Paper Info
Title
Exploiting Scalable Video Coding for Content Aware Downlink Video Delivery over LTE
Abstract
We propose a content aware scheduler to allocate resources for video delivery on the downlink of a Long Term Evolution LTE network. We consider multiple users subscribe to a video streaming service, and request videos encoded in H.264 Scalable Video Coding format. The scheduler maximizes the average video quality across all users by assigning resource blocks based on their device capabilities, link qualities, and available resources. We measure video quality using two full reference metrics: peak signal-to-noise ratio PSNR and structural similarity SSIM index. We formulate the video delivery problem first as an integer linear program ILP, and then reduce it to the multiple choice knapsack problem MCKP. To solve the MCKP, we propose two fast heuristics with reduced processing overhead at the eNodeB, and a fully polynomial-time approximate scheme FPTAS using dynamic programming and profit-scaling. Our evaluation results indicate that the heuristics are within a factor of <InlineEquation ID=\"IEq1\" <EquationSource Format=\"TEX\"$\\frac{1}{2}$</EquationSource> </InlineEquation>, and the FPTAS is very close to the optimal obtained from an ILP solver. We also propose a signaling mechanism to implement the content aware scheduler in existing LTE systems, and evaluate the impact of signaling delay on video distortion using both indoor and outdoor measurements collected from AT&T and T-Mobile networks.
Year
DOI
Venue
2014
10.1007/978-3-642-45249-9_28
ICDCN
Keywords
Field
DocType
scalable video coding,lte
Dynamic programming,Computer science,Computer network,Real-time computing,Heuristics,Linear programming,Solver,EnodeB,Video quality,Telecommunications link,Scalable Video Coding
Conference
Volume
ISSN
Citations 
8314
0302-9743
6
PageRank 
References 
Authors
0.45
13
4
Name
Order
Citations
PageRank
Ahmed Ahmedin1121.97
Kartik Pandit2251.31
Dipak Ghosal32848163.40
Amitava Ghosh42908229.17