A system and method of optimizing a 5g network

Abstract

Disclosure relates to a system to optimize a 5G network. The system may comprise a wireless communication network, a generation Node B (gNB) and at least one user equipment (UE). The gNB and the at least one UE are in wireless communication via the wireless communication network. The gNB is operable to configure a dataset mapping table. The dataset mapping table includes at least one dataset collection parameter. The gNB is further operable to transmit a wireless signal to the at least one UE via the wireless communication network. The wireless signal containing the at least one dataset collection parameter. in response to the wireless signal containing the at least one dataset collection parameter received by the at least one UE, the at least one UE is operable to execute a dataset collection process to collect a type of dataset corresponding to at least one dataset collection parameter. A method of the same is also disclosed.

Description

2024016661A SYSTEM AND METHOD OF OPTIMIZING A 5G NETWORKFIELD OF INVENTION

[0001] This disclosure relates to wireless communication network, and in particular, a system and method for optimizing signalling processes for a wireless communication network using data collection for training a global model.BACKGROUND

[0002] Existing techniques in 3rd Generation Partnership Project (3GPP) 5G (fifth generation) New Radio (NR) standard-based telecommunications network does not address excessive overhead signalling and unnecessary energy consumption. Increasingly, efforts towards development of 3GPP NR explores the role of training a global model to address such issues, with an objective of facilitating energy efficiency and power saving in an optimal manner.

[0003] This disclosure contemplates that it would be helpful to address or at least mitigate one or more issues in relation to conventional techniques for facilitating energy efficiency and power saving when training a global model.SUMMARY

[0004] A purpose of this disclosure is to ameliorate the problem of facilitating energy efficiency and power saving of a 3GPP 5G network when training a global model.

[0005] In an aspect of this disclosure, a method for optimizing a 5G network is provided. The method may comprise configuring, by way of a gNB, a dataset mapping table, the dataset mapping table comprising at least one dataset collection parameter. The method may further comprise transmitting, by way of the gNB, a wireless signal containing the at least one dataset collection parameter to at least2024016662 one user equipment (UE) in a wireless communication network. In response to receiving the signal containing the at least one dataset collection parameter by at least one UE in the network, executing, by way of the at least one UE, a dataset collection process for collecting a type of dataset corresponding to the at least one dataset collection parameter.

[0006] In some embodiment, the method may comprise mapping, by way of the gNB, the dataset type index to a corresponding model ID. In some embodiment, the method may comprise mapping, by way of the gNB, the dataset type index to a corresponding dataset type.

[0007] In some embodiment, in response to the dataset collection process executed, transmitting via the wireless communication network, by way of the at least one UE, at least one data packet containing the at least one dataset collection parameter collected by the at least one UE to the gNB.

[0008] In some embodiment, the dataset type index may be a predefined index. In some embodiment, the predefined index may correlate to a predetermined artificial intelligence I machine learning (AIML) learning model specific dataset 110. In some embodiment, the at least one dataset collection parameter may be a dataset type index.

[0009] In all of the above embodiments, transmitting the wireless signal from the gNB to the at least one UE may be selected from a network communication mode. In some embodiment, the network communication mode may be a system information broadcast message. In some embodiment, the network communication mode may be a UE specific message. In some embodiment, the network communication mode may be a L1 / L2 signalling. In some embodiment, the network communication mode may be a Medium Access Control Element (MAC CE). It shall be understood by a skilled practitioner, other suitable variation of network communication mode having the same technical characteristics may be applicable, but not limited thereto.2024016663

[0010] In an aspect of this disclosure, a computer program product is provided, the computer program product may comprise instructions stored thereon which, when executed by a computer, may cause the computer to carry out at least one of the steps according to the method as disclosed herein.

[0011] In an aspect of this disclosure, a computer-readable storage medium having data stored thereon is provided.

