# Planar Array Diagnostic Tool for Millimeter-Wave Wireless Communication Systems
## 1 Introduction  
Antenna array is a key technology component in various communication systems such as radar, radio-astronomy, remote sensing, satellite communications, and next-generation (fifth generation, 5G) wireless communications [1], where a very large number (in the hundreds) of radiating elements are particularly used to meet the increasing demands of high radiation performance andreconfigurability [2]. Conversely, the higher the number of radiating elements in the beam-forming configuration, the higher the probability of failed element(s) will be. This causes abrupt field variations across the aperture of the array, and distortion in the radiation features (e.g., beamwidth, peak sidelobe, and boresight). Therefore, the availability of reliable and effective diagnosis tools for large arrays remains an asset, because manual dismantling and replacement operations consume excessive time and cost, and are even unfeasible in satellite-borne installations. Currently, failure identification in antenna arrays is a theoretical and practical important research domain. Detection of faulty elements in antenna arrays is of great interest in both military and civilian markets. Upcoming technologies adopt active or passive antenna arrays with a large number of elements [1; 2; 3; 4; 5]. For instance, millimeter-wave transceivers implement multiple-input multiple-output (MIMO) features and beamforming for future 5G applications, as shown in Figure 1. The block diagram shows the location of the AWMF-0108 in a 5G MIMO system [6]. The integrated circuit (IC) contents in the circle are the gain and phase control blocks with amplification and RX/TX switching. The first industrial and commercial millimeter-wave quad-core IC transceiver for 5G applications is the AWMF-0108 [6]. Many compactable antennas were designed for that purpose. Thus, some communication systems will evolve for 5G technology, even before full deployment, which is not expected until 2020. The large number of elements in the planar antenna required by the transceiver must function optimally. Failure in the element(s) causes far-field degradation of antenna systems. The detection of failed elements from field measurements taken from a suitable observation point is very important to re-calibrate the feeding network and to reinstall the needed radiation characteristics by reconfiguring the excitations of the healthy elements [1; 3]. Testing of antennas is then a necessity when a certain number of elements exhibit fault. Therefore, the fast diagnosis of complex antenna structures is always a fundamental need. Far-field measurements are a very powerful approach for antenna array testing. The measurement data are sequentially presented for probable failure identification in the array under test (AUT). The matrix method algorithm (MMA) and back propagation algorithm (BPA) are the most commonly used mechanisms to detect the number and corresponding positions of defective elements using a reference antenna (healthy) and the AUT (defective). BPA [7] was established using the Fourier relationship between radiated far-field and the field situated on the array aperture, and it is applicable to planar antenna arrays. A generalized form of BPA is MMA [8; 9]. MMA uses linear algebra standard tools to stabilize the inversion matrix, which relates the array aperture field to radiated far-field. However, MMA and BPA demand a large number of measurements, thus causing long post-processing of large arrays. One approach to mitigate the problem is the use of a priori knowledge of the array without failure; consequently, only the defective array elements are identified. The modeled diagnostic problem is solved by employing available customs whose computation time is a little longer than standard methodologies. At this point, it is evident that the total time taken to get the antenna array diagnosed greatly depends on measurement time, with post-processing times having a higher order of magnitude.