Steady-state analysis of a semi-blind adaptive beamforming algorithm for TDMA signals

We describe an adaptive beamforming algorithm for time- division multiple-access (TDMA) signals that utilizes a modified least-squares (LS) cost function, and analyze its performance using a stochastic model. The beamformer weights are computed via a two-step procedure: initial weights are calculated from the training sequence, and these are refined by a semi-blind algorithm using the modified LS cost function. The main goal of the paper is to analyze this algorithm using a stochastic model and Wiener filter theory for the case when the look-direction vector is mismatched. The performance of the proposed adaptive beamformer is also evaluated using simulated TDMA data.