[0012] In an aspect of this disclosure, a system to optimize a 5G network. The system may comprise a wireless communication network, a generation Node B (gNB), and at least one user equipment (UE). The gNB and the at least one UE may be in wireless communication via the wireless communication network. The gnB may be operable to configure a dataset mapping table The dataset mapping table may comprise at least one dataset collection parameter. The gNB may be operable to transmit a wireless signal to the at least one UE via the wireless communication network, of which the wireless signal containing the at least one dataset collection parameter. In response to the wireless signal containing the at least one dataset collection parameter received by the at least one UE, the at least one UE may be operable to execute a dataset collection process to collect a type of dataset corresponding to at least one dataset collection parameter.

[0013] In some embodiment, the dataset mapping table may comprise at least one dataset collection parameter. In some embodiment, the at least one dataset collection parameter may comprise a model ID. In some embodiment, the at least one dataset collection parameter may comprise a dataset type index. In some embodiment, the collection parameter may comprise a type of dataset required for the model ID.

[0014] Other objects, features and characteristics, as well as the models of operation and the functions of the related elements of the structure the combination of parts and economics of manufacture will become more apparent upon consideration of the following detailed description and appended claims with reference to the accompanying drawings, all of which form a part of this2024016664 specification. It should be understood that the detailed description and specific examples, while indicating the non-limiting embodiments of the disclosure, are intended for purposes of illustration only and are not intended to limit the scope of the disclosure.BRIEF DESCRIPTION OF DRAWINGS

[0015] This disclosure will become more fully understood from the detailed description and the accompanying drawings, wherein:FIG. 1 shows a 5G network in accordance with an embodiment.FIG. 2 shows a dataset mapping table in accordance with an embodiment.FIG. 3 shows a flowchart of a method in accordance with an embodiment.DETAILED DESCRIPTION OF EMBODIMENTS

[0016] The following detailed description is merely exemplary in nature and is not intended to limit the disclosure or the application and uses of the disclosure. Furthermore, there is no intention to be bound by any theory presented in the preceding background of the disclosure or the following detailed description. It is the intent of this disclosure to present a system for performing the operations of the methods disclosed herein. Such system may be specially constructed for the required purposes or may comprise a computer or other device selectively activated or reconfigured by a computer program stored in the computer. The algorithms presented herein are not inherently related to any particular computer or other apparatus. Various machines may be used with programs in accordance with the teachings herein. Alternatively, the construction of more specialized apparatus to perform the required method steps may be appropriate. The structure of a computer will appear from the description below.2024016665

[0017] In addition, the present specification also implicitly discloses a computer program, in that it would be apparent to the person skilled in the art that the individual steps of the method described herein may be put into effect by computer code. The computer program is not intended to be limited to any particular programming language and implementation thereof. It will be appreciated that a variety of programming languages and coding thereof may be used to implement the teachings of the disclosure contained herein. Moreover, the computer program is not intended to be limited to any particular control flow. There are many other variants of the computer program, which can use different control flows without departing from the spirit or scope of the disclosure.

[0018] Furthermore, one or more of the steps of the computer program may be performed in parallel rather than sequentially. Such a computer program may be stored on any computer readable medium. The computer readable medium may include storage devices such as magnetic or optical disks, memory chips, or other storage devices suitable for interfacing with a computer. The computer readable medium may also include a hard-wired medium such as exemplified in the Internet system, or wireless medium such as exemplified in the mobile telephone system. The computer program when loaded and executed on such a computer effectively results in an apparatus that implements the steps of the preferred method.System 100

[0019] Turning now to the accompanying drawings, FIG. 1 shows system 100 of a 5G network 100 in accordance with an embodiment. The system 100 includes a base station also known as a next generation Node B (gNB) 102. The system 100 further includes one or more user equipment (UE) 104, 104’, 104”. Examples of UE may include a motor vehicle, a mobile device, but not limited thereto. In the embodiments described herein, the mobile device may include a wireless communication device such as a smartphone, a smartwatch, a laptop, a personal digital assistant but not limited thereto.2024016666

[0020] The gNB 102 and the at least one UE 104, 104’, 104” may be in wireless communication through a wireless network 106. Henceforth, the gNB 102 and each of the at least one UE 104, 104’, 104” are operable to exchange information data or wireless signals through transmitting and receiving one or more wireless signals through the wireless communication network 106 in all of the embodiments discussed herein, the gNB 102 includes a computer 108. In all of the embodiments discussed herein, each of the at least one UE includes a computer 108’. Each of the computer 108, 108’ may possess characteristics as discussed above.

