  Future services demand high data rate and quality. Thus, it is necessary to
define new and robust algorithms to equalize channels and reduce noise in
communications. Nowadays, new equalization algorithms are being developed to
optimize the channel bandwidth and reduce noise, namely, Blind Channel
Equalization. Conventional equalizations minimizing mean-square error generally
require a training sequence accompanying the data sequence. In this study, the
result of Least Mean Square (LMS) algorithm applied on two given communication
channels is analyzed. Considering the fact that blind equalizers do not require
pilot signals to recover the transmitted data, implementation of four types of
Constant Modulus Algorithm (CMA) for blind equalization of the channels are
shown. Finally, a comparison of the simulation results of LMS and CMA for the
test channels is provided.
