Information transmission method, apparatus and device, and storage medium and program product

Abstract

Provided in the present disclosure are an information transmission method, apparatus and device, and a storage medium and a program product. The method comprises: a first network node sending first information to a second network node, wherein the second network node is a network node that generates original movement trajectory prediction information, and the first information comprises indication information used for indicating updated movement trajectory prediction information and / or information related to new movement trajectory prediction information; and / or, the first network node sending second information to a third network node, wherein the third network node is a network node on an actual movement trajectory that is located after the first network node, or a network node in the new movement trajectory prediction information that is located after the first network node, and the second information comprises movement trajectory prediction information.

Description

Information transmission method and apparatus, device, storage medium, and program product

[0001] Cross-reference to Related Applications

[0002] The present disclosure claims priority from Chinese Patent Application No. 202411321837.6 filed on September 23, 2024 in China, the contents of which are incorporated herein by reference in its entirety. TECHNICAL FIELD

[0003] The present disclosure relates to the technical field of wireless communication, and in particular to an information transmission method, apparatus, device, storage medium and program product. BACKGROUND

[0004] Artificial Intelligence (AI) technology can extract features of massive data in complex scenarios and perform model training and deduction to achieve prediction and decision-making, so it is increasingly valued and applied by various industries. Mobility Optimization is one of the typical scenarios of the combination of the 5th Generation Mobile Communication Technology (5G) and AI technology, which uses data collection and AI technology to predict the UE Trajectory of a User Equipment (UE) in the future period of time, so as to achieve the purposes of assisting the handover decision of the network and reserving resources in advance. UE mobile trajectory prediction refers to the mobile trajectory prediction information generated by a source node for a certain UE in the cells within the range of the next hop or multi-hop target network node after leaving the source node. The real mobile trajectory information of the UE in each cell within the target network node is fed back to the source node by the subsequent target network node, so as to realize the performance detection and training of the AI model of the source node.

[0005] With the deep integration of AI technology and wireless network, there will be a large number of nodes in the network that deploy AI models to have prediction capabilities. In the UE mobile trajectory prediction scenario, after the source node generates multi-hop mobile trajectory prediction information for a certain UE and forwards it to target network node 1, if target network node 1 also has multi-hop UE mobile trajectory prediction capability, target network node 1 can generate new trajectory prediction information to replace the original prediction information and send it to target network node 2.

[0006] However, the inventors find that the related art at least has the following problems: in the above scenario, the source node cannot know that its trajectory prediction information is replaced by the prediction information of other nodes, which may cause the source node to wait for a long time for the subsequent node to feed back the real moving trajectory information, and also cannot update the AI model due to the lack of feedback information, affecting the prediction performance. SUMMARY

[0007] The purpose of the embodiments of the present disclosure is to provide an information transmission method, device, equipment, medium and product, which sends information to the network node generating the original moving trajectory prediction information after updating the moving trajectory prediction information through the intermediate node, indicates the related situation of the new prediction information, and optimizes the process of terminal moving trajectory prediction.

[0008] To achieve the above purpose, the embodiments of the present disclosure provide an information transmission method applied to a first network node, the method comprising:

[0009] sending first information to a second network node; wherein the second network node is a network node generating original moving trajectory prediction information, and the first information comprises indication information indicating updated moving trajectory prediction information and / or related information of new moving trajectory prediction information;

[0010] and / or sending second information to a third network node; wherein the third network node is a network node actually located behind the first network node on the moving trajectory or a network node located behind the first network node in the new moving trajectory prediction information, and the second information comprises related information of the original moving trajectory prediction information or related information of the new moving trajectory prediction information.

[0011] As a preferred embodiment, the method further comprises:

[0012] generating related information of new moving trajectory prediction information when it is determined that a moving trajectory prediction update condition is met; the moving trajectory prediction update condition is at least one of the following conditions:

[0013] the first update condition is that the original moving trajectory prediction information exceeds the valid period;

[0014] the second update condition is that the original moving trajectory prediction information does not match the real moving trajectory of the terminal;

[0015] the third update condition is that the remaining prediction trajectory in the original moving trajectory prediction information is insufficient.

[0016] As a preferred embodiment, the related information of the new moving trajectory prediction information comprises a predicted target network node sequence and / or a target cell sequence within each target network node range and / or a terminal residence duration in each cell.

[0017] As a preferred implementation, the first information comprises at least one of the following information: time information, reason information, real mobile track information and identification information of the second network node; wherein,

[0018] The time information is the generation time of the original mobile track prediction information and / or the generation time of the new mobile track prediction information;

[0019] The reason information is the triggered mobile track prediction update condition;

[0020] The real mobile track information comprises at least one of the following information: real cell sequence within the first network node range, last real network node, last real cell, next real network node, next real cell; the real network node is the node actually entered by the terminal, and the real cell is the cell actually entered by the terminal.

[0021] As a preferred implementation, before the new mobile track prediction information is generated and / or the first information is sent to the second network node when it is determined that the mobile track prediction update condition is met, the method further comprises:

[0022] receiving the original mobile track prediction information of the terminal generated by the second network node; wherein, the mobile track prediction information comprises a predicted target network node sequence and / or a target cell sequence within each target network node range.

