Compressive Sensing for Millimeter Wave Antenna Array Diagnosis

TL;DR

This paper introduces two compressive sensing-based techniques to diagnose blockages in millimeter wave antenna arrays, effectively identifying faulty elements with fewer measurements by jointly estimating blockage locations and effects.

Contribution

It presents novel compressive sensing methods for array diagnosis that improve fault detection efficiency in millimeter wave antennas affected by environmental blockages.

Findings

Accurately detects blocked antennas with fewer measurements.

Effectively estimates blockage-induced attenuation and phase shifts.

Reduces diagnosis time compared to traditional methods.

Abstract

The radiation pattern of an antenna array depends on the excitation weights and the geometry of the array. Due to wind and atmospheric conditions, outdoor millimeter wave antenna elements are subject to full or partial blockages from a plethora of particles like dirt, salt, ice, and water droplets. Handheld devices are also subject to blockages from random finger placement and/or finger prints. These blockages cause absorption and scattering to the signal incident on the array, and change the array geometry. This distorts the far-field radiation pattern of the array leading to an increase in the sidelobe level and decrease in gain. This paper studies the effects of blockages on the far-field radiation pattern of linear arrays and proposes two array diagnosis techniques for millimeter wave antenna arrays. The proposed techniques jointly estimate the locations of the blocked antennas and the induced attenuation and phase shifts. Numerical results show that the proposed techniques provide satisfactory results in terms of fault detection with reduced number of measurements (diagnosis time) provided that the number of blockages is small compared to the array size.