Recursive least mean square algorithm for linear antenna array optimization for beamforming using genetic algorithm

A smart antenna is actually a fusion of an array that changes individual antenna elements patterns in response of a dedicated signal to improve performance. Moving one step beyond of beam forming is adaptive algorithm which allows for the computation of continuously amend weights. The process of adaptation must satisfy a specified optimization principle. In this project two Adaptive algorithm Least Mean Square and Recursive Least Mean Square are implemented to revamp beam. Added optimization of beam is accomplished with the help of genetic algorithm which makes beam more optimize. This optimization method is used for the synthesis of antenna array radiation pattern in adaptive beam forming. The optimum value of weights of each antenna element is determined which produces a radiation pattern with minimum side lobe level. Analysis is being carried out with varying different element and space in between element to obtain the minimum weight with the help of genetic algorithm. This improves the performance to achieve the maximum reduction in side lobe level (of the order -20dB) with minimum function calls.