Deep Learning and or/ AI has been recognized as a state-of-the-art and path breaking technology for achieving significant data rate enhancement in communication systems. In hybrid RF/VLC, data rate maximization is subject to constraints on bandwidth, power and the user association. The joint optimization problem of bandwidth, power and user association to maximize the data rate is non-concave and obtaining an optimal solution is difficult with conventional optimization algorithms. The 5G communication and IoT Group in the Department is actively involved in developing Deep Q Network based solutions to address these issues. The application of DQN learning based algorithm is carried out by finding an optimal policy with the help of an action-value function. As the data sets for the considered system are large, a multi-layered neural network is used for approximating the action-value function estimator. In only RF systems, the group is involved in the application of Deep Learning and AI system in cognitive radio communication security.

Deep Learning/AI in Hybrid RF/VLC based 5G Communication