Positioning of UAV Base Stations Using 5G and Beyond Networks for IoMT Applications

5G and Beyond 5G networks (B5G) face the greatest obstacle to ensure accessibility with all categories of users. A significant part of the emerging wireless networks will greatly facilitate connectivity, and cooperation in high-speed communications from Unmanned Aviation Vehicles (UAVs) is expected. UAV has excellent features such as versatile delivery, simple line of sight (LOS) connecting, gradual independence and connectivity architecture speeds, and fixed framework communication systems. Given that many UAVs can achieve specific coverage for surface user terminals (UTs), one problem is how they can be implemented optimally. According to critical constraints, the implementation task was shaped as minimization, including the numbers of UAVs and the optimization of their network load: UAV should form a secure network structure and sustain links with the specified base stations (BSs). The challenge has been split into subtasks to address this problem of optimization with a core framework. The Unified Greedy Quest Algorithm for the Internet of Medical Things (UGQA-IoMT) algorithm is used for telemedicine applications and achieves a minimum number of UAVs and optimal places. The algorithm proposed refers to various scenarios in which UAVs are installed by themselves or with the set BSs, irrespective of the UT deployment. The performance gains in mean SNR of −3 dB, network load stability ratio of 99.89%, and coverage ratio of 97.5% are validated in coherent simulations of the proposed methodology for the real-time implementation.