Computing information rates of magnetic recording channels in the presence of medium noise

Abstract

An information-theoretic method is presented for computing information rates of magnetic recording channels with medium noise, assuming 0.5-Bernoulli as well as optimized Markov input processes. The method is based on the well-known conjectured Shamai-Laroia bound. The compound behavior of the magnetic recording channel is modelled by combining the Lorentzian read-back pulse, the microtrack channel model, and additive white Gaussian noise (AWGN). Numerical results are provided that show that from an information theoretic viewpoint in certain cases medium noise is preferable to AWGN.