A TRUST REGION OPTIMIZATION BASED DEEP LEARNING-BASED RESOURCE ALLOCATION METHOD FOR 5G AND BEYOND NETWORK TOPOLOGIES

摘要

The inventive method proposes a solution to the resource allocation problem in 5G and beyond communication networks. The present invention proposes a method in the field of solution of the problem of how resources are allocated in communication networks, particularly wireless networks. For the solution of this problem, especially deep learning techniques for finding an equilibrium point between speed, latency and reliability are utilized, and it proposes an efficient solution.