An Insight into Adaptive Elliptical and Hexagonal Arrays Synthesis using Normalized Fractional Least Mean Squares Algorithm

Background: Over the last two decades the use of adaptive arrays in wireless industry has seen a rapid growth. Smart antennas have the capability of ability to direct its main beam towards the desired user and supress nulls at the same time. Methods: In this paper, two different arrays namely elliptical and hexagonal arrays are considered. Four stochastic gradient based algorithms; Least Mean Squares (LMS), Fractional Least Mean Squares (FLMS), Normalized Least Mean Squares (NLMS) and Normalized Fractional Least Mean Squares (NFLMS) are evaluated. Findings: From the results conducted it is shown that hexagonal array using Normalized Fractional Least Mean squares algorithm as the weighting scheme provide optimum results in terms of side lobe reduction and more precise main beam direction when compared to the other array configuration taken into consideration. Applications: Smart antennas increase signal range, suppress the interfering signals to a minimum range which provide greater advantage in wireless systems.