[0021] In some embodiment, the gNB 102 may be operable to configure a dataset mapping table, the dataset mapping table may comprise at least one dataset collection parameter. The gNB 102 may be further operable to transmit a wireless signal to the at least one UE 104, 104’, 104”, the wireless signal containing the at least one dataset collection parameter.

[0022] In response to the wireless signal containing the at least one dataset collection parameter received by the at least one UE 104, 104’, 104” via the wireless communication network 106, the at least one UE 104, 104’, 104” may be operable to execute a data collection process to collect a type of dataset corresponding to at least one dataset collection parameter.

[0023] In all of the embodiments discussed herein, the transmitting and receiving of the wireless signals between the gNB 102 to the at least one UE 104, 104’, 104” via the wireless communication network 106 may be in the form of a network communication mode. In some embodiment, the network communication mode may be a system information broadcast message. In some embodiment, the network communication mode may be a UE specific message. In some embodiment, the network communication mode may be a L1 / L2 signalling. In some embodiment, the network communication mode may be a Medium Access Control Element (MAC CE).2024016667Dataset Mapping Table

[0024] FIG. 2 shows a dataset mapping table 200 in accordance with an embodiment. The dataset mapping table 200 configures a dataset type index for the at least one UE 104, 104’, 104” such that each of the at least one UE 104, 104’, 104” identifies a type of dataset to collect. Advantageously, this may facilitate energy efficiency and power saving by determining the type of dataset a UE is required to collect and provide to the gNB for model inference.

[0025] The dataset mapping table 200 includes one or more dataset collection parameter 202. The one or more dataset collection parameter 202 may include a model identity (ID) 204, a dataset type index 206, a dataset type 208, but not limited thereto.

[0026] In some embodiment, the dataset mapping table 200 may be configured as dataset type index 206 for a specific model ID 204 and the type of dataset 208 required of the specific model ID 204.

[0027] In some embodiment, the dataset type 208 may be a pre-defined index which correlates to an AIML model specific dataset. In some embodiment, the dataset type 208 may be a type of dataset suitable for a particular dataset type index 206.

[0028] FIG. 3 shows a flowchart of a method 300a in accordance with an embodiment. At step 302, a gNB 102 configures a data mapping table, the dataset mapping table comprising at least one dataset collection parameter. In a next step 304, the gNB 102 transmits a wireless signal containing the at least one dataset collection parameter to at least one user equipment (UE) in a wireless communication network.

[0029] In response to receiving the signal containing the at least one dataset collection parameter by at least one UE in the network, the at least one UE executes a dataset collection process for collecting a type of dataset corresponding to the at least one dataset collection parameter at step 306.2024016668

[0030] The configuration of the dataset mapping table includes mapping 308 of dataset collection parameters. In some embodiment, the gNB may map the dataset type index to a corresponding model ID. In some embodiment, the gNB may map the dataset type index to a corresponding dataset type. The dataset type index may be a predefined index. The predefined index correlates to a predetermined artificial intelligence I machine learning (AMIL) model specific dataset.

[0031] In response to the dataset collection process executed at step 306, the at least one UE 104, 104’, 104” commence transmitting at least one data packet containing the at least one dataset collection parameter collected by the at least one UE 104, 104’, 104” to the gNB 102 via the wireless communication network at step 310.

[0032] A main advantage of this disclosure is the configuration of a dataset mapping table by a gNB for determining types of datasets to be collected by one or more UE, to achieve efficiency by providing correct dataset to the gNB for model inference, thereby reducing power consumption.

