We develop an asynchronous framework across userkernel spaces for deep learning applications on the improvement of Wi-Fi performanceimplement it in the driver of commodity Intel Wi-Fi cards. Under this framework, we apply deep reinforcement learning to developing an intelligent rate adaptation (RA) algorithm (DRL-RA), which can achieve the highest throughput in varying channel conditions given many rate options of current Wi-Fi technologies. Its on-learning capability can learn how to efficiently approach the best rate from the experiences of its common usage patternenvironment.

Although there are few open-source core network projects, none of them are conformed to 3GPP Release 15 (R15). The free5GC is the first one in the world based on 3GPP R15. The ultimate goal of free5GC is to implement a full commercial, operational core network including Operation, AdministrationManagement (OAM), orchestrator,network slicing complied with 3GPP R15beyond.