An Overview of Compressing Sensing Techniques for Fast and Accurate NF Test

Compressive Sensing (CS) has been deployed in a variety of fields including wideband spectrum sensing, active user detection and antenna arrays. In massive MIMO arrays, CS has been applied to reduce the number of measurements required to verify the arrays excitation in a production environment. All follow the general approach of creating the sparsity needed for CS by subtracting the measured far-field or near-field of the test array from that of a ‘gold standard’ array measured under identical conditions. In our initial work the reconstruction of array excitation with a mean square error (MSE) of −30dB was achieved for a 20×28 element array antenna at half wavelength spacing using just 1.5% (177 samples) of the samples needed for a conventional NF measurement (12,100 samples) employing back projection to the aperture. Critical to the performance is the realization that the CS samples need to be confined to the central region of the NF measurement plane which for a conventional NF to FF planar antenna pattern measurement would offer a massive truncation error. This webinar addresses the optimal sampling strategy needed for this NF approach and presents a statistical performance analysis of the reconstruction accuracy.