Heterogeneous QoS Video Broadcasting with Optimal Joint Layered Video and Digital Fountain Coding

Abstract

Heterogeneous QoS video broadcast over wireless network is a challenging problem, where the demand for better video quality needs to be reconciled with different display size, channel condition and QoS requirements. In this paper, we present a framework for broadcasting scalable video to heterogeneous mobile users with diverse display devices and different channel conditions, which includes joint spatial-temporal layered video and Fountain coding optimization. First, we develop an elastic rate video adaptation method so as to serve mobile users with heterogeneous QoS requirements, which includes a hybrid temporal-spatial quality metric. Joint Fountain coding protection is introduced so as to provide adaptive and reliable video streams. Second, we use dynamic programming approach to obtain optimal video layer structure, so as to achieve maximum broadcasting utility. The objective is to achieve maximum overall receiving quality of the heterogeneous QoS users. Experimental results demonstrate the effectiveness of the solution.

Flow Optimization for Scalable Multi-view Video over Wireless Network

“…We adopt temporal-spatial content rate-distortion metric [8] to measure the video temporal and spatial quality of each view. For each spatial level v, the rate and distortion in temporal domain are given by:…”

“…We utilize a hybrid temporal-spatial content rate-distortion metric [8] to measure the temporal and spatial quality of each view received at the user and define the corresponding user utility. The flow allocation problem is formulated as an utility maximization model for efficient SMVV streaming, then a distributed and layered solution based on Lagrangian dual decomposition is proposed, in which the rate allocation in each video layer can be solved by the shortest path algorithm and the sub-gradient algorithm.…”

QoE-Enabled Big Video Streaming for Large-Scale Heterogeneous Clients and Networks in Smart Cities

“…Scalable video sources provide more adaptability by applying a variety of schemes, such as scalable stream extraction (e.g., [39], [49]- [52]), layer generation with different priorities (e.g., [40], [53]- [55]), and summarization (e.g., [56]), before they are dispatched to the next layers.…”

Multiple Configurations LT Codes

“…Ratelessness is an advantage of LT codes, with which a sender does not need to attend to the individual differences of receivers, and the performance of LT codes is independent of channel erasure rate because of another key characteristic, the universal property. LT codes, therefore, can be adopted as a solution for transmission through an unknown channel or in broadcasting scenarios over a heterogeneous network [3], [4].…”