 1
    Email author
  • Wen’an Zhou
    • 1
  • Lijun Song
    • 1
  • Mengyu Gao
    • 1
  1. 1.School of computer scienceBeijing University of Posts andTelecommunicationsBeijingChina

Personalised recommendations