On benefits of vector network coding

In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying them with L × L coding matrices that play a similar role as coding coefficients in scalar coding. Vector network coding generalizes scalar coding, and thus offers a wider range of solutions over which to optimize. This paper starts exploring the new possibilities vector network coding can offer along two directions. First, we propose a new randomized algorithm for vector network coding. We compare the performance of our proposed algorithm with the existing randomized algorithms in the literature over a specific class of networks. Second, we explore the use of structured coding matrices for vector network coding. We present deterministic designs that allow to operate using rotation coding matrices and thus result in reduced encoding complexity.