Low-Complexity Combined Approximate DFT and Adaptive Beamformer for Extremely Large Arrays

Discrete Fourier Transform (DFT) based beam-formers provide N beams with a uniform linear array having N antennas. Despite low-complexity, DFT beamformers cannot generate deep nulls at arbitrary directions of arrivals (DOAs) in the beam pattern to attenuate interferences. On the other hand, data-dependent adaptive beamformers can achieve deep nulls at arbitrary DOAs, however, at higher complexity due to an inversion of a matrix in deriving optimum weights. In this paper, we propose a combined approximate DFT (ADFT) and adaptive beamformer for a uniform linear array consisting of P subarrays, each consisting of M antennas. Here, we first employ P ADFT beamformers to process signals received by subarrays, and the P outputs of these subarrays are then processed by an adaptive beamformer. Simulation results confirm that the proposed beamformer provides the benefits of both DFT and adaptive beamformers. Furthermore, we present preliminary results of an experimental antenna array operating at 5.75 GHz, where a Howells-Applebaum beamformer is employed as the adaptive beamformer.