Comparative analysis of adaptive beamforming algorithm LMS, SMI and RLS for ULA smart antenna

The challenge of a modern day wireless system is to provide reliable and extensive service, which provide the desired capacity for communication. It is necessary to increase the capacity and channel bandwidth at the same time minimize the channel interference. Smart antenna is one of the best techniques to improve the capacity of the wireless communication system by improving the gain of main lobe in a direction of arrival (DOA) and null generation towards the interfere. The smart antenna adaptive algorithms Least Mean Square (LMS) achieve the best weight vector of antenna array elements for beamforming by iterative process. In this paper we analyzed the performance of LMS, Sample Matrix Inversion (SMI), Recursive least square (RLS) algorithms by varying the number of elements in the uniform linear array (ULA), and simulations results are carried out using MATLAB.