The Finding of the Defects of an 6G Array Antenna Using Deep Learning Programs

This paper talks about a measure to hinder people from wasting resources of developing the wireless communication system by applying deep learning approaches. As the array antenna is essential but costly to the 6G mobile communication device, no single flaw is not allowed in its manufacturing as well as design, which leads them to checking a flaw or some in its geometry. A measure is taken to comb through the pixels of the array antenna and will tell you attributes of the physical error interpreted by the deep learning algorithms. The electromagnetic characteristics will entail the information of the classes of the defects. An 8-by-8 array working for 28 GHz is taken an instance of and the corresponding far-field patterns will be presented with technical comments.