most citedKnowledge-Assisted Deep Reinforcement Learning in 5G Scheduler Design: From Theoretical Framework to Implementation

2 citations · 2 across the 1 of their papers we have counts for

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eess.SP2020★ 2 cited

Knowledge-Assisted Deep Reinforcement Learning in 5G Scheduler Design: From Theoretical Framework to Implementation

Zhouyou Gu, Changyang She, Wibowo Hardjawana +4

In this paper, we develop a knowledge-assisted deep reinforcement learning (DRL) algorithm to design wireless schedulers in the fifth-generation (5G) cellular networks with time-se…