[0023] As a preferred implementation, determining whether the first update condition is met comprises:

[0024] when the already camped time length is greater than a preset valid time length of the original mobile track prediction information, it is determined that the original mobile track prediction information is over the valid period; wherein, the already camped time length is the time length that the terminal has camped on the target cell within the target network node range in the original mobile track prediction information.

[0025] Determining whether the second update condition is met comprises:

[0026] when the next target network node or target cell predicted in the original mobile track prediction information is inconsistent with the next real network node or real cell actually switched by the terminal, it is determined that the original mobile track prediction information is inconsistent with the real mobile track of the terminal.

[0027] Determining whether the third update condition is met comprises:

[0028] When the remaining node quantity is less than a preset node quantity threshold or the remaining cell quantity is less than a preset cell quantity threshold, it is determined that the remaining predicted trajectory in the original mobile trajectory prediction information is insufficient; wherein the remaining node quantity or the remaining cell quantity is a quantity of target network nodes or target cells after the first network node in the original mobile trajectory prediction information.

[0029] As a preferred implementation, the sending of the first information to the second network node comprises:

[0030] When a communication interface exists between the first network node and the second network node, the first information is sent to the second network node through the communication interface.

[0031] When no communication interface exists between the first network node and the second network node, the first information is forwarded to the second network node through an intermediate network node having a communication interface.

[0032] As a preferred implementation, the second network node can update a mobile trajectory prediction model deployed by itself according to the first information after receiving the first information.

[0033] The embodiments of the present disclosure further provide an information transmission device applied to a first network node, the device comprising:

[0034] a first information sending module configured to send first information to a second network node; wherein the second network node is a network node generating original mobile trajectory prediction information, and the first information comprises indication information indicating updated mobile trajectory prediction information and / or related information of new mobile trajectory prediction information;

[0035] and / or,

[0036] a second information sending module configured to send second information to a third network node; wherein the third network node is a network node after the first network node on an actual mobile trajectory or a network node after the first network node in new mobile trajectory prediction information, and the second information comprises related information of the original mobile trajectory prediction information or related information of the new mobile trajectory prediction information.

[0037] The embodiments of the present disclosure further provide an information transmission device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the information transmission method according to any one of the above embodiments when executing the computer program.

[0038] The embodiment of the present disclosure further provides a computer readable storage medium, which comprises a stored computer program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to execute the information transmission method according to any one of the above when the computer program runs.

[0039] The embodiment of the present disclosure further provides a computer program product, which comprises a computer program or computer instructions, and the computer program or the computer instructions are executed by a processor to realize the information transmission method according to any one of the above.

[0040] Compared with the related art, the information transmission method, device, equipment, storage medium and program product disclosed by the present disclosure optimize the information interaction process between nodes after new prediction information is generated in the multi-node terminal moving trajectory prediction scene. After receiving the moving trajectory prediction information predicted by the previous network node, the intermediate network node judges the moving trajectory prediction update condition. When the update condition is met, the new moving trajectory prediction information is generated, and the first information is sent to the network node generating the original moving trajectory prediction information, to inform the network node that the moving trajectory prediction information has been updated and the related information of the new moving trajectory prediction information. This can make the network node know that its trajectory prediction information is replaced by the prediction information of other nodes in time, and in the case of being replaced, the effective first information is obtained for iterative optimization of the prediction model deployed by itself. In addition, the network node can be prevented from being in the state of waiting for the feedback of the real moving trajectory information of other nodes for a long time, causing unnecessary resource waste, and effectively improving the cell switching performance and user experience. BRIEF DESCRIPTION OF DRAWINGS

[0041] FIG. 1 is a schematic diagram of moving trajectory prediction information in the related art;

[0042] FIG. 2 is a signaling flow diagram of moving trajectory prediction information and real moving trajectory information in the related art;

[0043] FIG. 3 is a flow diagram of an information transmission method provided by an embodiment of the present disclosure;

[0044] FIG. 4 is a flow diagram of a preferred information transmission method in an embodiment of the present disclosure;

[0045] FIG. 5 is a structural diagram of an information transmission device provided by an embodiment of the present disclosure;

[0046] FIG. 6 is a structural diagram of an information transmission device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present disclosure will be clearly and completely described in the description of the embodiments of the present disclosure in combination with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the protection scope of the present disclosure.

[0048] In the description of the present application, it should be understood that the terms "center", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0049] The terms "first", "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise stated, the meaning of "a plurality of" is two or more.

[0050] It should be noted that the embodiments of the present disclosure are applicable to the scenario of predicting the moving trajectory of a terminal UE. Currently, the 5G New Radio (NR) introduces the functions of first-hop UE moving trajectory prediction (Predicted UE Trajectory) and measured UE trajectory collection (measured UE trajectory collection) of real / actual UE. In the future, the UE moving trajectory prediction in the Multi-hop scenario will be introduced. The UE moving trajectory prediction refers to the moving trajectory prediction information generated by a source node for a certain UE in the next hop or multi-hop target network node after leaving the source node. Taking the Multi-hop scenario as an example, as shown in FIG. 1, which is a schematic diagram of moving trajectory prediction information in the related art, the moving trajectory prediction (Predicted UE Trajectory) information generated by the source node for a certain UE includes the order and related information of the UE entering each target cell in the range of target network node 1 (Target node-1), target network node 2 (Target node-2), and target network node 3 (Target node-3) in sequence. The measured UE trajectory collection (measured UE trajectory collection) of real / actual UE is that one or more target network nodes feed back the real moving trajectory information (measured UE trajectory) of the UE in each cell in the target network node to the source node, which is used for performance testing and training of the AI / ML model.

