Adaptive Equalizers
Krzysztof Wesołowski · 2003
Abstract The paper considers the problem of adaptive equalization. After introduction of the system model and explanation of the phenomenon of intersymbol interference observed on many communication channels, the equalizer structures and algorithms are classified. Then, linear equalizers are considered, concentrating on Zero‐Forcing (ZF), Mean Square Error (MSE) and Least Squares (LS) adaptation algorithms. Subsequently, the choice of a reference signal and fast linear equalizers using periodic test signals are described. Next, the symbol‐spaced equalizer with the fractionally‐spaced equalizer is compared, showing performance superiority of the latter. The operation of the decision feedback equalizer (DFE) is explained in the next section. Subsequently, more complicated than a DFE, non‐linear equalization structures are described such as those based on the Maximum a Posteriori Probability (MAP) symbol‐by‐symbol detection and the Maximum Likelihood (ML) sequence estimation. Equalizers for trellis‐coded signals are also considered. The last part of the paper is devoted to blind adaptive equalizers and their algorithms. The Bussgang algorithms, the algorithms using the second‐order statistics of the received signal and the probabilistic algorithms are shortly characterized.