Adaptive Beamforming Approach with Robust Interference Suppression

Abstract

Array antennas which are smart enough to distinguish between the desired and interference signal are nothing but Smart Antennas. They work on Space Division Multiple Access and are used in mobile communication to increase the capacity of communication channels. DOA and Beamforming together make a Smart Antenna. We shall restrict our discussion to Beamforming. This paper explains the Variable Step Size Normalized Least Mean Square (VSSNLMS) method to direct the main beam towards the desired user. We shall take into consideration, the already existing algorithms for beamforming such as Sample Matrix Inverse (SMI) and Least Mean Square (LMS) in order to compare the performance level of the new algorithm. However the weight expression of the SMI algorithm involves inversion of the array correlation matrix and the LMS algorithm enters damped modes, both of which are highly undesirable. To overcome this, a new approach for adaptive beamforming called VSSNLMS is introduced. With the help of simulation results, it can be proved that the VSSNLMS approach converges faster than SMI and LMS along with reduced noise and better interference suppression. The Simulation tool used is Matrix Laboratory.