Joint redundant and random network coding for robust video transmission over lossy networks

  • Authors:
  • Xingjun Zhang;Cuiping Jing;Feilong Tang;Scott Fowler;Huali Cui;Xiaoshe Dong

  • Affiliations:
  • Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China;Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, China;Department of Science and Technology, Linköping University, Linköping, Sweden;Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China;Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China

  • Venue:
  • Mobile Information Systems - Advances in Network-Based Information Systems
  • Year:
  • 2012

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Abstract

In this paper a novel unequal packet loss protection scheme R2NC based on low-triangular global coding matrix with ladder-shaped partition is presented, which combines redundant and random network coding for robust H.264/SVC video transmission. Firstly, the error-correcting capabilities of redundant network coding make our scheme resilient to loss. Secondly, the implementation of random network coding at the intermediate nodes with multiple input links can reduce the cost of network bandwidth, thus reducing the end-to-end delay for video transmission. Thirdly, the low-triangular global coding matrix with ladder-shaped partition is maintained throughout the R2NC processes to reduce the impact of global coding matrix's rank deficiency on video transmission and provide unequal erasure protection for H.264/SVC priority layers. The redundant network coding avoids the retransmission of lost packets and improves error-correcting capabilities of lost packets. Based only on the knowledge of the packet loss rates on the output links, the source node and intermediate nodes can make decisions for redundant network coding and random network coding i.e., how much redundancy to add at this node. However, the redundancy caused by redundant network coding makes the network load increases. In order to improve network throughput, we performed random network coding at the intermediate nodes. Our approach is grounded on the overall distortion of reconstructed video minimization by optimizing the amount of redundancy assigned to each layer. The convex optimization model is constructed under the constraint of network coding and scalable video coding. Experimental results are shown to demonstrate the significant improvement of H.264/SVC video reconstruction quality with R2NC over packet lossy networks.