On the design of complex-valued spreading sequences using a genetic algorithm

We investigate the design of complex-valued spreading sequences with respect to a combination of different correlation properties. The two classes of complex sequences considered are the Oppermann sequences, which offer a wide range of correlation properties, and the modified Walsh-Hadamard sequences, which have been shown to offer good correlation properties. Since the number of parameters for the optimization problem is large, especially for the modified Walsh-Hadamard sequences, it is difficult if not impossible to use global optimization methods for solving such problems. Thus, we propose to transform the problem with continuous variables to another problem with discrete variables. This problem can then be solved efficiently using a genetic algorithm. These types of algorithms have been successfully applied in various areas, such as neural networks; however, to the authors best knowledge, their use for the design of complex spreading sequences has been rather sparse.