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Uplink puncturing for mixed URLLC and eMBB services in 5G-based IWNs: a model-aided DRL method
Regular Papers | Updated：2026-01-07

    • Uplink puncturing for mixed URLLC and eMBB services in 5G-based IWNs: a model-aided DRL method

      Enhanced Publication
    • 面向5G工业无线网络的URLLC与eMBB混合业务上行链路穿刺传输：一种模型辅助深度强化学习方法
    • “In the realm of 5G-based industrial wireless networks, a new puncturing method has been proposed to tackle the resource slicing challenges between ultra-reliable low-latency communication and enhanced mobile broadband services. The research introduces a model-aided deep reinforcement learning algorithm that optimizes scheduling parameters, demonstrating accelerated convergence and superior resource efficiency.”
    • Frontiers of Information Technology & Electronic Engineering   Vol. 26, Issue 11, Pages: 2338-2352(2025)

    • DOI：10.1631/FITEE.2500173    

      CLC： TN929.5

    • Received：18 March 2025，

      Revised：2025-07-22，

      Published Online：29 November 2025，

      Published：2025-11

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  • Jingfang DING, Meng ZHENG, Haibin YU, et al. Uplink puncturing for mixed URLLC and eMBB services in 5G-based IWNs: a model-aided DRL method[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(11): 2338-2352. DOI： 10.1631/FITEE.2500173.

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