Beam array optimization for smart antenna systems using stochastic algorithms

Beam forming systems using adaptive array antennas are a viable solution to a number of problems in applications related to mobile communications. Genetic Algorithms and Particle Swarm Optimization have been extensively used in electromagnetic optimization and antenna design problems. In this paper two smart antennas are investigated, with the purpose to determine the appropriate configuration for each element of the array. The directional patterns of the antenna arrays vary as well as the corresponding geometry; a linear array, composed of 16 elements, for a base station application and a planar uniform circular array (PUCA) composed of 18 radiators. The synthesis problem addressed is to find spatial and feeding configuration of the radiators that conform to certain design constraints. Synchronous GA and PSO algorithms have been utilized to perform beam array optimization for the smart antenna systems. Their efficiency is evaluated on the basis of convergence to the optimal solution for the corresponding problem and convergence speed. The proposed methodology is very flexible allowing the incorporation of additional factors as coupling characteristics.