Application of Perceptron Model for Adaptive Beamforming in Array Antennas

Abstract-In this paper, a single neuron neural network beamformer is proposed. A perceptron model is designed to optimize the weights of a dipole array antenna to steer the beam to desired directions. The objective is to reduce the complexity by using a single neuron neural network and utilize it for adaptive beamforming in dipole array antennas. The optimized coefficients calculated from the single neuron neural network are compared with the optimized coefficients from the traditional Least Mean Square (LMS) method. Matlab is used to optimize the weights in neural network and LMS method as well as display the comparison in graphical format.