Modeling thin-film storage channels

A straightforward method for modeling nonlinearity and data-dependent (transition-dependent) media noise in a thin-film storage channel is presented. The least-squares approach for measuring the channel linear pulse response is described, and this FIR (finite impulse response) channel model is contrasted with a nonlinear moving average modeling technique described in terms of a random-access memory used as a finite state machine (FSM). It is shown that the channel nonlinearity is largely trailing in time, and performance figures of modeling accuracy for the channel FSM are presented. The nonlinear distortion increased dramatically at higher data rates for the thin-film disk examined. In addition, the variation of the channel noise power according to the flux transition density is described. A jitter noise effect is identified. A FSM modeling technique for identifying this noise power variation as a function of the channel input data pattern is given. Finally, it is shown how to combine these two modeling techniques to create arbitrarily long, representative read signals for the thin-film disk. By using these compact channel models, one can easily test new coding or equalization techniques