Deep Q-Network for 5G NR Downlink Scheduling
Deep Q-Network for 5G NR Downlink Scheduling
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DOI：
10.1109/iccworkshops53468.2022.9814547
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Walaa AlQwider;T. Rahman;V. Marojevic
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文献类型：
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作者：
Walaa AlQwider;T. Rahman;V. Marojevic
第三代合作伙伴项目 (3GPP) 推出了第五代新无线电 (5G NR) 规范，该规范提供比传统蜂窝通信标准更高的灵活性，可以更好地处理新兴用例的异构服务和性能要求。然而，这种灵活性使得资源管理更加复杂。因此，本文设计了一种基于深度Q网络（DQN）的数据驱动的资源分配方法。所提出模型的目标是最大化 5G NR 小区吞吐量，同时为所有用户提供公平的资源分配。使用符合 3GPP 的 5G NR 模拟器的数值结果表明，DQN 调度器比现有调度器更好地平衡了小区吞吐量和用户公平性。
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.