Method of supporting reinforcement learning in mobile communication system and devices for performing the same
AssigneeElectronics and Telecommunications Research Institute
InventorsJihoon Sung, Myung Ki Shin
Life of this patent
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Abstract
A method of supporting reinforcement learning (RL) in a mobile communication system and devices for performing the same are disclosed. The method of supporting RL in a mobile communication system includes receiving a subscription request to train an RL model from a consumer network function (NF), training the RL model by collecting data in response to the subscription request, and when training of the RL model is completed based on a training completion condition, transmitting a notification including RL model information to the consumer NF.
Claims14
A method of operating a device including a network data analytics function (NWDAF) that supports reinforcement learning (RL) in a mobile communication system, the method comprising:
- receiving a subscription request to train an RL model from a consumer network function (NF);
- training the RL model by collecting data in response to the subscription request;
- and
- when training of the RL model is completed based on a training completion condition, transmitting a notification comprising RL model information to the consumer NF, and
- wherein the subscription request comprises parameters that the consumer NF is able to provide, and
- wherein the parameters comprise an expected RL training completion time, an expected RL training completion condition other than time, an expected RL model confidence level, an expected reward, a candidate action space, an RL model update period, an RL preparation flag, an RL correlation identifier (ID), and an available data requirement.
A device including a network data analytics function (NWDAF) that supports reinforcement learning (RL) in a mobile communication system, the device comprising:
- a processor;
- and
- a memory electrically connected to the processor and configured to store instructions executable by the processor,
- wherein the processor performs a plurality of operations when the instructions are executed by the processor, and
- the plurality of operations comprises:
- receiving a subscription request to train an RL model from a consumer network function (NF);
- training the RL model by collecting data in response to the subscription request;
- and
- when training of the RL model is completed based on a training completion condition, transmitting a notification comprising RL model information to the consumer NF, and
- wherein the subscription request comprises parameters that the consumer NF is able to provide, and
- wherein the parameters comprise an expected RL training completion time, an expected RL training completion condition other than time, an expected RL model confidence level, an expected reward, a candidate action space, an RL model update period, an RL preparation flag, an RL correlation identifier (ID), and an available data requirement.
Dependencies are inferred from the claim text.