Generally, Smart antennas combine the antenna array with signal processing capability to optimize automatically the beam pattern in response to the received signal through beamforming. This last is defined as a signal processing technique employing antenna arrays for directional signal transmission or reception. Complex weights are calculated using adaptive beamforming techniques and then multiplied with the user signal to adjust its magnitude and phase and thus to optimize it. This causes the antenna array output to maximize transmission or reception in a particular direction and to minimize the output in other direction. Several adaptive beamforming methods are available in the literature for smart antenna and wireless communication, among them, most popular are the LMS, the Recursive Least Squares (RLS), the Sample Matrix Inversion (SMI) and the Conjugate Gradient Method (CGM) algorithms (Dakulagi & Alagirisamy, 2020). Furthermore, the LMS suffers from certain restriction when applied in some wireless communications due to its slow convergence (Deng et al, 2018).