DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Final rejection is in response to the amendment filed on 5/21/2026.
Claims 1-20 are pending. Claims 1 and 13 are currently amended. Claims 1 and 13 are independent claims.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Pravinchandra Bhatt et al. (US 2023/0344652 A1, hereinafter Bhatt) in view of Wu et al. (US 2021/0184989 A1, hereinafter Wu).
Regarding claim 1, Bhatt teaches a method, comprising:
identifying, by a Service Management and Orchestration (SMO) framework, at least one data model to manage an artificial intelligence or machine learning (AI/ML) model deployed in a Network Function (NF) via at least one management function, [Abstract describes AI model deployed on the device that hosts the network function, certificate update trigger for a network function (data model) using AI/ML model; Par,[0045] describes CUO as part of SMO and NMS for management functions];
receiving, by the SMO framework, AI/ML associated data from the NF via the at least one management function according to the data model, [Abstract, Par.[0043], [0046] receives information (in this case about certificate update procedure) from a NF to use an associated AI/ML model; Figurers 2 and 3 and associated description];
updating, by the SMO framework, a network configuration based on the AI/ML associated data, [Par.[0047] among others describes update to network configurations based on certificate update schedule using AI/ML model; Par.[0064] The CUO can apply the AI/ML model 210 to determine an optimum schedule for certificate updates for network function]; and
transmitting, by the SMO framework, the updated network configuration to the NF to control wireless communications, [Par.[0048] among others describes CUO/SMO triggers the network function to perform certificate updates based on updated schedule; see Figures 4, 6 among others];
Bhatt does not explicitly teach wherein the at least one management function manages the AI/ML model deployed in the NF, updates the AI/ML model, and monitors a performance of the AI/ML model;
Wu, in an analogous art teaches wherein the at least one management function manages the AI/ML model deployed in the NF, updates the AI/ML model, and monitors a performance of the AI/ML model, [Abstract describes managing, monitoring, and updating the ML models];
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to augment Bhatt. The motivation/suggestion would have been to include data-centric network architecture that provides data plane functions (DPFs) that serve as a shared database for control functions, user functions and management functions for data plane resources in a network, [Wu: Abstract].
Claim 13 corresponds to claim 1 and Figure 1, 4-7 show various system related elements.
Regarding claim 2, Bhatt and Wu teach the method of claim 1, and Bhatt teaches wherein the at least one data model comprises at least one of a configuration data model, a performance data model, or a fault data model, wherein the configuration data model comprises at least one AI/ML configuration parameter, [Abstract, Par.[0043], [0046] receives configuration related information (in this case about certificate update procedure) from a NF to use an associated AI/ML model to determine a schedule (configuration parameter)], wherein the performance data model comprises at least one AI/ML performance measurement indication, [notice that the certificate update procedure may relate to performance also as in Par.[0050] monitoring network performance parameters], and wherein the fault data model comprises at least one AI/ML fault indication, [notice that the certificate update procedure may relate to fault/failure also due to expiration and unavailability].
Regarding claim 3, Bhatt and Wu teach the method of claim 2, and Bhatt teaches further comprising: updating the at least one AI/ML configuration parameter based on the AI/ML associated data, [Par.[0043] update schedule using AI/ML model; and
transmitting the at least one AI/ML configuration parameter to the NF to apply the at least one AI/ML configuration parameter to the AI/ML model using an online model update, an offline model update, or an external framework, [Par.[0046] describes CUO/DB to train the AI/ML model for predicting the time/schedule required for updating certificates; Par.[0064] The CUO can apply the AI/ML model 210 to determine an optimum schedule for certificate updates for various network functions; see also Par.[0055]. [0059] for a framework to train/update AI/ML model].
Regarding claim 4, Bhatt and Wu teach the method of claim 1, and Bhatt teaches wherein the at least one data model comprises an AI/ML data model, and wherein the AI/ML data model comprises at least one AI/ML configuration parameter, [Abstract, Par.[0043], [0046] receives configuration related information (in this case about certificate update procedure) from a NF to use an associated AI/ML model to determine a schedule (configuration parameter)], at least one AI/ML performance measurement indication. [notice that the certificate update procedure may relate to performance also as in Par.[0050] monitoring network performance parameters], and at least one AI/ML fault indication, [notice that the certificate update procedure may relate to fault/failure also due to expiration and unavailability].
