Let us implement an adaptive equalizer based on the LMS algorithm given in (6.6.25). The channel…

Let us implement an adaptive equalizer based on the LMS algorithm given in (6.6.25). The channel number of taps selected for the equalizer is 2K + 1 = 11. The received signal-plus-noise power PR is normalized to unity. The channel characteristic is given by the vector x as

x = [0.05 – 0.063 0.088 – 0.126 – 0.25 0.9047 0.25 0 0.126 0.038 0.088]

sol:

The convergence characteristics of the stochastic gradient algorithm in (6.6.25) are illustrated in Figure 6.34. These graphs were obtained from a computer simulation of the 11-tap adaptive equalizer. The graphs represent the MSE averaged over several realizations. As shown, when ∆ is decreased, the convergence is slowed somewhat, but a lower MSE is achieved, indicating that the estimated coefficients are closer to Copt·