QoE-aware Downlink Resource Allocation Scheme for Live Streaming in Mobile Edge Computing

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In recent years, mobile data traffic grows continuously. To load demand for more bandwidth in mobile network, the standards of the 5G mobile network are being developed. Based on the evolution of 5G mobile network, ETSI proposed mobile edge computing (MEC). MEC brings computing and storage resources to the edge of mobile network, and enables UE to use cloud computing and storage resources closely to reduce the increasing load on the core network. MEC is characterized by low latency, proximity, high bandwidth, real-time insight into radio network information and location awareness, and improve UE’s quality of experience. Live streaming need better quality of experience (QoE) than other mobile applications. In this paper, we proposed a downlink resource allocation scheme to provide better quality of experience for the UEs who watch live streaming. We used the characteristic of MEC, real-time insight into radio network information, to receive real-time data rate of UE and MPEG-DASH live streaming information. Using the real-time information and QoE function quantify the quality of experience, which is calculated after each UE is allocated resource. The resource allocation scheme we proposed combines Max-Min scheduling with UE’s QoE, to provide better quality of experience to UE. Simulation results show that the method we propose can improve UE’s QoE and has good fairness.