Smart antennas by using LMS and SMI algorithms reduces interfernce
Suraya Mubeen, A. Mallikarjuna Prasad, A. Jhansi Rani · 2016
LMS (least mean square) and the SMI (sample matrix inversion) algorithms are presented for the interference rejection of adaptive array antennas. Interference rejection is achieved by optimally determining the array weights. LMS algorithm, which is based on the steepest-descent method, is the most common technique used for continuous adaptation. SMI algorithm based on an estimate of the correlation matrix is a method of directly calculating the antenna array weights. Performance results of LMS and SMI algorithms are investigated and given for different interference angles, step size of LMS, block size of SMI and interference-to-noise ratios (INRs) for a three elements uniformly spaced linear array.