Soft Computing Approaches for Two-Dimensional Beamforming

Abstract

Last decade has seen constant growth in wireless technology. Still there is requirement for higher data rates. Current technologies have nearly maximized the use of temporal and spectral techniques to improve capacity and data transfer speeds. But additional spatial dimension is not yet exploited. We can improve capacity of cellular systems by canceling interfering signals using directional arrays. This process is known as beamforming. There are numerous studies available for beamforming mostly using uniform linear arrays but little work has been done on other array configurations. Constrained beamforming techniques with planar array configurations are to be developed for capacity improvement of wireless systems in 3D space. In this work, we have employed the bacterial foraging optimization algorithm (BFOA) and genetic algorithm (GA) for constrained beamforming using uniform planar array and uniform circular arrays.