Adaptive Algorithms Comparison and Analysis for Beamforming Application in Smart Antenna

In the field of wireless communications effective and authentic usage of spectrum will be an added advantage to achieve the desired capacity for a communication system. So minimizing the interference within the channel would give a greater dominance over the increase of channel capacity and the signal bandwidth. This means that improving the gain in the direction of arrival (DOA) and inserting null values at interference points is critical to increasing the capacities of a radio channels, which is why smart antennas are so important. To get the optimal weight vector of antenna array components for beamforming, adaptive algorithms play a vital role. When antenna elements in a uniform linear array were rearranged, we assessed the performance of three methods: the MATLAB-based Least Mean Square (LMS), the LMF-based LMF, and the LMMN-based LMMN techniques.