Algorithms of Adaptive Beam Forming for Smart Antenna: A Comparative Study

Abstract

For enhancing data rate Smart Antennas have been gaining prominence in the recent times where the main beam is steered towards direction of interest via phase shifter. The sense behind this development is the availability of high-end processors to handle the complex computations involved. The phase shifting and array weighing can be performed on digital data rather than in hardware is the major advantage of digital beam former. This paper gives comparative study of five adaptive algorithms-Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Sample Matrix Inversion (SMI), Recursive Least Square (RLS) and Conjugate Gradient Method (CGM) for computing the array weights. This adaptive algorithm assures very high rate of convergence & highly reduced mean square error. The weights obtained by the above algorithms are then used to steer the antenna array beam in the direction of interest, thereby enhancing SNR.