Implementation of dual-band Planar Inverted F- Antenna (PIFA) using machine learning (ML) for 5G mobile applications

. This paper proposed a new hybrid model for feeding printed PIFA antennas with the dual frequency ranges of 29GHz and 32GHz, which are optimal for 5G mobile communications. A two-element rectangular PIFA with an inset feed for the 29GHz and 32GHz bands is the first prototype in this initiative.To create The second program involves PIFA inset-fed lines and is symmetric dual-band two-element slotted rectangular patches. Inverted I-shaped slots in primary patches could be used to gain dual-band response. For 5G portable apps, hybrid algorithms are used.Bayesian convolution and the genetic algorithm are the two algorithms. These two algorithms are useful for wireless 5G applications. The third prototype is an asymmetric PIFA antenna with inverted I-shaped slotted perpendicular patches in dual service. The partial rectangular ground plane is inserted with the slot-formed DGS. The substrate has a width of 52074mm2, and the integrated antennas have very limited planar configurations occupy hardly any room, making them easier to fit into handset devices for the upcoming 5G mobile communications. Return demand drops, and bandwidths are diminished.Without any supplementary constructions, PIFA has a small mutual coupling. By using these two algorithms the antenna systems have directivity, gain, and providing effective values that are perfect for 5G mobile applications, as well as expected reflections and interactive application characteristics.