In this paper, we present a Quality of Experience (QoE) based framework for point-to-point adaptive video in best effort band-limited satellite networks. We consider two time-varying factors degrading QoE in this scenario, namely: network unavailability due to bursty erasure events and the best effort shared channel dynamics. Our proposal is two-fold 1) Content-aware erasure protection through the novel Overlapping Network Coding (ONC) and 2) An online QoE optimization formulation for source video adaptation to account for network variations of the best effort network. Furthermore, we show the feasibility of combining these two strategies and their benefits in terms of QoS and QoE metrics. Our contributions are as follows. Firstly, we investigate generations based fixed rate ONC and show its advantage over Maximum Distance Separable (MDS) codes for better recovery of the intra-coded frames. Specifically, ONC can provide up to 85% of gain in QoS as compared to MDS code for the intra-coded frames when there are more than N − K erasures in a coding block. The penalty of performance loss on predictive-coded frames minimally affects QoE. Secondly, the online QoE-driven cross-layer adaptation, shows an improvement of at least 50% with respect to a nonadaptive strategy. Finally we show that by combining both ONC for bursty erasures and QoE adaptation we can obtain improvements in reducing SSIM spread up to 90% for a smooth QoE video throughout the entire streaming session.

A novel cross-layer optimized video adaptation driven by perceptual semantics is presented. The design target is streamed live video to enhance situational awareness in challenging communications conditions. Conventional solutions for recreational applications are inadequate and novel quality of experience (QoE) framework is proposed which allows fully controlled adaptation and enables perceptual semantic feedback. The framework relies on temporal/spatial abstraction for video applications serving beyond recreational purposes. An underlying cross-layer optimization technique takes into account feedback on network congestion (time) and erasures (space) to best distribute available (scarce) bandwidth. Systematic random linear network coding (SRNC) adds reliability while preserving perceptual semantics. Objective metrics of the perceptual features in QoE show homogeneous high performance when using the proposed scheme. Finally, the proposed scheme is in line with content-aware trends, by complying with information-centric-networking philosophy and architecture.