Random Linear Network Coding for 5G Mobile Video Delivery

An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio

Class-Based MDP for improved multimedia transmission over LTE

International audienceThis paper proposes an improved cross-layer control mechanism to efficiently stream videos to mobile users over an LTE network. A proxy-based filtering algorithm among scalable layers is considered to decide the number of SVC layers to transmit for each frame according to the communication conditions and to the class to which the video belongs to. The problem is cast in the context of Markov Decision Processes which allow the design of foresighted policies maximizing some long-term accumulated reward. Optimal actions to apply to the system are obtained by reinforcement learning. The proposed solution is implemented in an LTE simulation platform. Experiments show the performance of the proposed class-based layer filtering algorithm for a single video transmission and its robustness to content changes