Abstract
Adaptive digital beamforming is widely used in modern radar and wireless communication systems. Evolutionary algorithms (EA) are powerful tools for more flexible adaptive beamforming. The major drawback of conventional evolutionary algorithms is generally slow in searching for solutions. Bat Algorithm (BA) is a relatively new and faster evolutionary algorithm. In this paper we apply Bat algorithm in adaptive beamforming and also compared its computational efficiency with that of Particle Swarm Optimization (PSO) algorithm which is considered much faster than Genetic Algorithms (GA). Numerical experiments show BA is very efficient, showing a promising tool for adaptive beamforming.
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