Optimization of Base Station for 6G Wireless Networks for Efficient Resource Allocation using Deep Learning

Abstract

Sixth Generation (6G) networks are currently being investigated to cope with the increasing number of devices in the communication network. The parameters of 6G are still a work in progress but it is speculated that 6G will have a transmission speed of up to 100 Gbps with a frequency band that could be in terahertz. To contribute to the study on optimization of 6G networks we have developed a novel neural network called BSOnet that takes different parameters as input and then gives an output about the state of the base station in the network. With our proposed algorithm we were able to achieve a decreased power consumption in the network. We believe that study will pave the path for future studies on the optimization for 6G networks using deep learning.

Keywords: 6G Wireless network, Deep learning, Neural network, Resource allocation