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In the last years, the video content consumed by mobile users has increased exponentially. Since mobile network capacity cannot be increased as fast as required, it is crucial to develop intelligent schedulers that allocate radio resources very efficiently and are able to provide a high Quality of Experience (QoE) to most of the users. This paper proposes a new and effective scheduling solution—the Maximum Buffer Filling (MBF) algorithm—which aims to increase the number of satisfied users in video streaming services provided by wireless networks. The MBF algorithm uses the current buffer level at the client side and the radio channel conditions, which are reported to the network by the client, as well as the bitrate of the requested video segment. The proposed scheduling strategy can also fulfill different satisfaction criteria, since it can be tuned to maximize the numbers of users with high QoE levels or to minimize the number of users with low QoE levels. A simulation framework was developed, considering a Long Term Evolution (LTE) scenario, in order to assess the performance of the proposed scheduling scheme and to compare it with other well-known scheduling solutions. The results show the superior performance achieved by the proposed technique, in terms of the number of satisfied and unsatisfied users.

QoE-Aware Scheduling Algorithm for Adaptive HTTP Video Delivery in Wireless Networks