Deep Q-Network for 5G NR Downlink Scheduling

The Third Generation Partnership Project (3GPP) introduced the fifth generation new radio (5G NR) specifications which offer much higher flexibility than legacy cellular communications standards to better handle the heterogeneous service and performance requirements of the emerging use cases. This flexibility, however, makes the resources management more complex. This paper therefore designs a data driven resource allocation method based on the deep Q-network (DQN). The objective of the proposed model is to maximize the 5G NR cell throughput while providing a fair resource allocation across all users. Numerical results using a 3GPP compliant 5G NR simulator demonstrate that the DQN scheduler better balances the cell throughput and user fairness than existing schedulers.