Prediction-based Blind Equalization with Encoded Input Sequences

A blind equalizer attempts to compensate the inter-symbol interference caused by a communication channel without the knowledge of the transmitted sequence. Linear prediction-error lters (PEF) can be used to obtain the equalized symbols. These equalizers are derived assuming a white information sequence. In real communication systems, channel encoding is commonly used to enable the detection and correction of symbol errors. It is interesting to study the eeect of coding on the performance of the equalizers. A linear block code and a convolutional code are used in simulations and the results are compared to the results obtained for an unencoded white information sequence. Both the mean square error (MSE) and the symbol error rate (SER) are considered.