QoE-driven cross-layer optimization in wireless networks addressing system efficiency and utility fairness

We address a multi-criteria Quality of Experience (QoE) driven optimization problem for multi-user wireless video delivery. The optimization is done in a cross-layer fashion by using parameterized models of application and link layer in order to determine the application data rate and the network resources that fulfill the criteria. Mean Opinion Score (MOS) is used as a unified utility metric that encompasses the user-perceived quality under certain receiving conditions for the user application. We consider two partially contrary objectives, which are maximizing the total perceived quality of the whole system and maximizing the utility fairness among all users. A tuning mechanism is proposed, which allows the network operator to change dynamically its operating point of the resource allocation based on its pre-defined policy of any combinations of these two objectives. We implemented the proposed tuning algorithm in an emulated Long-Term Evolution (LTE) system and verified its feasibility through simulations.