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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/04/2025 has been considered by the examiner.
The information disclosure statement filed 12/04/2025 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. It has been placed in the application file, but the information referred to therein has not been considered.
Examiner is unable to locate legible copies for the following cited foreign patents:
CA3099659, WO2022122997 and WO202424608.
Various versions (with differing number of pages) of WO2019/216975 have been submitted as NPL documents along with the 12/04/2025 IDS.
Response to Arguments
Applicant’s arguments with respect to the art rejection of claims 1 and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim 1 has been amended (12/04/2025) to recite the limitations of claim 3 (Claim 3 was objected to as being dependent upon a rejected claim but “would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims”). Amended Claim 1 does not recite the limitations of claim 2 (an intervening claim).
The 12/04/2025 amendment to independent claim 1 overcomes the prior art rejection to Hirzallah et al. (U.S. 2024/0414500) of the 09/04/2025 Office Action.
The 12/04/2025 amendment to independent claim 20 overcomes the prior art rejection to Hirzallah et al. (U.S. 2024/0414500) of the 09/04/2025 Office Action.
Claim Objections
Claim 2 is objected to because of the following informality:
Claim 2, line the claimed “receiving the first group of KPIs” should be “receiving the group of KPIs”. Claim 1 claims “a group of KPIs” in lines 17-18 not “a first group of KPIs”.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 3-5, 8-9, 12, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (U.S. 2025/0048131) in view of Balevi et al. (U.S. 2024/0340660).
With respect to claim 1, Kumar et al. disclose:
a processing system including a processor (For example refer to the device of Fig. 9 which corresponds to network entity 105, lines 1-5 of [0194], and [0198] refer to the disclosed at least one processor (processing system including a processor)); and a memory that stores executable instructions that, when executed by the processing system ([0198] last sentence refer to the disclosed “and at least one memory…”), facilitate performance of operations (Fig. 9 and at least [0198] in particular the last sentence “at least one processor and at least one memory coupled with the at least one processor may be configured to perform one or more of the functions described herein”, , the operations ([0198] and functions of related Fig. 2-3 [0047]-[0048], and [0104]) comprising: identifying a service (e.g. refer to Fig. 3, in order to perform 310 the network node performs the identifying a service e.g. at least one of beam management, CSI feedback, positioning procedures as described in lines 6-20 of [0104], lines 4-7 of [0111], [0129] refer to the generating of the control signaling indicating a functionality ID (corresponding to the service)) associated with a communication device (the UE 115) which will activate (run) the ML models corresponding to the functionality ID, lines 9-13 of [0127], lines 4-7 of [0111]) ; determining a first functionality resulting in a first determination (the functionality whose ID is signaled to the UE); based on the first determination, generating first instructions for the communication device (310, and at least last sentence of [0129]), wherein the first instructions indicate to the communication device to use a first group of artificial intelligence (AI) models to implement the first functionality of the service (lines 4-7 of [0111], lines 7-10, [0113], lines 9-13 of [0127] as related to step 315 [0130] activation (running) of the ML models corresponding to (or associated with) the functionality ID);
and transmitting the first instructions to the communication device (310), wherein the communication device (the UE), in response to receiving the first instructions, selects the first group of Al models (315, lines 4-7 of [0111], lines 7-10, [0113], lines 9-13 of [0127]), wherein the communication device implements the first functionality of the service utilizing the first group of Al models (refer to the portions cited above),determining one or more first key performance indicators (KPIs) from a group of KPIs ([0131] and 320 and related [0114] refer to the “one or more performance metrics of the ML-based functionality”, [0115] in particular lines 5-end of [0115])does not satisfy a first performance criterion (lines 5-end of [0115] and 325) resulting in a second determination (failure to satisfy a corresponding threshold value or determination of experiencing performance degradation [0115]),wherein the group of KPIs is associated with the first functionality of the service (320, [0114]-[0115], [0131]-[0132], lines 1-5 switching to a different ML model-based functionality); based on the second determination, determining a second functionality resulting in a third determination (LCM operation 325, lines 11-16 of [0110], [0111], [0112]-[0113], [0134], lines 9-13 of [0127] e.g. 325 being a functionality-based LC operation of switching to a different ML- based functionality); based on the third determination, generating second instructions for the communication device (part of performing 330), wherein the second instructions indicate to the communication device to use a second group of Al models to implement the second functionality of the service (refer to the approximate middle of [0112], [0113] underlying ML models associated with the switched functionality, [0111], lines 1-13 of [0127] “process flow 300 describes an ML mode, but it is to be understood that the techniques described herein may be applicable to any type and quantity of ML…model, functionality…”); and transmitting the second instructions to the communication device (the LCM control message is transmitted to the UE), wherein: the communication device, in response to receiving the second instructions, selects the second group of Al models (lines 16-22 of [0110], [0111], lines 7-10 of [0112] refer to the “one or more underlying ML models that the UE 115-a runs to achieve the functionality…” and [0113] describing functionality-based LCM and also discloses “underlying ML models associated with the ML-based functionality” switched according to already cited portions of Kumar et al.) and the communication device (the UE) implements the second functionality of the service utilizing the second group of Al models (refer to at least the last sentence of [0109], 7-10 of [0112] refer to the “one or more underlying ML models that the UE 115-a runs to achieve the functionality…”, approximate second half of [0137]).
