Deep Learning Aided Transmit Power Estimation in Mobile Communication System

Abstract

This letter investigates the problem of transmit power control in a mobile communication system. We propose a transmit power estimation scheme to maximize the overall system capacity where the transmit power control of the user is investigated using a recurrent neural network. This leads to a reduction in the need for generating a massive overhead with pilot signals in a dense cellular network. The gains obtained from the simulations are quantified in terms of the mean square error and overall system capacity. Our proposed scheme outperforms the conventional power control technique and other neural networks.