Power Allocation for Joint Large Intelligent Surfaces Decode-And-Forward Relay in Full-Duplex Communications - A Deep Learning Approach

Large Intelligent Surfaces are key technologies for the upcoming 6G networks for their high capabilities and low power consumption. To further extend the coverage, relays can be employed to overcome distances and obstacle limitations. In this paper, we integrate the large intelligent surfaces technology with the decode-and-forward relay to aid the communication of a base station with a full-duplex user in the presence of device-to-device communicating devices. A closed form expression for the optimum power to achieve maximum data rate is derived in the presence of self-interference and co-channel interference from the device-to-device communications. A neural network approach is proposed, that accurately predicts the minimum power required to achieve maximum data rates. Results show that the neural network is a promising alternative to avoid complex calculations.