Non-Blind Beamforming Generalized Receiver with DOA Estimation in MIMO Wireless Communication Systems

We investigate the generalized receiver (GR) constructed based on the generalized approach to signal processing in noise employing non-blind beamforming algorithms and direction of arrival (DOA) estimation, which is implemented by multiple-input multiple-output (MIMO) wireless communication systems. We compare three non-blind beamforming algorithms, namely, the least mean square (LMS), the recursive least square (RLS), and the sample matrix inverse (SMI) algorithms under GR employment in MIMO wireless communication systems. DOA estimation techniques are applied based on multiple signal classification (MUSIC) and estimation of signal parameters via rotational invariance technique (ESPRIT). We suppose several GR structures employing the above mentioned non-blind beamforming algorithms jointly with DOA estimation procedure. Comparative analysis of simulation results allows us to conclude that the performance curves of GR with considered non-blind beamforming algorithms are very close to each other. Also, simulation results demonstrate superiority in the output signal-to-interference-plus-noise ratio (SINR) under employment of GR with the discussed non-blind beamforming algorithms and DOA estimation in MIMO wireless communication systems in comparison with the correlation receiver that is optimal in the Neyman-Pearson sense if a priori information about the information signal parameters is known. Key-Words: Generalized receiver, non-blind beamforming, direction of arrival (DOA), multiple signal classification (MUSIC), signal-to-interference-plus-noise ratio (SINR), and root-mean-square error (RMSE).