[0051] Referring to FIG. 2, which is a signaling flow diagram of moving trajectory prediction information and real moving trajectory information in the related art, taking the single-hop UE moving trajectory related signaling flow as an example, the UE moving trajectory prediction information and the measured UE trajectory collection (measured UE trajectory collection) of real / actual UE are as shown in FIG. 2. Node 1 sends a data collection request (DATA COLLECTION REQUEST) to node 2, expecting to carry configuration information for collecting real moving trajectory information. Node 2 returns a data collection response (DATA COLLECTION RESPONSE) to node 1. Node 1 sends a handover request (HANDOVER REQUEST) to node 2, which carries the predicted moving trajectory prediction information. Node 2 returns a handover response (HANDOVER REQUEST ACK). Node 2 starts / stops collecting real moving trajectory information and UE performance information, and returns a data collection update instruction (DATA COLLECTION UPDATE) to node 1, which carries real moving trajectory information and UE performance information and other related measurement information.

[0052] However, in the UE moving trajectory prediction scenario, the following situation may exist: assuming that the source node and the target network node 1 both have multi-hop UE moving trajectory prediction capability, the source node generates multi-hop moving trajectory prediction information for a UE and sends it to the target network node 1, the target network node 1 can choose to continue to send the prediction information generated by the source node to the next-hop target network node 2, or choose to generate new trajectory prediction information and send it to the target network node 2, that is, replace the original prediction information with new prediction information, both the source node and the target node 1 generate UE moving trajectory prediction information, and the subsequent target network nodes need to feed back the real moving trajectory information of the UE for performance detection of the AI / ML model. In the above scenario, the following problems cannot be solved: how does the source node know that its trajectory prediction information has been replaced by the prediction information of other nodes, and how to obtain the real moving trajectory information of the UE in the case of prediction information replacement, and there is no corresponding process support in the related art. This problem may cause the source node to wait for the feedback of the real moving trajectory information for a long time, and also cannot update the AI / ML model due to the lack of feedback information, affecting the prediction performance.

[0053] To solve the above problems, referring to FIG. 3, which is a flowchart of an information transmission method provided by an embodiment of the present disclosure, an information transmission method is provided, which is applied to a first network node, and the method comprises the following steps:

[0054] S11, sending first information to a second network node; wherein the second network node is a network node generating original moving trajectory prediction information, and the first information comprises indication information indicating updated moving trajectory prediction information and / or related information of new moving trajectory prediction information;

[0055] and / or;

[0056] S12, sending second information to a third network node; wherein the third network node is a network node actually located after the first network node on the moving trajectory or a network node located after the first network node in the new moving trajectory prediction information, and the second information comprises related information of the original moving trajectory prediction information or related information of the new moving trajectory prediction information.

[0057] It should be noted that the first network node, the second network node and the third network node and the like network nodes can include NG-RAN (5G wireless access network) nodes, and specifically can be base stations, which do not affect the beneficial effects obtained by the present disclosure.

[0058] In the embodiments of the present disclosure, the first network node is a network node with mobile trajectory prediction capability. In the process of mobile trajectory prediction of the terminal, the first network node has the function of forwarding the mobile trajectory prediction information, and also has the ability to update the mobile trajectory prediction information and feed back the first information to the previous network node generating the original mobile trajectory prediction information.

[0059] Preferably, the method further comprises:

[0060] When it is determined that the mobile trajectory prediction update condition is met, new mobile trajectory prediction information is generated.

[0061] The related information of the new mobile trajectory prediction information includes a predicted target network node sequence, a target cell sequence in the range of each target network node, and / or a duration of terminal staying in each cell.

[0062] Preferably, before the new mobile trajectory prediction information is generated and / or the first information is sent to the second network node when it is determined that the mobile trajectory prediction update condition is met, the method further comprises:

[0063] Receiving the original mobile trajectory prediction information of the terminal generated by the second network node; wherein the mobile trajectory prediction information includes a predicted target network node sequence and / or a target cell sequence in the range of each target network node.

[0064] In the embodiments of the present disclosure, the second network node generates multi-hop mobile trajectory prediction information for a certain terminal UE. Understandably, the mobile trajectory of the terminal refers to the trajectory of the terminal moving on each cell, and one or more cells in the range of a certain node are monitored by the node. The mobile trajectory prediction information includes a target network node sequence predicted by the second network node, that is, the order of the multi-hop target network node range that the terminal UE may enter, and also includes a target cell sequence in the range of each target network node, that is, the mobile trajectory of the terminal UE on each target cell after entering the target network node range.

[0065] As an example, the mobile trajectory prediction information generated by the second network node for the terminal UE is a cell sequence of target cell cell-11, target cell cell-12, target cell cell-13, target cell cell-21, target cell cell-22, target cell cell-31 and target cell cell-32, wherein cell-11, cell-12 and cell-13 are in the range of target network node 1, cell-21 and cell-22 are in the range of target network node 2, and cell-31 and cell-32 are in the range of target network node 3.

