Comments: Reinforcement Learning Model Selection for Resource Allocation and Subcarrier Spacing Optimization in 5G Sliced Spectrum Networks

Reinforcement Learning Model Selection for Resource Allocation and Subcarrier Spacing Optimization in 5G Sliced Spectrum Networks

The evolution of 5G technology presents unique challenges and opportunities for optimizing network performance through advanced techniques such as Reinforcement Learning (RL). Effective 5G network management requires precise optimization of subcarrier spacing and uplink-downlink (UL-DL) allocation,...

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Bibliographic Details
Main Authors:	Samidi F.S., Radzi N.A.M., Aripin N.M.
Other Authors:	57215054855
Format:	Conference paper
Published:	Institute of Electrical and Electronics Engineers Inc. 2025
Subjects:	Network performance Queueing networks Reinforcement learning Resource allocation Dynamic condition Efficient learning Learning process Networks management Optimisations Performance Real- time Reinforcement learning models Stable performance Subcarrier spacing 5G mobile communication systems
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Reinforcement Learning Model Selection for Resource Allocation and Subcarrier Spacing Optimization in 5G Sliced Spectrum Networks

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