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Configuring an equalizer involves choosing an adaptive algorithm and indicating your choice when creating an equalizer object in MATLAB. This section includes information that might help you choose an adaptive algorithm. It then describes how to indicate your choice and how to access properties of an adaptive algorithm that you have chosen.
Although the best choice of adaptive algorithm might depend on your individual situation, here are some generalizations that might influence your choice:
The LMS algorithm executes quickly but converges slowly, and its complexity grows linearly with the number of weights.
The RLS algorithm converges quickly, but its complexity grows with the square of the number of weights, roughly speaking. This algorithm can also be unstable when the number of weights is large.
The various types of signed LMS algorithms simplify hardware implementation.
The normalized LMS and variable-step-size LMS algorithms are more robust to variability of the input signal's statistics (such as power).
The Constant modulus algorithm is useful when no training signal is available, and works best for constant-modulus modulations such as PSK.
However, if CMA has no additional side information, it can introduce phase ambiguity. For example, CMA might find weights that produce a perfect QPSK constellation but might introduce a phase rotation of 90, 180, or 270 degrees. Alternatively, differential modulation can be used to avoid phase ambiguity.
Details about the adaptive algorithms are in the references listed in Selected Bibliography for Equalizers.
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