[0066] The second network node generates the mobile trajectory prediction information, and sends the mobile trajectory prediction information to a first hop target network node 1 in the prediction information, and the target network node 1 can select to continue to send the mobile trajectory prediction information to a next hop target network node 2.

[0067] The embodiments of the present disclosure are applied to an intermediate network node in a certain mobile trajectory, denoted as a first network node A, which is deployed with a terminal mobile trajectory prediction model and has a terminal mobile trajectory prediction capability. When the first network node A receives mobile trajectory prediction information (denoted as predicted UE trajectory-1) from other nodes (a previous hop target network node), it determines whether a preset mobile trajectory prediction update condition is met. If it is determined that the mobile trajectory prediction update condition is not met, the first network node A does not update the mobile trajectory prediction information, but sends the original mobile trajectory prediction information and related information to a next hop target network node, i.e., a third network node. If it is determined that the mobile trajectory prediction update condition is met, the first network node A generates new mobile trajectory prediction information (denoted as predicted UE trajectory-2) based on its own AI prediction capability.

[0068] After determining that the mobile trajectory prediction update condition is met and generating the new mobile trajectory prediction information, the first network node A generates first information, which includes indication information for indicating that the mobile trajectory prediction information has been updated. The indication information is used to indicate that the first network node A generates the new UE mobile trajectory prediction information (predicted UE trajectory-2) instead of the UE mobile trajectory prediction (predicted UE trajectory-1) generated by the second network node, i.e., the first network node A no longer sends the prediction information predicted UE trajectory-1 to the target network node behind. The first information also includes related information of the new mobile trajectory prediction information. The first network node A sends the first information to the second network node. In this way, the second network node can know that its mobile trajectory prediction information is replaced after receiving the first information, and can perform iterative optimization of its own prediction model according to the valid first information, thereby avoiding resource waste caused by waiting for the real mobile trajectory information feedback from the subsequent node for a long time.

[0069] In addition, after determining that the mobile trajectory prediction update condition is met and generating new mobile trajectory prediction information, the first network node A replaces the original mobile trajectory prediction information and sends the new mobile trajectory prediction information predicted UE trajectory-2 and related information thereof to the predicted next-hop target network node, i.e., the third network node, in handover preparation (for example, in a HANDOVER REQUEST message).

[0070] By using the technical means of the embodiments of the present disclosure, in the multi-node terminal mobile trajectory prediction scenario, the information interaction process between nodes after new prediction information is generated is optimized. After receiving the mobile trajectory prediction information predicted by the previous network node, the intermediate network node determines the mobile trajectory prediction update condition. When the update condition is met, new mobile trajectory prediction information is generated, and first information is sent to the network node that generates the original mobile trajectory prediction information, to inform the network node that the mobile trajectory prediction information has been updated and the related information of the new mobile trajectory prediction information. This can enable the network node to learn in time that its trajectory prediction information is replaced by the prediction information of other nodes, and in the case of being replaced, to obtain effective first information for iterative optimization of the prediction model deployed by the network node. This can also avoid the network node being in a state of waiting for feedback of real mobile trajectory information from other nodes for a long time, causing unnecessary resource waste, and effectively improving cell handover performance and user experience.

[0071] It should be noted that in the above-mentioned UE mobile trajectory prediction scenario, the following problem cannot be solved by the related art: how does the intermediate network node choose to continue forwarding the prediction information of the previous network node or generate new prediction information? There is no corresponding mechanism to support this in the related art. This problem can cause the intermediate network node to be unable to adapt to changes in the situation to provide accurate and reliable prediction information to the target network node behind it, and the target network node behind it can perform resource reservation and other operations based on inaccurate prediction information, causing unnecessary resource waste.

[0072] To solve the above-mentioned problem, the mobile trajectory prediction update condition is improved in the embodiments of the present disclosure. As a preferred implementation, the mobile trajectory prediction update condition includes at least one of a first update condition, a second update condition, and a third update condition; wherein,

[0073] The first update condition is that the original mobile trajectory prediction information exceeds a valid period;

[0074] The second update condition is that the original mobile trajectory prediction information does not match the real mobile trajectory of the terminal;

[0075] The third update condition is that the remaining predicted trajectory in the original mobile trajectory prediction information is insufficient.

[0076] Preferably, judging whether the first updating condition is satisfied comprises the following steps:

[0077] When the resident time length is greater than the preset valid time length of the original mobile trajectory prediction information, it is determined that the original mobile trajectory prediction information is out of validity period; wherein the resident time length is the time length that the terminal has resided on a target cell within a target network node range in the original mobile trajectory prediction information.

[0078] In the embodiments of the present disclosure, the method for judging whether the UE mobile trajectory prediction information (predicted UE trajectory-1) is out of validity period can be as follows: obtaining the preset valid time length of the original mobile trajectory prediction information, obtaining the time length that the terminal has resided on a target cell within a target network node range predicted by the original mobile trajectory prediction information, and then comparing the size relationship between the valid time length of the UE mobile trajectory prediction information and the time length that the UE has resided on the node involved in the prediction information. If the valid time length is less than or equal to the resident time length, it is determined that the UE mobile trajectory prediction information is out of validity period, that is, the prediction information does not have a relatively accurate reference meaning for the target network node after the first network node A. At this time, the first network node A determines to generate a new UE mobile trajectory prediction information (predicted UE trajectory-2).

