JOURNAL ARTICLE

End-to-end distortion optimized error control for real-time wireless video streaming

Abstract

In wireless video streaming, the packet loss often occurs and affects the end-user visual quality. To alleviate the transmission error effects, intra refresh coding is usually used to improve the streaming error resilience ability from the view of source coding. At the physical layer, the adaptive modulation and coding (AMC) is also used to promote the transmission reliability at the transporting level. Both the error control components have their own influences on the received video quality. To achieve the best video transmission performance, it is crucial to make an error control tradeoff between intra refresh coding and AMC. In this paper, we propose an end-to-end video distortion optimized cross-layer error control method which jointly considers the video quantization parameter (QP) and intra refresh rate at the application layer, and AMC at the physical layer for delay-constraint real-time video streaming. The experimental results show that the proposed cross-layer error control streaming method can achieve the superior objective and subjective performances to the layer-independent error control streaming methods with and without cross-layer optimization.

Keywords:
Computer science Video quality Real-time computing Network packet Error detection and correction Packet loss Wireless Quantization (signal processing) Coding (social sciences) Bit error rate Physical layer Computer network Channel (broadcasting) Algorithm Telecommunications

Metrics

4
Cited By
0.93
FWCI (Field Weighted Citation Impact)
11
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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