Optimal high-rate convolutional codes for partial response channels

Optimized high-rate convolutional codes are considered as the outer encoder of a serially concatenated structure where the inner encoder is replaced by the magnetic recording channel. Simulation results of the iterative decoding algorithm for an equalized Lorentzian channel model and a more realistic model that includes data-dependent transition noise are presented. The effect of precoder on performance is also studied, and simulation results are supported by EXIT chart analysis. All results refer to a comparison of the optimized codes with previously proposed schemes employing punctured codes or non optimized unpunctured codes with tail-biting decoding. Both trellis termination and tail-biting termination of the high-rate codes are studied. To terminate the code trellis we use the method derived by Amat, Montorsi and Benedetto, which only requires ν (the code memory) tail-biting bits. Simulation results confirm the ML analysis: owing to their better distance properties, the scheme based on the new codes outperform state-of-the-art magnetic recording schemes based on both punctured and non optimized high-rate codes. The cost of using an unpunctured code versus the punctured one in terms of increased decoding complexity is turned into an advantage by applying to the high-rate code the soft-input soft-output (SISO) algorithm working on its dual trellis.