Machine Learning Approaches for Adaptive Signal Processing in 6G Networks

Due to the very rapid growth of wireless communication networks, the arrival of the 6th Generation (6G) signals the beginning of groundbreaking experiences and new opportunities. The success of 6G networks hinges on their capacity to adapt to complicated and constantly evolving communication environments. This study investigates the critical role of ML in enabling adaptive signal processing in 6G networks. In conclusion, our study proves that ML is crucial for adaptive signal processing in 6G networks and suggests that it could impact the design of future wireless communication systems. The advent of 6G networks, enabled by machine learning, will usher in a new age of connectedness and innovation by satisfying the need for very fast, extremely reliable, and extremely efficient communication.