Optimizing beam pattern of adaptive linear phase array antenna using local genetic algorithm

An innovative optimal adaptive antenna technique based on the phase shift perturbation method is proposed. Local genetic algorithms are used to search the optimal weighting vector of the phase shift perturbations for array factor. The design for an optimal radiation pattern of an adaptive antenna can not only adjustably suppress interferers by placing nulls at the directions of the interfering sources but also provide a maximum main lobe in the direction of the desired signal at the same time, i.e., to maximize the signal to interference ratio (SIR). In order to achieve this goal, a new convergent method referred as the two-way convergent method for local genetic algorithms is proposed. The local genetic algorithm combines genetic algorithm and local search heuristics to solve combinatorial optimization problems. The local genetic algorithm is a kind of an improved type of the traditional genetic algorithm. It can make the stopping criteria reasonable and can avoid the shortcomings of the traditional genetic algorithm whose stopping criteria are set up by using the trial and error method. The optimal radiation pattern can be used in practical wireless communication.