Maximum Distance Separable 2D Convolutional Codes
Joan‐Josep Climent, Diego Napp, Carmen Perea, Raquel Pinto · IEEE Transactions on Information Theory · 2015
Maximum distance separable (MDS) block codes and MDS 1D convolutional codes are the most robust codes for error correction within the class of block codes of a fixed rate and 1D convolutional codes of a certain rate and degree, respectively. In this paper, we generalize this concept to the class of 2D convolutional codes. For that, we introduce a natural bound on the distance of a 2D convolutional code of rate k/n and degree δ, which generalizes the Singleton bound for block codes and the generalized Singleton bound for 1D convolutional codes. Then, we prove the existence of 2D convolutional codes of rate k/n and degree δ that reach such bound when n k(((I(δ/k)J + 2)(I(δ/k)J + 3))/2) if k f δ, or n k((((δ/k) + 1)((δ/k) + 2))/2) if k | δ, by presenting a concrete constructive procedure.