Kumar et al. do not disclose: a first functionality from a group of functionalities associated with the service; a first group of artificial intelligence (AI) models from a plurality of groups of Al models, from the plurality of groups of Al models, a second functionality from the group of functionalities associated with the service, a second group of AI models from the plurality of groups of Al models, from the plurality of groups of Al models.
In the same field of endeavor, Balevi et al. disclose: a first functionality from a group of functionalities associated with a service ([0041] AI/ML feature corresponds to a service and corresponds to multiple functionalities (a group of functionalities), [0107]); a first group of artificial intelligence (AI) models from a plurality of groups of Al models ([0041], [0107], [0110] e.g. 2 groups of ML models 812&814 and 818&820 corresponding to a first functionality and a second functionality for the service, the first and second functionality provide alternative functionality), from the plurality of groups of Al models (when the first or second functionality is selected the respective plurality of ML models is selected from the plurality of groups of ML models), a second functionality from the group of functionalities associated with the service (refer to the functionality which is the alternative functionality, [0107]-[0110]) , a second group of AI models from the plurality of groups of Al models (the second group of AI models of the (second) functionality which is the alternative functionality, alternative to the first functionality), from the plurality of groups of Al models (the second group of AI models of the (second) alternative functionality).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kumar et al. based on the cited teachings of Balevi et al. to perform the determining a first functionality from a group of functionalities associated with the service (e.g. from a group of two functionalities, the other (second) functionality being an alternative functionality), to indicate to the communication device to use a first group of artificial (AI) models from a plurality of groups of Al models (the plurality of groups of AI modes of the first and second functionalities), perform determining a second functionality from the group of functionalities associated with the service (the switched functionality is selected from the group of the first functionality and second (alternative) functionality), indicate to the communication device to use a second group of AI models from the plurality of groups of Al models (the group of AI models of the alternative (switched or second) functionality), the communication device to select (to perform the selects) the second group of AI models from the plurality of groups of Al models (the second group of AI models is selected from the plurality of groups of AI models (of the first functionality and the second (alternative) functionality).
The motivation for one of ordinary skill in the art before the effective filing date of the claimed invention includes implementing dynamic capabilities with respect to features supported by a UE and managed by a network entity (e.g. base station of Kumar et al.) according to the disclosed relations between a service (feature) corresponding functionalities and corresponding AI/ML models (Balevi et al. [0040]-[0042], [0107]-[0110], Kumar et al. at least [0128]).
With respect to claim 3, modified Kumar et al. disclose: wherein the group of KPIs comprises one or more of channel state information (CSI), beam measurement report information, or reliability metrics (at least reliability metrics are disclosed in [0114] “one or more performance metrics” e.g. MMSE error metric, packet loss value, error rate).
With respect to claim 4, modified Kumar et al. disclose: wherein the first performance criterion is associated with a performance of the service ([0115] in particular lines 1-8).
With respect to claim 5, modified Kumar et al. disclose wherein the service comprises channel state information (CSI) prediction (lines 9-12 of [0104], ML models used for CSI feedback, (predict the CSI), [0003] refer to the “predictive models …e.g. machine learning (ML) models to perform one or more functions”, lines 1-10 of [0056]).
With respect to claim 8, modified Kumar et al. disclose: wherein the first performance criterion is based on CSI (lines 9-12 of [0104], ML models used for CSI feedback, (predict the CSI), [0003] refer to the “predictive models …e.g. machine learning (ML) models to perform one or more functions”, lines 1-10 of [0056]. When implementing ML CSI prediction, the first performance criterion of [0114]-[0115] is understood to be based on CSI (prediction)).
With respect to claim 9, modified Kumar et al. disclose: wherein the service comprises beam prediction (lines 9-12 of [0104], ML models used for beam management (beam prediction)), [0003] refer to the “predictive models …e.g. machine learning (ML) models to perform one or more functions”, lines 1-10 of [0056]).
With respect to claim 12, modified Kumar et al. disclose: wherein the first performance criterion is based on beam measurement report information (lines 9-12 of [0104], ML models used for beam management (beam prediction)), [0003] refer to the “predictive models …e.g. machine learning (ML) models to perform one or more functions”, lines 1-10 of [0056]. When implementing ML beam management, the first performance criterion of [0114]-[0115] is understood to be based on beam measurement report information).