Regarding claim 5, Bhatt and Wu teach the method of claim 4, and Bhatt teaches wherein the at least one management function comprises a management function to use the at least one AI/ML configuration parameter, the at least one AI/ML performance measurement indication, and the at least one AI/ML fault indication, [claim is not clear about what management function does and is interpreted as managing AI/ML model meaning training and updating the model itself, in addition to the citation in claim 4, see Par.[0054], [0055], [0059], [0064] about training and updating the AI/ML model].
Regarding claim 6, Bhatt and Wu teach the method of claim 4, and Bhatt teaches wherein the at least one management function comprises a plurality of management functions corresponding to the at least one AI/ML configuration parameter, the at least one AI/ML performance measurement indication, and the at least one AI/ML fault indication, [claim is not clear about what management function does and is interpreted as CUO/SMO managing AI/ML model meaning training and updating the model itself, in addition to the citation in claim 4, see Par.[0054], [0055], [0059], [0064] about training and updating the AI/ML model].
Regarding claim 7, Bhatt and Wu teach the method of claim 1, and Bhatt teaches, further comprising: receiving network operation information from the NF, wherein the updated network configuration is further determined based on the network operation information, [Abstract and elsewhere from the citations above, certificate information (network operation from the NF) and CUO/SMO determines a schedule for triggering certificate update (updated network configuration)].
Regarding claim 8, Bhatt and Wu teach the method of claim 1, and Bhatt teaches, further comprising: training a second AI/ML model associated with the AI/ML model, re-training the AI/ML model, or using a different trained version of the AI/ML model based on the AI/ML associated data to determine the updated network configuration associated with the AI/ML model, [claim recited in the alternative; see Par.[0054], [0055], [0059], [0064] about training and updating the AI/ML model].
Regarding claim 9, Bhatt and Wu teach the method of claim 1, and Bhatt teaches, further comprising: registering the at least one management function associated with the AI/ML model in a service registry of the SMO framework to be discovered by a service consumer, [Par.[0045] CUO acts as part of a management function installed in SMO framework for managing certificate updates using an associated AI/ML model; CA/RA in Figure 1 and Par.[0052] for service consumer aspect of an operator].
Regarding claim 10, Bhatt and Wu teach the method of claim 9, and Bhatt teaches, further comprising: managing authorization of the service consumer to access the at least one data model, CA/RA in Figure 1 and Par.[0052] The system 100 may also comprise a certification authority (CA) or registration authority (RA) 150 of an operator. The CA/RA 150 may transmit an announcement about certificate revocation to the CUO 110. The network functions 130 may execute certificate update procedure with the CA/RA].
Regarding claim 11, Bhatt and Wu teach the method of claim 1, and Bhatt teaches, wherein the NF comprises a physical network function, and wherein transmitting the updated network configuration using an adapter in the SMO framework, [Par.[0046] describes network functions may be physical network functions and Par.[0048] describes CUO/SMO triggers the network functions to perform certificate updates based on updated schedule; see Figures 4, 6].
Regarding claim 12, Bhatt and Wu teach the method of claim 1, and Bhatt teaches, wherein the NF is a first network function of a radio access network (RAN) or a second network function of a core network, [Figure 1 and Par.[0045]].
Claim 14 corresponds to claim 2 and is rejected as above.
Claim 15 corresponds to claim 3 and is rejected as above.
Claim 16 corresponds to claim 5 and is rejected as above.
Claim 17 corresponds to claim 6 and is rejected as above.
Claim 18 corresponds to claim 7 and is rejected as above.
Claim 19 corresponds to claim 8 and is rejected as above.
Claim 20 corresponds to claims 9 and 10 together and is rejected as above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/PADMA MUNDUR/Primary Examiner, Art Unit 2443
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