Adaptive algorithms in smart antenna beamformation for wireless communication

The challenges for today's wireless communication technology are increased data rates, channel capacity and spectrum efficiency with reduced interference. The adaptive antenna array is capable of adapting to the varying signal environments automatically and forms beams in the directions of the desired signals by steering nulls in the directions of interfering signals. Therefore smart antenna is the best solution to overcome the above mentioned challenges. Smart antennas uses advanced digital signal processing algorithms to enhance the detection of desired users in an interfering environment through spatial filtering. In this paper we will discuss the influence of Least Mean Squares (LMS), Recursive Least Squares (RLS) and Normalized Least Mean Square (NLMS) algorithms in adaptive beamforming. The simulations used for the study are carried out using MATLAB R2013a.