Stefan Valentin - Principal Researcher, Huawei Technologies, France Communication systems
Date: - Location: Eurecom
Mobile video streaming is a rising business but poses significant challenges for network and service operators. In mobile networks, time-variant wireless channels often violate the content's rate requirement, which leads to poor streaming quality and wasted channel capacity. This tutorial will cover new techniques for anticipatory adaptation, which drastically improve this situation. By proactively adapting load and resource allocation to a prediction of the wireless channel state, the network prevents service outages even before they occur. Drive tests and simulation consistently show impressive gains in video quality at no significant cost for the operators. After presenting powerful heuristics, we will survey optimal formulations based on linear programming, quadratically constrained programming, and Markov decision processes. Channel prediction will be covered from the perspective of applying support vector machines and Bayesian spatio-temporal inference to radio maps. We will conclude with a vision for context and user-centric adaptation that could play a key role for providing truly seamless services in 5G.
