Adaptive resource allocation and frame scheduling for wireless multi-user video streaming

We propose an application-driven multi-user resource allocation and frame scheduling concept for wireless video streaming. Our approach is based on joint optimization of the application layer, the data link layer and the physical layer. For this, key parameters from these three layers are abstracted. The abstracted parameters at the application layer describe the rate-distortion characteristics of the pre-encoded video streams. At the lower layers they describe the current transmission characteristics of all users. The outcome of the joint optimization leads to adaptive resource allocation at the lower layers and an adaptive decision on which frames to send on the application layer. We show that for our scenario the expected video quality at the client side can be described analytically which leads to low complexity joint optimization. The performance of our approach is demonstrated using a real-time testbed implementation.