[0079] It should be noted that the valid time length of the UE mobile trajectory prediction information and the time length that the UE has resided on the node can be delivered in the prediction information and / or the configuration information of the first information collection, which is not limited here.

[0080] Preferably, judging whether the second updating condition is satisfied comprises the following steps:

[0081] When the next target network node or target cell predicted in the original mobile trajectory prediction information is inconsistent with the next real network node or real cell actually switched by the terminal, it is determined that the original mobile trajectory prediction information is inconsistent with the real mobile trajectory of the terminal.

[0082] In the embodiments of the present disclosure, the UE mobile trajectory prediction information (predicted UE trajectory-1) is determined to be inconsistent with the actual UE mobile trajectory, and the specific method can be as follows: a next target network node or a target cell predicted in the mobile trajectory prediction information is acquired; a next actual network node or an actual cell actually switched by the terminal is determined according to actual mobile information of the terminal; and when the target network node is inconsistent with the actual network node, or the target cell is inconsistent with the actual cell, it is determined that the mobile trajectory prediction information is inconsistent with the actual mobile trajectory of the terminal. That is, when the first network node A finds that the actual network node determined by the first network node A for switching of the UE is different from the target network node located at the next hop of the node A in the prediction information predicted UE trajectory-1, or the first network node A finds that the actual cell determined by the first network node A for switching of the UE is different from the next target cell in the prediction information predicted UE trajectory-1, that is, the UE mobile trajectory prediction information is inaccurate, the first network node A determines to generate new UE mobile trajectory prediction information predicted UE trajectory-2.

[0083] Preferably, the determining whether the third update condition is met comprises the following steps:

[0084] When the remaining node quantity is less than a preset node quantity threshold, or the remaining cell quantity is less than a preset cell quantity threshold, it is determined that the remaining predicted trajectory in the original mobile trajectory prediction information is insufficient; wherein the remaining node quantity or the remaining cell quantity is a quantity of target network nodes or target cells located after the first network node in the original mobile trajectory prediction information.

[0085] In the embodiments of the present disclosure, the remaining node quantity in the UE mobile trajectory prediction information is determined to be insufficient, and the specific method can be as follows: the first network node A pre-sets a node quantity threshold, if the remaining node quantity in the UE mobile trajectory prediction information, that is, a quantity of target network nodes predicted to be entered by the UE after the first network node A, is less than or equal to the node quantity threshold, the first network node A determines to generate new UE mobile trajectory prediction information; or the first network node A pre-sets a cell quantity threshold, if the remaining cell quantity in the UE mobile trajectory prediction information, that is, a quantity of target cells predicted to be entered by the UE after the first network node A, is less than or equal to the cell quantity threshold, the first network node A determines to generate new UE mobile trajectory prediction information predicted UE trajectory-2.

[0086] By adopting the technical means of the embodiments of the present disclosure, in the multi-node terminal moving track prediction scenario, the condition for the intermediate network node to judge whether the prediction information needs to be updated is optimized, and the information interaction process between network nodes after the new prediction information is generated. After receiving the network node predicted moving track prediction information, the intermediate network node judges whether the original prediction information has become invalid according to the actual situation, and provides prediction information with higher and more reliable prediction accuracy in time in the case of invalidity or impending invalidity, effectively avoiding subsequent target network nodes from performing resource reservation or switching decision and other operations based on the wrong prediction information. At the same time, after generating the new moving track prediction information, the first information is sent to the network node generating the original moving track prediction information, informing the network node that the moving track prediction information has been updated and the related information of the new moving track prediction information, so that the network node can learn in time that its track prediction information is replaced by the prediction information of other nodes, and in the case of being replaced, the effective first information is obtained for iterative optimization of the prediction model deployed by itself, which can also avoid the network node being in the state of waiting for the feedback of the real moving track information of other nodes for a long time, causing unnecessary resource waste, effectively improving the cell switching performance and user experience.

[0087] As a preferred embodiment, step S11, that is, sending the first information to the second network node, comprises:

[0088] When there is a communication interface between the first network node and the second network node, the first information is sent to the second network node through the communication interface;

[0089] When there is no communication interface between the first network node and the second network node, the first information is forwarded to the second network node through an intermediate network node having a communication interface.

[0090] In the embodiments of the present disclosure, in the process of sending the first information to the second network node, if there is an interface (for example, an Xn interface) between the first network node A and the second network node, the first network node A can directly send the first information to the second network node; if there is no interface between the first network node A and the second network node, the first network node A can send the first information to other intermediate nodes for forwarding, the intermediate nodes have interfaces with the first network node A and the second network node respectively, and the first network node can determine the first information forwarding target according to the identification information of the second network node in the first information.

[0091] As a preferred implementation, the related information of the new mobile trajectory prediction information includes at least one of the following information: time information, reason information, real mobile trajectory information, and identification information of the second network node; wherein the time information is the generation time of the original mobile trajectory prediction information and / or the generation time of the new mobile trajectory prediction information; the reason information is the triggered mobile trajectory prediction update condition; the real mobile trajectory information includes at least one of the following information: a real cell sequence within the first network node, a last real network node, a last real cell, a next real network node, and a next real cell; the real network node is the node actually entered by the terminal, and the real cell is the cell actually entered by the terminal.

