A genetic algorithm (GA) based blind equalization method is presented for joint channel and data estimation. The GA is an optimization technique using natural selection and evolutionary processes that searches for solutions of the problem through phases of evaluation, reproduction, crossover, and mutation repeatedly. The most important advantages of these algorithms are parallel search capability, convergence to global optimum, and reduced problem-dependence. Different schemes for each of above phases have been considered in achieving better results.
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This manuscript is available at http://ieeexplore.ieee.org/ and may be cited as: Caimi, F. M., & Wang, D. (1999). Joint channel and data estimation: genetic algorithm based blind equalization. Oceans'99 MTS/IEEE: Riding the crest into the 21st century. (Vol. 2, pp. 931-937). Washington, DC: Oceans'99 MTS/IEEE Conference Committee. doi:10.1109/OCEANS.1999.804998
Florida Atlantic University. Harbor Branch Oceanographic Institute contribution #1311.