Title :
A signal-dependent autoregressive channel model
Author :
A. Kavcic;A. Patapoutian
Author_Institution :
Div. of Eng. & Appl. Sci., Harvard Univ., Cambridge, MA, USA
Abstract :
A fast and accurate channel model is presented that captures intersymbol interference, signal non-linearities and signal-dependent noise correlation. The noise is modeled as the output of a signal-dependent autoregressive filter. This channel model is well suited for detector designers who desire realistic simulators with short run-times.
Keywords :
"Gaussian noise","Filters","Parametric statistics","Statistical distributions","Intersymbol interference","Detectors","Computational modeling","Runtime","Stochastic resonance","Signal processing"
Journal_Title :
IEEE Transactions on Magnetics