[0092] Specifically, in addition to the indication information for indicating that the first network node A has generated the new mobile trajectory prediction information predicted UE trajectory-2, the first information sent by the first network node A to the second network node further includes related information of the new mobile trajectory prediction information generated by the first network node A.

[0093] The time information is the generation time of the original mobile trajectory prediction information predicted UE trajectory-1 and / or the generation time of the new mobile trajectory prediction information predicted UE trajectory-2, which can be used to assist the second network node to iteratively optimize the performance of its AI model or the effective duration of the prediction information.

[0094] The reason information is used to indicate the reason why the original prediction information is invalid or cannot be continuously sent to the subsequent target network node, and the specific reason can include but is not limited to: the UE mobile trajectory prediction information exceeds the valid period, is inconsistent with the real mobile trajectory of the UE, and the remaining prediction trajectory is insufficient, etc., which helps the second network node to iteratively optimize the performance of its AI model according to the reason information.

[0095] The real mobile trajectory information (measured UE trajectory) is used to indicate the UE mobile trajectory within the range of the first network node A and / or related to the first network node A (for example, the next hop and next hop network nodes of the first network node A), that is, this information can include: the last hop network node and / or cell identification of the first network node A, one or more cell identifications within the range of the first network node A and the UE residence duration in each cell, the next hop node and / or cell identification of the first network node A (that is, the real network node and / or real cell determined by the first network node A for the UE).

[0096] It should be noted that the first network node A hop network node and / or cell identification information can enable the second network node to know that the original prediction information is valid at the network node and the network node before the network node, and the second network node can wait to obtain the real mobile trajectory information measured UE trajectory fed back by the related node for optimizing the AI model prediction performance. While the first network node A next hop network node and / or cell identification information can enable the second network node to know whether the original prediction information is wrong and the real network node or real cell of the UE real handover, for optimizing the AI model prediction performance, and also enable the second network node to know that it is not necessary to wait for the real mobile trajectory information measured UE trajectory fed back by the target network node after the first network node A in the original prediction information.

[0097] The identification information of the second network node is used to indicate the second network node receiving the first information, and in the case that the first information is forwarded to the second network node by the first network node A through other intermediate nodes, the intermediate node forwarding the first information knows the identity information of the second network node needing to receive the first information.

[0098] By using the technical means of the embodiments of the present disclosure, the content of the first information sent by the intermediate network node to the network node generating the original mobile trajectory prediction information after generating the new mobile trajectory prediction information is optimized, which is beneficial for the original network node to obtain useful first information and perform related operations for optimizing the performance of the AI model, thereby improving the prediction accuracy of the mobile trajectory prediction information of the terminal and improving the cell handover performance and user experience.

[0099] As a preferred embodiment, referring to FIG. 4, which is a flowchart of the preferred information transmission method in the embodiments of the present disclosure, the second network node can update the mobile trajectory prediction model deployed by itself according to the first information after receiving the first information.

[0100] In the embodiments of the present disclosure, after receiving the first information, the second network node can perform AI model prediction performance optimization iteration according to the first information and other related information, and the specific operation can be but not limited to:

[0101] According to the indication information indicating that the new UE moving track prediction has been generated in the first information, the second network node can know that the prediction information of the second network node itself may have prediction errors or time-out of validity period, and part of the target network nodes contained in the original prediction information may not be able to feedback the real moving track information. Further, the first information can be combined with the real moving track information to determine that the AI model prediction performance optimization iteration can be performed according to the real moving track information feedback by the previous target network node of the first network node A and the information of the next-hop real network node feedback by the first network node A.

[0102] According to the cause value information in the first information, the second network node can know the specific reason for the invalidation of the prediction information. For example, if the prediction information validity period is out of time, there may be problems such as inaccurate validity period length, mismatch between the validity period length and the number of nodes contained in the prediction information, or inaccurate prediction of the UE's expected residence time at each node or each cell in the prediction information. The second network node can combine the generation time / time of day of the UE moving track prediction in the first information, the time / time of day determined by the first network node A to generate new prediction information, and / or other information to optimize the AI model prediction performance, and improve the prediction accuracy of the validity period length, the number of predicted nodes, or the residence time at each node or each cell. If the prediction information does not match the real moving track of the UE, the second network node can combine the real moving track information in the first information and / or other information to optimize the AI model prediction performance and improve the accuracy of the UE moving track prediction.

[0103] It should be noted that when the first network node A generates new moving track prediction information, the first network node A is a source node relative to the subsequent target network nodes predicted by the first network node A, and the iteration optimization of the prediction model deployed by the first network node A is also applicable to the above-mentioned embodiments, which will not be repeated here.

[0104] By using the technical means of the embodiments of the present disclosure, the performance optimization of the AI model of the second network node after receiving the first information is optimized, which is beneficial to improve the prediction accuracy of the moving track prediction information of the terminal and effectively improve the cell switching performance and user experience.

[0105] Referring to FIG. 5, which is a structural schematic diagram of an information transmission device provided by an embodiment of the present disclosure, the present disclosure further provides an information transmission device 20 applied to a node with moving track prediction capability. The device 20 comprises:

[0106] A first information sending module 21 is configured to send first information to a second network node. The second network node is a network node generating original moving track prediction information. The first information comprises indication information indicating that the moving track prediction information has been updated and / or related information of new moving track prediction information.

