Rank Deficient Decoding of Linear Network Coding

摘要

Network coding is a new paradigm of communication networks that promises advantages in throughput, robustness, and complexity. Since the fundamental premise of linear network coding is that transmitted data packets are subject to linear combinations, for all network coding schemes so far, a full rank of received packets is required to invert the linear mapping so as to recover the transmitted data packets. This requirement unfortunately results in a key drawback of network coding: either all the packets (or bits) in a session are recovered simultaneously or none can be recovered. Aiming to overcome this all-or-nothing property, leading to long delays and low throughputs. This work proposes a variety of rank deficient decoders of linear network coding. To this end, two classes of rank deficient decoders are proposed. Both classes of decoders recover data from fewer received packets and hence achieve higher throughputs and shorter delays than the full rank decoder.