MAX- MIN Power Control of Cell Free Massive MIMO System employing Deep Learning

The sixth generation (6G) of wireless communication networks should deliver higher data rates and spectral efficiency for novel demands and utilizations. Cell free massive MIMO is one promising technique to achieve these goals. Distribution of base stations (BSs) in this system creates more efficiency and better coverage of users than the conventional cellular system. On the other hand, deep learning methods have been proven to be competitive frameworks in comparison of traditional optimization approaches in wireless communication applications. In this paper, power allocation in cell free massive MIMO system in uplink transmission is investigated. Firstly, we achieve lower bound of spectral efficiency, which is valid for all decoders. Besides, we evaluate MAX- MIN power allocation problem from the perspective of deep learning and common optimization methods. The simulation results confirm the superior performance of the deep learning compared to traditional optimization methods. Furthermore, computations complexity of power allocation in the deep learning case are extremely low.