A Comparative Study of Optimization Techniques in Adaptive Antenna Array Processing: The Bacteria-Foraging Algorithm and Particle-Swarm Optimization

This paper presents a comparative study between the Bacteria-Foraging (BF) and Particle-Swarm Optimization (PSO) algorithms, and their application to the antenna-array optimization problem. The performance of the Bacteria-Foraging Algorithm is studied by varying its different parameters in beamforming and null-steering problems. Null steering along with sidelobe suppression is also done for various degrees of complexity. A generic cost function is developed, the parameters of which can be controlled to meet the requirements of the particular application. The two algorithms are compared for null depth, average sidelobe level, and rate of convergence for different numbers of interference signals. The performance of these methods are compared for output noise power for the same noise inputs. Results are shown for a linear dipole antenna-array system.