Exploiting the implicit error correcting ability of networks that use random network coding

Abstract

In this dissertation, we developed a method that uses the redundant information implicitly generated inside a random network coding network to apply error correction to the transmitted message. The obtained results show that the developed implicit error correcting method can reduce the effect of errors in a random network coding network without the addition of redundant information at the source node. This method presents numerous advantages compared to the documented concatenated error correction methods. We found that various error correction schemes can be implemented without adding redundancy at the source nodes. The decoding ability of this method is dependent on the network characteristics. We found that large networks with a high level of interconnectivity yield more redundant information allowing more advanced error correction schemes to be implemented. Network coding networks are prone to error propagation. We present the results of the effect of link error probability on our scheme and show that our scheme outperforms concatenated error correction schemes for low link error probability.