With respect to claim 20, Kumar et al. disclose: generating, by a processing system including a processor (For example refer to the device of Fig. 9 which corresponds to network entity 105, lines 1-5 of [0194], and [0198] refer to the disclosed at least one processor (processing system including a processor). Additionally refer to related Fig. 2-3); first instructions for a communication device (e.g. 310 of Fig. 3, [0129]), wherein the first instructions indicate to the communication device to use a first group of artificial intelligence (AI) models (lines 9-13 of [0127], last sentence of [0109], lines 7-10 of [0112]) to implement a first functionality of a service ([0128], [0129], lines 10-16 of [0104] e.g. one of beam management, CSI prediction or mobility optimization corresponds to a service); and transmitting, by the processing system (network node device of Fig. 9 (105-b in Fig. 3), the first instructions to the communication device (the UE), wherein the communication device, in response to receiving the first instructions, selects the first group of AI models (refer to the paragraphs cited above, the UE activates (runs) the ML models to achieve (perform) the functionality), and wherein the communication device implements the first functionality of the service utilizing the first group of AI models (refer above); generating second instructions (the generating the selection of LCM operation 325, [0111] in particular the last sentence, [0113], [0115], lines 1-5 of [0133], lines 9-14 of [0127]) for the communication device (for the UE of Fig. 3), wherein the second instructions indicate to the communication device to use a second group of AI models to implement a second functionality of the service (refer to the approximate middle of [0112], [0113] underlying ML models associated with the switched functionality, [0111], lines 1-13 of [0127] “process flow 300 describes an ML mode, but it is to be understood that the techniques described herein may be applicable to any type and quantity of ML…model, functionality…”); and transmitting the second instructions to the communication device (330), wherein: the communication device (the UE) , in response to receiving the second instructions, selects the second group of AI models (lines 16-22 of [0110], [0111], lines 7-10 of [0112] refer to the “one or more underlying ML models that the UE 115-a runs to achieve the functionality…” and [0113] describing functionality-based LCM and also discloses “underlying ML models associated with the ML-based functionality” switched according to already cited portions of Kumar et al.), and the communication device implements the second functionality of the service utilizing the second group of AI model (refer to at least the last sentence of [0109], 7-10 of [0112] refer to the “one or more underlying ML models that the UE 115-a runs to achieve the functionality…”, approximate second half of [0137]).
Kumar et al. do not disclose: a first group of artificial intelligence (AI) models from a plurality of groups of Al models, from the plurality of groups of Al models, a second group of AI models from the plurality of groups of Al models, from the plurality of groups of Al models.
In the same field of endeavor, Balevi et al. disclose: a first group of artificial intelligence (AI) models from a plurality of groups of Al models ([0041], [0107], [0110] e.g. 2 groups of ML models 812&814 and 818&820 corresponding to a first functionality and a second functionality for the service, the first and second functionality provide alternative functionality), from the plurality of groups of Al models (when the first or second functionality is selected the respective plurality of ML models is selected from the plurality of groups of ML models), a second group of AI models from the plurality of groups of Al models (the second group of AI models of the (second) functionality which is the alternative functionality, alternative to the first functionality), from the plurality of groups of Al models (the second group of AI models of the (second) alternative functionality).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kumar et al. based on the cited teachings of Balevi et al. to use a first group of artificial (AI) models from a plurality of groups of Al models (the plurality of groups of AI modes of the first and second functionalities), the second instructions indicate to the communication device to use a second group of AI models from the plurality of groups of Al models (to use the group of AI models of the alternative (second) functionality out of the group of AI models of the first and second functionalities), the communication device to perform the selects the second group of AI models from the plurality of groups of Al models (the second group of AI models is selected from the plurality of groups of AI models (of the first functionality and the second (alternative) functionality).
The motivation for one of ordinary skill in the art before the effective filing date of the claimed invention includes implementing dynamic capabilities with respect to features supported by a UE and managed by a network entity (e.g. the base station of Kumar et al) according to the disclosed relations between a service (feature) corresponding functionalities and corresponding AI/ML models (Balevi et al. [0040]-[0042], [0107]-[0110], Kumar et al. at least [0128]).
Allowable Subject Matter
Claims 15-18 are allowed.
Claims 2, 6-7, 10-11, 13-14 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
CA 3099659, WO 2022122997, WO 2024242608
Shrivastava et al. (U.S. 2025/0056249) refer to at least [0037]-[0039].
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.
Contact Information
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SOPHIA VLAHOS
Examiner
Art Unit 2633
/SOPHIA VLAHOS/Primary Examiner, Art Unit 2633 3/2/2026