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

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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]


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·


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