Artificial Intelligence Techniques For Rate Maximization In Interference Channels

Enabling multiple users to transmit on the same channel, simultaneously, is an essential part of the future generation of communication systems. Optimization of transmit power has a significant impact on the performance of communication systems. Under spectrum re-use, the transmit power of one user causes interference to the other users on the shared channels, also known as interference channels (ICs). Under IC model, the structure of power allocation problems becomes complex. Recently, artificial intelligence (AI) techniques have shown promising results in various wireless communication problems. This paper aims to explore various AI techniques to optimize power allocation in multiuser IC transmission. Sum rate maximization problem subject to guaranteed per user performance under limited available power budget at each transmitting node is considered. Specifically, we first investigate the performance of Particle Filter and Particle Swarm Optimization based search algorithm. Then, Linear Regression and Neural Network based predictors are designed to reduce the overall time complexity. Finally, extensive simulations are presented to compare the performance of obtained solutions. (C) 2021 Published by Elsevier B.V.