On the construction of MRD convolutional codes

Abstract

The problem of building optimal block codes, such as MDS codes, over small fields has been an active area of research that led to several interesting conjectures. In the context of convolutional codes, optimal constructions, such as MDS or MDP, are very rare and all require very large finite fields. In this work, we focus on the problem of constructing optimal convolutional codes with respect to the rank distance, i.e., we study the construction of Maximum Rank Distance (MRD) convolutional codes. Considering convolutional codes within a very general framework, we present concrete novel classes of MRD convolutional codes for a large set of given parameters.