Adaptive Video Streaming Over LTE Networks

• Improving QoE and Fairness in HTTP Adaptive Streaming over LTE Network [1]
• The proposed algorithm can be used into two modes: client-side and network-assisted.
• Authors have considered three elements to assign the rates
• Client Buffer Size (DASH standard allows clients to report it)
• Channel Condition 
• Video Complexity
• Experiments have been done in "ns2".
• In their simulations, the available resources dedicated to streaming users is dynamically updated.
• They have used SSIM as for the quality metric.

• Optimization of HTTP adaptive streaming over mobile cellular networks [2]
• They have considered data and video users at the same time.
• They have used the same utility function for data and video users, however with different parameters.
• All fairness utility functions are of the same form [3].
• They didn't change the default proportionally fair scheduler inside eNB. They instructed that scheduler by providing it with GBR values. 
• They compared their work with Best Effort and traditional GBR schedulers. 
• All these schedulers share the same principle, described in [4].

References
[1] Cicalo, Sergio, et al. "Improving QoE and Fairness in HTTP Adaptive Streaming over LTE Network." (2015).
[2] D. De Vleeschauwer, H. Viswanathan, A. Beck, S. Benno, G. Li, and R. Miller, “Optimization of HTTP adaptive streaming over mobile cellular networks,” in Proc. IEEE INFOCOM, 2013, pp. 898–997.
[3] M. Uchida, J. Kurose, “An Information-Theoretic Characterization of Weighted α-Proportional Fairness,” In Proceedings of IEEE INFOCOM'09, ( pp. 1053-1061)
[4] M. Andrews, L. Qian, A. Stlyar, “Optimal Utility Based Multi-user Throughput Allocation subject to Throughput Constraints,” In Proceedings of IEEE INFOCOM'05, Vol. 4, pp. 2415-2424, 2005