Improving Recovery Rate for Packet Loss in Large-Scale Telecom Smart TV Systems

Xiuyan JIANG  Dejian YE  Yiming CHEN  Xuejun TIAN  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.11   pp.2365-2375
Publication Date: 2013/11/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.2365
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Information Network
Keyword: 
smart TV,  packet loss,  QoS,  error recovery,  

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Summary: 
Smart TVs are expected to play a leading role in the future networked intelligent screen market. Currently, many operators are planning to deploy it in large scale in a few years. Therefore, it is necessary for smart TVs to provide high quality services for users. Packet loss is one critical reason that decreases the QoS in smart TVs. Even a very small amount of packet loss (1-2%) can decrease the QoS and affect users' experience seriously. This paper applies stochastic differential equations to analyzing the queue in the buffer of access points in smart TV multicast systems, demonstrates the reason for packet loss, and then proposes an end-to-end error recovery scheme (short as OPRSFEC) whose core algorithm is based on Reed-Solomon theory, and optimizes four aspects in finite fields: 1) Using Cauchy matrix instead of Vandermonde matrix to code and decode; 2) generating inverse matrix by table look-up; 3) changing the matrix multiplication into the table look-up; 4) originally dividing the matrix multiplication. This paper implements the scheme on the application layer, which screens the heterogeneity of terminals and servers, corrects 100% packet loss (loss rate is 1%-2%) in multicast systems, and brings very little effect on real-time users experience. Simulations demonstrate that the proposed scheme has good performances, successfully runs on Sigma and Mstar Moca TV terminals, and increases the QoS of smart TVs. Recently, OPRSFEC middleware has become a part of IPTV2.0 standard in Shanghai Telecom and has been running on the Mstar boards of Haier Moca TVs properly.