LMS Algorithm for Blind Adaptive Nonlinear Compensation

This paper presents low-complexity blind adaptive nonlinear compensation algorithms for bandlimited signals. The new algorithms utilize highpass filtering to extract the out-of-band signal energy caused by nonlinear distortion. A least-mean-square (LMS) algorithm and its normalized version are derived based on minimization of the square of the extracted out-of-band signal without access to the original input signal or prior knowledge of the nonlinearity. In this sense the developed algorithms are "blind" and only require prior knowledge of the signal bandwidth. Unlike the Pth-order power series inverse, the proposed nonlinear compensation method is not affected adversely by large input amplitudes. The effectiveness of the online algorithms is illustrated with several simulation examples.