LINK ADAPTATION OPTIMIZED WITH MACHINE LEARNING

    公开(公告)号:US20220149980A1

    公开(公告)日:2022-05-12

    申请号:US17440209

    申请日:2019-03-18

    IPC分类号: H04L1/00 G06N3/02

    摘要: Methods and systems for dynamically selecting a link adaptation policy, LAP. In some embodiments, the method includes generating a machine learning, ML, model, wherein generating the ML model comprises providing training data to an ML algorithm. The method further includes using channel quality information, additional information, and the ML model to select a LAP from a set of predefined LAPs. In some embodiments, the additional information comprises: neighbor cell information about a second cell served by a second TRP, distance information indicating a distance between a UE and a first TRP, and/or gain information indicating radio propagation gain between the UE and the serving node. The method further includes the first TRP transmitting second data to the UE using the selected LAP.

    LINK ADAPTATION OPTIMIZATION WITH CONTEXTUAL BANDITS

    公开(公告)号:US20220182175A1

    公开(公告)日:2022-06-09

    申请号:US17440030

    申请日:2019-03-18

    IPC分类号: H04L1/00 H04W24/10

    摘要: Methods and systems for dynamically selecting a link adaptation policy, LAP. In some embodiments, the method includes using channel quality information, additional information, and a machine learning, ML, model to select a LAP from a set of predefined LAPs, the set of predefined LAPs comprising a first LAP and a second LAP. In some embodiments, the additional information comprises: neighbor cell information about a second cell served by a second TRP, distance information indicating a distance between a UE and a first TRP, and/or gain information indicating a radio propagation gain between the UE and the serving node. The method further includes the first TRP transmitting data to the UE using the selected LAP.