  While random linear network coding is a powerful tool for disseminating
information in communication networks, it is highly susceptible to errors
caused by various sources. Due to error propagation, errors greatly deteriorate
the throughput of network coding and seriously undermine both reliability and
security of data. Hence error control for network coding is vital. Recently,
constant-dimension codes (CDCs), especially K\"otter-Kschischang (KK) codes,
have been proposed for error control in random linear network coding. KK codes
can also be constructed from Gabidulin codes, an important class of rank metric
codes. Rank metric decoders have been recently proposed for both Gabidulin and
KK codes, but they have high computational complexities. Furthermore, it is not
clear whether such decoders are feasible and suitable for hardware
implementations. In this paper, we reduce the complexities of rank metric
decoders and propose novel decoder architectures for both codes. The synthesis
results of our decoder architectures for Gabidulin and KK codes with limited
error-correcting capabilities over small fields show that our architectures not
only are affordable, but also achieve high throughput.
