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2018 ITU Kaleidoscope Academic Conference




                                                                    Consumer Electronics, vol. 62, no. 4, pp. 380 – 388,
                                                                    Nov. 2016.
                                                              [8]   J.Nightingale, P. Salva-Garcia, Jose M. Alcaraz
                                                                    Calero, and Q.Wang, “5G-QoE: QoE Modelling for
                     (a) Live video sequesces (original)            Ultra-HD Video Streaming in 5G Networks”, IEEE
                                                                    Trans. on Broadcasting, vol. 62, no. 4, pp. 621 – 634,
                                                                    April 2018.
                                                              [9]   M. De Filippo De Grazia, D. Zucchetto , A. Testolin,
                                                                    A. Zanella , M. Zorzi, and M.Zorzi, “QoE Multi-
                                                                    Stage Machine Learning for Dynamic Video
                   (b) Received video sequence (decoded)
                                                                    Streaming,”  IEEE Trans. on Cognitive Comm. and
                                                                    Networks, vol. 4, no. 1, pp. 146–161, March 2018.
            Figure 9 – Some original and decoded frames during live
                               streaming.                     [10]  M. Gadaleta, F. Chiariotti, M. Rossi, and A. Zanella,
                                                                    “D-DASH:  A Deep Q-learning Framework for
                  6.  CONCLUSION AND FUTURE WORK                    DASH Video Streaming,” IEEE Trans. on Cognitive
                                                                    Comm. and Networking, vol. 3, no. 4, pp. 703-718
           A HTTP adaptive streaming through 4G wireless network    Dec. 2017.
           was implemented using  Double Sarsa approach of    [11]  R. S. Sutton and A. G. Barto, “Reinforcement
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           choices that are made to adjust video quality in a real time   Massachusetts, 2012.
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           system and the action to be selected in that state providing   [12]  H.V. Hasselt, "Double Q-learning," Advances in
           maximum reward. The proposed Double Sarsa based          Neural Information Processing Systems Conference
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           was developed and implemented utilizing ITU-T P.1203.1   2010), Dec. 2010.
           model. The results  were validated using  FR  video quality
           metrics and proposed method could be recommended in   [13]  H. V. Hasselt, A. Guez and D. Silver, “Deep
                                                                    Reinforcement Learning with Double Q-learning”,
           standardization  of future  audio-visual streaming services
           over wireless IP network. The system was implemented and   DOI: arXiv:1509.06461, Dec. 2015.
           tested in one  way communication;  however, it can   [14]  M. Dumke, “Double Q(σ) and Q(σ,γ)Unifying
           undoubtedly be employed to facilitate two-way  video    Reinforcement Learning Control Algorithms”, DOI:
           communication.                                          arXiv:1711.01569v1 5, Nov. 2017.
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