Constantin Michael Melas

Performance and error propagation of two DFE channels

We compare performance and error propagation of DFE with and without a d=1 RLL code, at 2.67 user density and with a single coefficient FIR phase equalizer. Performance without error propagation is slightly better with d=1 in spite of the rate loss, because precursor ISI can be completely eliminated. We develop a model to estimate the effects of error propagation for both d=0 and d=1. The model is in good agreement with a 20 db SNR simulation. For an overall error rate of 10/sup -6/, the probability of a burst of length 50 in the decoded data is 10/sup -13/ for d=1 and 10/sup -8/ for d=0. This large difference is due both to the higher code rate and to the larger postcursor cancellation for d=0. In the model, we rigorously compute burst error probabilities using a Markov chain derived from our channel assumptions. We also use the model to compute the decay rate of the burst error probability and to identify the set of infinitely propagating sequences. In the simulations, we use random data and a commonly used (1,7) code for DFE17, to which we added AWGN noise at SNR 20 db. Finally, we compare the results of the model with the simulations.

Enhanced linear interpolation for low sampling rate asynchronous channels

Linear interpolation can be used to recover synchronous samples from asynchronous ones, replacing PLO hardware with a digital algorithm. With Enhanced Linear Interpolation, (ELI), computing additional samples midway between existing samples effectively doubles the sampling frequency. Linear interpolation is then used between the asynchronous samples and midpoint samples. The interpolation error is computed as a function of input waveform parameters, sampling frequency, and midpoint interpolator parameters, for both synchronous and asynchronous channel equalization. ELI allows the sampling rate to be below the bit rate.

Asynchronous equalization in magnetic linear tape systems with the data set separator sequence (DSS)

A method of equalization using a data sequence always present on tape is described. This data sequence is part of the standard LTO format. The equalizer calculation is based on the Levinson Toeplitz matrix inversion method and utilizes cosine pulse symmetrization to achieve results independent of the target-signal phase delay.

Performance And Error Propagation Of Decision Feedback Channels

DFE channels can compensate for nonlinearities inherent in magnetic recording [I]. However, because they use past binary decisions in the detection process, incorrect decisions may propagate, and could increase channel cost by requiring more extensive ECC. We compare the performance of the standard DFE channel with the DFE17 channel using a 1,7 Run Length Limited code [21 [31. We estimate the error burst probability resulting from propagation for both channels, based on both modeling and simulation results.