On the left primeness of some polynomial matrices with applications to convolutional codes

Maximum distance profile (MDP) convolutional codes have the property that their column distances are as large as possible for given rate and degree. There exists a well-known criterion to check whether a code is MDP using the generator or the parity-check matrix of the code. In this paper, we show that under the assumption that [Formula: see text] divides [Formula: see text] or [Formula: see text] divides [Formula: see text], a polynomial matrix that fulfills the MDP criterion is actually always left prime. In particular, when [Formula: see text] divides [Formula: see text], this implies that each MDP convolutional code is noncatastrophic. Moreover, when [Formula: see text] and [Formula: see text] do not divide [Formula: see text], we show that the MDP criterion is in general not enough to ensure left primeness. In this case, with one more assumption, we still can guarantee the result.

Complete MDP convolutional codes

Maximum distance profile (MDP) convolutional codes have the property that their column distances are as large as possible. It has been shown that, transmitting over an erasure channel, these codes have optimal recovery rate for windows of a certain length. Reverse MDP convolutional codes have the additional advantage that they are suitable for forward and backward decoding algorithms. Beyond that the subclass of complete MDP convolutional codes has the ability to reduce the waiting time during decoding. The first main result of this paper is to show the existence and genericity of [Formula: see text] complete MDP convolutional codes for all code parameters with [Formula: see text] as well as that complete MDP convolutional codes cannot exist if [Formula: see text]. The second main contribution is the presentation of two concrete construction techniques to obtain complete MDP convolutional codes. These constructions work for all code parameters with [Formula: see text] but require that the size of the underlying base field is (sufficiently) large.