Robust Beamforming Algorithms for Smart Antenna Systems.

In this paper, the performances of well-known adaptive beamforming algorithms, namely, Sample Matrix Inversion (SMI) and Least Mean Square (LMS), are analyzed. From the simulation results, it is observed that for SMI, as the number of user increases the main lobe spreads in all directions. As a result, beamforming in the user direction may not be correct. To overcome this, LMS algorithm can be used. The LMS algorithm is the best choice in most of the commercial wireless applications due to its low complexity. 5G and beyond 5G networks require beamforming algorithms with high directivity and fast convergence rate. Hence, in this paper, LMS algorithm is modified to improve the convergence rate. Furthermore, improved LMS algorithms are applied to horizontal - vertical Uniform Linear Array. This is also called 2D-ULA. These improved LMS algorithms are called 2D-LMS 1 and 2D-LMS 2. The main drawback of LMS algorithm is its low convergence rate; because of this, LMS algorithm may not track the desired signal when the signal conditions are changing rapidly. Simulation results show that the proposed 2D-LMS 1 and 2D-LMS 2 algorithms have improved convergence rate, higher directivity, low complexity and fast execution time as compared to conventional LMS algorithm. Hence, the proposed algorithms are best suited for 5G and beyond wireless communications. [ABSTRACT FROM AUTHOR]