ADAPTIVE BEAMFORMING ALGORITHM FOR SMART ANTENNA SYSTEM IN MOBILE NETWORK

Abstract

As the growing demand for wireless communications is constantly increasing, the need for better coverage, improved capacity, and higher transmission quality rises. One of the promising technologies is the use of smart antenna system. Smart antennas combine the antenna array with signal processing capability to optimize automatically the beam pattern in response to the received signal through beamforming. The purpose of this thesis work is to investigates Adaptive beamforming algorithms for optimum weight computation. Afterward, developing and possibly implementing an adaptive beamforming algorithm in the mobile communication environment to enhance service quality and capacity. The strategy used to achieve the major aim was an in-depth investigation of Two adaptive algorithms, the Least Mean Square (LMS) and the Sample Matrix Inversion (SMI). The Simulation results provided showed that the beam steering ability and nullifying capability was satisfactory for those algorithm, and (LMS) algorithm had slow convergence rate beside simplicity, (SMI) on the other-hand had fast convergence rate but suffering from computational complexity. So a Matrix-Inversion Least Mean Square (MI-LMS) adaptive algorithm was proposed and developed, which combines (SMI) and (LMS) to improve the convergence speed. Simulation results revealed that the MI-LMS algorithm provides remarkable improvements in terms of interference suppression and convergence rate over LMS and SMI. Furthermore, The effects of varying the array parameters have been analyzed and investigated. Finally, a simulation scenario was presented for verifying the Spatial Division Multiple Access (SDMA) concept.