[0107] The second information sending module 22 is configured to send second information to a third network node, wherein the third network node is a network node located after the first network node on an actual moving track or a network node located after the first network node in new moving track prediction information, and the second information comprises relevant information of the original moving track prediction information or relevant information of the new moving track prediction information.

[0108] Preferably, the device 20 further comprises:

[0109] The prediction information receiving module is configured to receive original moving track prediction information of the terminal generated by the second network node, wherein the moving track prediction information comprises a predicted target network node sequence and / or a target cell sequence within a range of each target network node.

[0110] The prediction information updating module is configured to generate new moving track prediction information when it is determined that a moving track prediction updating condition is met.

[0111] As a preferred implementation, the moving track prediction updating condition comprises at least one of a first updating condition, a second updating condition and a third updating condition, wherein:

[0112] The first updating condition is that the moving track prediction information exceeds a valid period.

[0113] The second updating condition is that the moving track prediction information does not match a real moving track of the terminal.

[0114] The third updating condition is that a remaining predicted track in the moving track prediction information is insufficient.

[0115] As a preferred implementation, determining whether the first updating condition is met comprises:

[0116] When a resided time length is greater than a preset valid time length of the original moving track prediction information, it is determined that the original moving track prediction information exceeds the valid period, wherein the resided time length is a time length in which the terminal has resided on a target cell within a range of a target network node in the original moving track prediction information.

[0117] Determining whether the second updating condition is met comprises:

[0118] When a predicted next target network node or target cell in the original moving track prediction information does not match a next real network node or real cell actually switched by the terminal, it is determined that the original moving track prediction information does not match the real moving track of the terminal.

[0119] Determining whether the third updating condition is met comprises:

[0120] determining that the remaining predicted trajectory in the original mobile trajectory prediction information is insufficient when a remaining node quantity is less than a preset node quantity threshold or a remaining cell quantity is less than a preset cell quantity threshold, wherein the remaining node quantity or the remaining cell quantity is a quantity of target network nodes or target cells that are behind the first network node in the original mobile trajectory prediction information.

[0121] As a preferred implementation, the related information of the new mobile trajectory prediction information includes at least one of the following information: time information, reason information, real mobile trajectory information, and identification information of a second network node; wherein,

[0122] The time information is a generation time of the mobile trajectory prediction information and / or a generation time of the new mobile trajectory prediction information.

[0123] The reason information is a triggered mobile trajectory prediction update condition.

[0124] The real mobile trajectory information includes at least one of the following information: a real cell sequence within the first network node, a last real network node, a last real cell, a next real network node, and a next real cell; the real network node is a node actually entered by the terminal, and the real cell is a cell actually entered by the terminal.

[0125] As a preferred implementation, the first information sending module 21 is specifically configured to:

[0126] When a communication interface exists between the first network node and the second network node, sending first information to the second network node through the communication interface;

[0127] When a communication interface does not exist between the first network node and the second network node, forwarding the first information to the second network node through an intermediate network node having a communication interface.

[0128] By means of the technical solution of the embodiments of the present disclosure, in the multi-node terminal moving track prediction scenario, the condition for the intermediate network node to determine whether to update the prediction information is optimized, and the information interaction process between network nodes after the new prediction information is generated. After receiving the moving track prediction information predicted by the previous network node, the intermediate network node determines whether the original prediction information has become invalid according to the actual situation, and provides prediction information with higher and more reliable prediction accuracy in time in the case of invalidity or impending invalidity, effectively avoiding subsequent target network nodes from performing resource reservation or switching decision operations and the like based on the wrong prediction information. At the same time, after the new moving track prediction information is generated, the first information is sent to the network node from which the original moving track prediction information is generated, to inform the network node that the moving track prediction information has been updated and the related information of the new moving track prediction information, so that the network node can learn in time that its track prediction information is replaced by the prediction information of other nodes, and in the case of being replaced, the effective first information is acquired to perform iterative optimization of the prediction model deployed by the network node, and the network node can also be prevented from being in the state of waiting for the feedback of the real moving track information of other nodes for a long time, causing unnecessary resource waste, and effectively improving the cell switching performance and user experience.

[0129] It should be noted that the information transmission device provided by the embodiments of the present disclosure is used to execute all process steps of the information transmission method of the above-mentioned embodiments, and the working principles and beneficial effects of the two are one-to-one correspondence, so they will not be repeated here.

[0130] Referring to FIG. 6, which is a structural schematic diagram of an information transmission device provided by the embodiments of the present disclosure, the embodiments of the present disclosure further provide an information transmission device 30, which comprises a processor 31, a memory 32, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the information transmission method according to any one of the above-mentioned embodiments is implemented.

[0131] The embodiments of the present disclosure further provide a computer readable storage medium, which comprises a stored computer program, wherein when the computer program is running, the device where the computer readable storage medium is located executes the information transmission method according to any one of the above-mentioned embodiments.

[0132] The embodiments of the present disclosure further provide a computer program product, which comprises a computer program or computer instructions, and when the computer program or the computer instructions are executed by a processor, the information transmission method according to any one of the above-mentioned embodiments is implemented.

[0133] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing relevant hardware, and the program can be stored in a computer readable storage medium. When the program is executed, the program can include the processes of the above-mentioned embodiment methods. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM), a random access memory (RAM), or the like.

