Deep reinforcement learning for RAN optimization and control
2021 IEEE Wireless Communications and Networking Conference (WCNC)(2021)
摘要
Due to the high variability of the traffic in the radio access network (RAN), fixed network configurations are not flexible enough to achieve optimal performance. Our vendors provide several settings of the eNodeB to optimize the RAN performance, such as media access control scheduler, loading balance, etc. But the detailed mechanisms of the eNodeB configurations are usually very complicated and n...
更多查看译文
关键词
Wireless communication,Heuristic algorithms,Key performance indicator,Training data,Reinforcement learning,Data models,Tuning
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要