Artificial Intelligence for Dynamic Resource Allocation of 5G FR2 Networks

With the rapid advance of mobile technology, developing efficient resource allocation methods has become crucial for the fifth-generation mobile network (5G). These methods are essential to ensure the network’s optimal performance and to meet users’ growing demands for reliable and high-speed connectivity. This work proposes using fuzzy logic for dynamic resource allocation to save energy on devices connected to the 5G FR2 network, considering the current buffer, battery level, and BLER. The results show that our proposal obtains a good tradeoff between energy consumption and backlogged bits compared to the other methods evaluated.