[0134] The above is the preferred embodiment of the present disclosure, and it should be pointed out that those skilled in the art can make several improvements and refinements without departing from the principles of the present disclosure, and these improvements and refinements are also considered within the protection scope of the present disclosure.

Claims

1. A method for transmitting information, applied to a first network node, comprising: transmitting first information to a second network node, wherein the second network node is a network node generating original mobile trajectory prediction information, and the first information comprises indication information indicating updated mobile trajectory prediction information and / or related information of the new mobile trajectory prediction information; and / or transmitting second information to a third network node, wherein the third network node is a network node located after the first network node in an actual mobile trajectory or a network node located after the first network node in the new mobile trajectory prediction information, and the second information comprises related information of the original mobile trajectory prediction information or related information of the new mobile trajectory prediction information. 2.The method according to claim 1, further comprising: generating related information of the new mobile trajectory prediction information when it is determined that a mobile trajectory prediction update condition is met; wherein the mobile trajectory prediction update condition is at least one of the following: a first update condition that the original mobile trajectory prediction information exceeds a valid period; a second update condition that the original mobile trajectory prediction information does not match a real mobile trajectory of a terminal; and a third update condition that a remaining prediction trajectory in the original mobile trajectory prediction information is insufficient; wherein the related information of the new mobile trajectory prediction information comprises a predicted target network node sequence, a target cell sequence within a range of each target network node, and / or a duration of terminal staying in each cell; wherein the first information comprises at least one of the following: time information, cause information, real mobile trajectory information, and identification information of the second network node; wherein the time information is a generation time of the original mobile trajectory prediction information and / or a generation time of the new mobile trajectory prediction information; the cause information is a triggered mobile trajectory prediction update condition; and the real mobile trajectory information comprises at least one of the following: a real cell sequence within a range of the first network node, a last real network node, a last real cell, a next real network node, and a next real cell; wherein the real network node is a node actually entered by the terminal, and the real cell is a cell actually entered by the terminal; and wherein the method further comprises: receiving original mobile trajectory prediction information of the terminal generated by the second network node, wherein the mobile trajectory prediction information comprises a predicted target network node sequence and / or a target cell sequence within a range of each target network node; determining whether the first update condition is met, comprising: determining that the original mobile trajectory prediction information exceeds the valid period when a stayed duration is greater than a preset valid duration of the original mobile trajectory prediction information, wherein the stayed duration is a duration of the terminal staying in a target cell within a range of a target network node in the original mobile trajectory prediction information; and determining whether the second update condition is met, comprising: determining that the original mobile trajectory prediction information does not match the real mobile trajectory of the terminal when a real cell sequence within a range of the first network node does not match a predicted target cell sequence within a range of a predicted target network node in the original mobile trajectory prediction information. ​ ​ ​ ​ ​ ​ ​ 3. The information transmission method of claim 1, wherein, ​ 4. The information transmission method of claim 1, wherein, ​ ​ ​ ​ 5. The information transmission method of claim 2, wherein, ​ ​ 6. The information transmission method of claim 2, wherein, ​ ​ 7. The information transmission method of claim 2, wherein, ​ When the next target network node or target cell predicted in the original mobile trajectory prediction information is inconsistent with the next real network node or real cell actually switched by the terminal, it is determined that the original mobile trajectory prediction information is inconsistent with the real mobile trajectory of the terminal.

8. The information transmission method of claim 2, wherein, The determining whether the third update condition is satisfied comprises: When the remaining node quantity is less than a preset node quantity threshold or the remaining cell quantity is less than a preset cell quantity threshold, it is determined that the remaining predicted trajectory in the original mobile trajectory prediction information is insufficient; wherein the remaining node quantity or the remaining cell quantity is the quantity of target network nodes or target cells after the first network node in the original mobile trajectory prediction information.

9. The information transmission method of claim 1, wherein, The sending of the first information to the second network node comprises: When there is a communication interface between the first network node and the second network node, sending the first information to the second network node through the communication interface; When there is no communication interface between the first network node and the second network node, forwarding the first information to the second network node through an intermediate network node having a communication interface.

10. The information transmission method according to any one of claims 1 to 9, wherein, The second network node can update the mobile trajectory prediction model deployed by itself according to the first information after receiving the first information. 11.An information transmission apparatus applied to a first network node, the apparatus comprising: a first information sending module configured to send first information to a second network node; wherein the second network node is a network node generating original mobile trajectory prediction information, and the first information comprises indication information indicating updated mobile trajectory prediction information and / or related information of new mobile trajectory prediction information; and / or, a second information sending module configured to send second information to a third network node; wherein the third network node is a network node after the first network node in an actual mobile trajectory or a network node after the first network node in new mobile trajectory prediction information, and the second information comprises related information of the original mobile trajectory prediction information or related information of the new mobile trajectory prediction information. 12.An information transmission device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the information transmission method according to any one of claims 1 to 10 when executing the computer program.

13. A computer readable storage medium comprising a stored computer program, wherein, The computer readable storage medium is controlled to perform the information transmission method according to any one of claims 1 to 10 when the computer program is running. 14.A computer program product comprising a computer program or computer instructions, wherein the computer program or the computer instructions implement the information transmission method according to any one of claims 1 to 10 when executed by a processor.

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