Title :
Blind equalization and identification of nonlinear and IIR systems-a least squares approach
Author :
Raz, Gil M. ; Van Veen, Barry D.
Author_Institution :
Lincoln Lab., MIT, Lexington, MA, USA
fDate :
1/1/2000 12:00:00 AM
Abstract :
A deterministic approach to blind nonlinear channel equalization and identification is presented. This approach applies to nonlinear channels that can be approximately linearized by either finite memory, finite-order Volterra filters, or by a finite number of finite memory nonpolynomial nonlinearities. Both the nonlinear equalizers and the linearized channels are identified. This method also applies to blind identification of linear IIR channels. General conditions for existence and uniqueness are discussed, and numerical examples are given
Keywords :
IIR filters; blind equalisers; identification; least squares approximations; nonlinear filters; IIR systems; blind equalization; blind identification; blind nonlinear channel equalization; deterministic approach; existence; finite memory finite-order Volterra filters; finite memory nonpolynomial nonlinearities; identification; least squares; linear IIR channels; linearized channels; nonlinear systems; uniqueness; Blind equalizers; Convolution; Deconvolution; Finite impulse response filter; Gas insulated transmission lines; IIR filters; Least squares approximation; Least squares methods; Linear approximation; Nonlinear systems;
Journal_Title :
Signal Processing, IEEE Transactions on