Performance Comparison of ZF, LMS and RLS Algorithms for Linear Adaptive Equalizer

For high speed data communication, extracting true data from the noisy transmitted data corrupted with inter-symbol interference (ISI), equalizers are a necessary component of the receiver architecture. Adaptive algorithms have been extensively used in communication signal processing. The recent digital communication systems need equalizers with a fast converging rate, that cannot be met by conventional adaptive filtering algorithms. ZF and LMS are widely used due to their simplicity and robustness, but fail to complete convergence criteria. RLS exhibit better performances, but is complex and unstable, and hence avoided for practical implementation. This paper analyses the performance of ZF, LMS and RLS algorithms for linear adaptive equalizer.