Adaptive Beamforming Method based on Constrained LMS Algorithm for Tracking Mobile User

In this paper, Constrained Least Mean Square (CLMS) algorithm for narrowband adaptive beamforming for tracking mobile user in a 2D urban environment has been used. This algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. The capability of the smart antenna systems to track the user with the main lobe and interference with the nulls creates a significant impact on the current and future wireless sensor networks. The adaptability of the algorithm is closely observed for uniformly spaced linear array. Simulation results indicate that adaptive beamforming method is able to considerably increase the Signal to Interference plus Noise Ratio (SINR) of mobile user in comparison with the ordinary Equal Sectoring (ES) method.