[0033] The foregoing description shall be interpreted as illustrative and not be limited thereto. One of ordinary skill in the art would understand that certain modifications may come within the scope of this disclosure. Although the different non-limiting embodiments are illustrated as having specific components or steps, the embodiments of this disclosure are not limited to those combinations. Some of the components or features from any of the non-limiting embodiments may be used in combination with features or components from any of the other non-limiting embodiments. For these reasons, the appended claims should be studied to determine the true scope and content of this disclosure.2024016669List of Reference Signs100 System of a 5G network102 Base station or gNB104, 104’, 104” user equipment (UE)106 Wireless communication network108, 108’ Computer110 Dataset for computer200 Dataset mapping table202 At least one dataset collection parameter204 Model identity (ID)206 Dataset type index208 Dataset type300 Method302 Configure dataset mapping table304 Transmitting wireless signal by gNB306 Executing dataset collection process by at least one UE308 Mapping the dataset type index310 Transmitting dataset collection parameter from UE to gNB

Claims

20240166610Patent claims1 . A method (300) for optimizing a 5G network, the method (300) comprising: configuring (302), by way of a gNB, a dataset mapping table, the dataset mapping table comprising at least one dataset collection parameter; transmitting (304), by way of the gNB, a wireless signal containing the at least one dataset collection parameter to at least one user equipment (UE) in a wireless communication network; and in response to receiving the signal containing the at least one dataset collection parameter by at least one UE in the network, executing (306), by way of the at least one UE, a dataset collection process for collecting a type of dataset corresponding to the at least one dataset collection parameter.

2. The method (300) according to claim 1 , the method comprising: mapping (308), by way of the gNB, the dataset type index to• a corresponding model ID;• a corresponding dataset type, or combination thereof.

3. The method (300) according to claims 1 -2, the method comprising: in response to the dataset collection process executed, transmitting (310) via the wireless communication network, by way of the at least one UE, at least one data packet containing the at least one dataset collection parameter collected by the at least one UE to the gNB.

4. The method (300) according to claims 1 -3, wherein the dataset type index may be a predefined index.202401666115. The method (300) according to claim 4, wherein the predefined index correlates to a predetermined artificial intelligence / machine learning (AIML) model specific dataset.

6. The method (300) according to claims 1 - 5, wherein the at least one dataset collection parameter is a dataset type index.

7. The method (300) according to any one of the preceding claims, wherein transmitting the wireless signal from the gNB to the at least one UE is selected from a network communication mode consisting of:• a system information broadcast message;• a UE specific message;• a L1 / L2 signalling;• Medium Access Control Element (MAC CE), and combination thereof.

8. A computer program product comprising instructions stored thereon which, when the program is executed by a computer, cause the computer to carry out at least one of the steps according to the method (300) of claims 1 - 7.

9. A computer-readable storage medium having data stored thereon the computer program of claim 8.

10. A system (100) to optimize a 5G network, the system (100) comprising: a wireless communication network (106); a gNB (102); at least one user equipment (UE) (104, 104’, 104”), the gNB (102) and the at least one UE (104, 104’, 104”) in wireless communication via the wireless communication network (106), wherein the gNB (102) is operable to: configure a dataset mapping table (200), the dataset mapping table (200) comprising at least one dataset collection parameter (202);20240166612 and transmit a wireless signal to the at least one UE (104, 104’, 104”), via the wireless communication network (106), the wireless signal containing the at least one dataset collection parameter (202).11 . The system (100) according to claim 10, wherein in response to the wireless signal containing the at least one dataset collection parameter received by the at least one UE, the at least one UE is operable to execute a dataset collection process to collect a type of dataset corresponding to at least one dataset collection parameter.

12. The system (102) according to claims 10 - 11 , wherein the dataset mapping table (200) comprises at least one dataset collection parameter (202), the at least one dataset collection parameter (202) comprises: a model ID (204); a dataset type index (206); a type of dataset (208) required for the model ID , or combination thereof.

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