Joint heterogeneous statistical-QoS/QoE provisionings for edge-computing based WiFi offloading over 5G mobile wireless networks

Abstract

As one of the critical techniques to support the multimedia services over mobile wireless networks, the statistical quality of service (QoS) technique has been proved to be effective in statistically guaranteeing delay-bounded multimedia data transmissions over the time-varying wireless channels. On the other hand, WiFi offloading technique has been widely cited as one of the 5G promising candidate techniques to improve the QoS/video quality-of-experience (QoE) for mobile users. However, due to the limitations of mobile wireless networks, it is difficult for the joint measurement of the statistical QoS and QoE. As a result, supporting the joint statistical-QoS/QoE provisionings has imposed many new challenges for the 5G mobile wireless networks. To effectively overcome the aforementioned challenges, in this paper we propose the joint heterogeneous statistical QoS/QoE provisioning schemes by applying the edge-computing based WiFi offloading technique over 5G mobile wireless networks. In particular, we build the wireless communication model, the edge-computing based WiFi offloading model, and the joint heterogeneous statistical QoS/QoE model. Under the joint heterogeneous statistical QoS/QoE constraints, we formulate and solve the effective-capacity optimization problem by using the optimal power-allocation policies for our proposed WiFi offloading scheme. Also conducted is a set of simulations which evaluate the system performance and show that our proposed schemes outperform the other existing schemes for efficiently implementing the joint heterogeneous statistical-QoS/QoE provisionings over 5G mobile wireless networks.