Method and apparatus for performing handover based on ai model in a wireless communication system
A method and apparatus for performing handover based on AI model in a wireless communication system is provided. The source node acquire a mobility information for a specific UE. The source node transmits, to the specific UE, a measurement configuration including a request for a location information. The source node receives, from the specific UE, the location information. The source node determine a target RAN node for the specific UE by using an AI model, based on the mobility information and the location information. The source node performs a handover procedure for the specific UE with the determined target RAN node.
1 . A method comprising,
transmitting, by a source node to a User Equipment (UE), a measurement configuration;
receiving, by the source node from the UE, a measurement report including location information based on the measurement configuration;
transmitting, by the source node to a target node, a handover request message related to the UE,
wherein the handover request message includes prediction information for cells where the UE is predicted to connect,
wherein the prediction information includes one or more predicted information, and
wherein each predicted information includes (i) information a for a predicted cell and (ii) duration information; and
receiving, by the source node from the target node, a handover request acknowledge message in response to the handover request message.
2 . The method of claim 1 , wherein the UE is in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the UE.
3 . The method of claim 1 ,
wherein the location information further includes at least one of (i) a current location for the UE or (ii) a past location for the UE.
4 . The method of claim 3 ,
wherein the location information further includes a predicted location for the UE, and
wherein the predicted location includes at least one of:
(i) information for at least one of:
a Global Positioning System (GPS),
a Global Navigation Satellite System (GNSS),
a Tracking Area (TA), or
a cell where the UE will move into; or
(ii) information for confidence of the predicted location.
5 . The method of claim 4 , wherein the predicted location for the UE includes output of at least one of:
an Artificial Intelligence (AI) model,
a Machine Learning (ML) model, or
an inference function.
6 . The method of claim 1 , wherein the prediction information includes one or more predicted information, in time order.
7 . The method of claim 1 , wherein the duration information is related to a predicted duration of time the UE stays in the predicted cell.
8 . The method of claim 1 , wherein the prediction information includes output of at least one of:
an Artificial Intelligence (AI) model,
a Machine Learning (ML) model, or
an inference function.
9 . The method of claim 1 , wherein the prediction information is transmitted from the UE or a core network node.
10 . The method of claim 1 ,
wherein the source node is a source gNB, and
wherein the target node is a target gNB.
11 . A source node comprising:
a memory; and
at least one processor operatively coupled to the memory, and adapted to perform operations, the operations comprising:
transmitting, to a User Equipment (UE), a measurement configuration;
receiving, from the UE, a measurement report including location information based on the measurement configuration;
transmitting, to a target node, a handover request message related to the UE,
wherein the handover request message includes prediction information for cells where the UE is predicted to connect,
wherein the prediction information includes one or more predicted information, and
wherein each predicted information includes (i) information for a predicted cell and (ii) duration information; and
receiving, from the target node, a handover request acknowledge message.
12 . The source node of claim 11 ,
wherein the source node is a source gNB, and
wherein the target node is a target gNB.
13 . A method comprising,
receiving, by a User Equipment (UE) from a source node, a measurement configuration; and
transmitting, by the UE to the source node, measurement reports including location information based on the measurement configuration,
wherein the source node transmits, to a target node, a handover request message related to the UE,
wherein the handover request message includes prediction information for cells where the UE is predicted to connect,
wherein the prediction information includes one or more predicted information, and
wherein each predicted information includes (i) information for a predicted cell and (ii) duration information; and
wherein the source node receives, from the target node, a handover request acknowledge message in response to the handover request message.
14 . The method of claim 13 , wherein the prediction information includes one or more predicted information, in time order.
15 . The method of claim 13 , wherein the duration information is related to a predicted duration of time the UE stays in the predicted cell.
16 . The method of claim 13 , wherein the prediction information includes output of at least one of:
an Artificial Intelligence (AI) model,
a Machine Learning (ML) model, or
an inference function.
17 . The method of claim 13 , wherein the prediction information is transmitted from the UE or a core network node.
18 . The method of claim 13 ,
wherein the source node is a source gNB, and
wherein the target node is a target gNB.
19 . The method of claim 13 , wherein the UE is in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the UE.