| |
| The convergence rate of the traditional LMS algorithm for adaptive beamforming is highly dependent on the eigenvalue-structure of the correlation matrix of the signals arriving at the antenna array elements. A poor eigenvalue-structure of the correlation matrix will lead to a bad convergence. In this paper, we applied self-orthogonalizing transform - the Karhunen-Loeve Transform (KLT) to the input signal vector before feeding it into the LMS algorithm, analyzed the influencing factors of the eigenvalue -spread of the correlation matrix, and compared the KLT-LMS algorithm with the traditional LMS algorithm. The simulation results illustrate that the convergence rate of the self-orthogonalizing algorithm is independent of the eigenvalue-structure of the correlation matrix and the KLT-LMS algorithm outperforms the traditional LMS algorithm. |
|
| Keywords:Wireless communication, array antennas, adaptive beamforming, KLT-LMS algorithm |
|
