Symbol Erasure Correction in Random Networks With Spread Codes

We consider data transmission over a network where each edge is an erasure channel and the inner nodes transmit the random linear combinations of their incoming information. We distinguish two channel models in this setting: the row and the column erasure channel model. For both models, we investigate spread codes and determine their symbol erasure correction capability and the probability of decoding success. We also compare the performance of spread codes to other known codes suitable for those models. Furthermore, we explain how to decode these codes in the two channel models and compare the decoding complexities. The results show that depending on the application and the to-be-optimized aspect, any combination of codes and channel models can be the best choice.