Improved robustness adaptive step size LMS equalization algorithm and its analysis

In order to improve the performance of LMS (Least Mean Square) adaptive filtering algorithm, an improved robustness adaptive step-size LMS equalization algorithm was presented by establishing a nonlinear relationship between the two relevant statistics for step-size factor μ(n) and the error signal e(n). Compared with other algorithms, this algorithm overcomes of sensitivity to the noise coming from outside by introducing the statistics for the correlation of error signal e(n). Meanwhile, this algorithm presents some improvement on the principle of robustness. Theoretical analysis and simulation results indicate that this algorithm has a faster convergence speed and a better steady-state error, and can go back to steady state quickly when the channel is varying with time, which shows a better robustness and convergence than other traditional ones.