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Equation 3.42 could be made dominant most of the time, while the measurement model of Equation 3.43 fine tuned the estimate in order to provide a more accurate CIR estimate. This scenario occurred, when a so-called decision directed mechanism was invoked, where the coefficients of the DFE were adapted based on the past detected symbols. In other words, the CIR variations throughout the entire frame and not just during the training period were tracked by the algorithm. The performance of the algorithm in this situation was quantified recently by Narayanan et al. [ 1441, Harun et al. [l241 and Shukla et al. [ 1251, where the Kalman algorithm and its variants like the square root Kalman algorithm [ 1351 provided good convergence properties. However, Harun et al. [ 1241 showed that there was little difference in the performance of the Kalman algorithm and the LMS algorithm in this scenario using the assumption of perfect i.e error free decision feedback in order to adapt the equalizer coefficients. As it was shown in Figure 3.16, the performance of the RKCE was superior to that of the RKDFE, even though the complexity of the CIR estimator was lower. However, if the CIR estimator had to adapt throughout the entire transmission frame, the complexity of the DFE coefficient computation portrayed in Figure 3.14 and Table 3.1 1 would grow due to its proportionality to Nf . This would offset the complexity advantage of the RKCE. In the next chapter, we will investigate the employment of adaptive modulation in a narrow-band [l451 and widebandchannelenvironment. In the narrow-band environment, the application of power control techniques will be implemented in the context of adaptive modulation and we will also explore the utilization of equalization techniques in conjunction with adaptive modulation in a dispersive i.e wideband channel environment. barcode font for word 2007 free download Barcode labels in Microsoft Word 2016, 2013, 2010, or 2007 Mail ...
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