A closed-form scaling law for convolutional LDPC codes over the BEC
Pablo M. Olmos, Rudiger L. Urbanke · 2013
We propose a scaling law for the error probability of convolutional LDPC ensembles when transmission takes place over the binary erasure channel. We discuss how the parameters of the scaling law are connected to fundamental quantities appearing in the asymptotic analysis of these ensembles and we verify that the predictions of the scaling law fit well with data derived from simulations over a wide range of parameters.