DETAILED ACTION
The non-final office action is responsive to the preliminary amendment filed on 02/06/2026. Claims 1-17 are pending; claims 1-17 are rejected.
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/03/2026 and 02/26/2025 were filed before the mailing date of the non-final office action. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claims 5 and 10 are objected to because of the following informalities: “and/or”. Appropriate correction is required. It is not clear the conjunction should be treated as “and” or “or”. As people with ordinary skill in the art would know that “and” is a type of coordinating conjunction and is commonly used to indicate a dependent relationship. Here, the two clauses are dependent on each other and both are true and take together. And “or” is another type of coordinating conjunction, but it indicates an independent relationship. Here, the two clauses are somewhat separate; while they are related, they are not co-dependent on each other. In terms of networking or software, “and” is used to indicate a function where both categories are met, whereas “or” indicates a function where either categories are met. Examiner will treat “and/or” as “or” for examination purpose.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-17 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication 2025/0287242 A1 to Soldatiet al. (hereinafter Soldati242) in view of U.S. Patent Application Publication 2025/0071029 A1 to Soldatiet al. (hereinafter Soldati029).
As to claim 1, Soldati242 teaches a communication method performed by a first communication apparatus (A method performed by a first network node (111) (e.g. claimed “a first communication apparatus”). The method is for handling one or more reports. The first network node (111) operates in a wireless communications network (100). The first network node (111) receives (604) a message, from at least one of a second network node (112) and one or more wireless devices (130) operating in the wireless communications network (100), Soldati242 Abstract), comprising:
obtaining a first function configured to evaluate a report of The sending in this Action 603 may be to the second network node 112, e.g., via the second link 142… The first message may comprise a first request to receive one or more reports. The one or more reports may comprise the respective information of the respective LCM of the one or more ML models available at least in part in at least one of the one or more wireless devices 130. The request may be, e.g., a subscription request, Soldati242, [0120]-[0135], Fig. 6);
Soldati242 does not explicitly the report being about resource consumed by a second communication apparatus.
Soldati029 discloses requesting a report about resource consumed by a second communication apparatus (Receiving a FIRST MESSAGE from a first network node, the FIRST MESSAGE comprising configurations/instructions/semantics information for verifying that an AI/ML model. Transmitting a SECOND MESSAGE to the first network node, the SECOND MESSAGE comprising a report associated with verifying an AIML model... An indication of whether the resources required by the model to be executed are not available at the second network node. In addition, the type of resource not satisfying the model's requirements can be specified, Soldati029, [0081]-[0106], [0203]-[0298]).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to report resource consumption as taught by Soldati029 to modify the method of Soldati242 in order to provide an ability to request, if needed, specific information to be used to train or execute the AI/ML algorithm and to avoid reception of unnecessary information.
Soldati242-Soldati029 discloses
determining, based on the first function and information about a first Al model, a first resource consumed by the second communication apparatus for executing the first Al model (Receiving a FIRST MESSAGE from a first network node, the FIRST MESSAGE comprising configurations/instructions/semantics information for verifying that an AI/ML model. Transmitting a SECOND MESSAGE to the first network node, the SECOND MESSAGE comprising a report associated with verifying an AIML model... An indication of whether the resources required by the model to be executed are not available at the second network node. In addition, the type of resource not satisfying the model's requirements can be specified, Soldati029, [0081]-[0106], [0203]-[0298]); and
determining, based on the first resource, whether to send first information to the second communication apparatus, wherein the first information comprises at least one of the first Al model or a manner of obtaining the first Al model (The performing in this Action 606 of the one or more actions uses the information comprised in at least one of the one or more reports. The one or more actions comprise at least one of: retraining or triggering a retraining of at least one of the one or more ML models, updating or triggering an update of at least one of the one or more ML models, deploying or triggering a deployment of an additional ML model, revoking or triggering a revocation of at least one of the one or more ML models, forwarding the one or more reports to the third network node 113 operating in the wireless communications network 100, and completing an ongoing procedure handled by the first network node 111, Soldati242, [0170]-[0178], Fig. 6).
As to claim 2, Soldati242-Soldati029 discloses the method according to claim 1, wherein the first function comprises at least one of:
a second Al model generated through training based on second information and third information (Soldati242, [0170]-[0178], Fig. 6);
a mapping function formed through fitting based on the second information and the third information; or
a mapping table obtained through statistics collection based on the second information and the third information, wherein
an input of the first function is related to the second information, an output of the first function is related to the third information, and the second information comprises at least one of the-information about an AI operator, information about an AI module, or information about a third AI model; and
the third information comprises at least one a resource consumed by a third communication apparatus for executing the AI operator, a resource consumed by a third communication apparatus for executing the AI module, or a resource consumed by a third communication apparatus for executing the third AI model, the third communication apparatus is the second communication apparatus or the third communication apparatus has a same first capability as the second communication apparatus, and the first capability is related to execution of the AI operator, the AI module, or the third AI model.
As to claim 3, Soldati242-Soldati029 discloses the method according to claim 2, wherein the information about the AI module comprises at least one of: type information of the AI module, a parameter of the AI module, information about front and rear modules of the AI module, or information about front and rear operators of the AI module; the information about the AI operator comprises at least one of444wig:type information of the AI operator, a parameter of the AI operator, information about front and rear operators of the AI operator, or information about front and rear modules of the AI operator; and the information about the third AI model comprises at least one ofthe4c+14ewing:a parameter of an overall structure of the third AI model or a parameter of a substructure of the third AI model (The message may comprise at least one of: a) the one or more first indications of the respective identifier or identity of the one or more ML models, b) the one or more second indications of the respective vendor of the one or more ML models, c) the one or more third indications of the respective version of the one or more ML models, d) the one or more fourth indications of the type of the one or more ML models, Soldati242, [0179]-[0229]).
As to claim 4, Soldati242-Soldati029 discloses the method according to claim 1, wherein the information about the first AI model comprises at least one of: information about an AI operator comprised in the first AI model, information about an AI module comprised in the first AI model, a parameter of an overall structure of the first AI model, or a parameter of a substructure of the first AI model (Soldati242, [0179]-[0229]; Soldati029, [0203]-[0298]).
As to claim 5, Soldati242-Soldati029 discloses the method according to claim 1, wherein the obtaining a first function comprises: receiving the first function; or receiving first indication information, and obtaining the first function based on the first indication information, wherein the first indication information comprises information indicating a manner of obtaining the first function, and/or an identifier of the first function (The first message may comprise a first request to receive one or more reports. The one or more reports may comprise the respective information of the respective LCM of the one or more ML models available at least in part in at least one of the one or more wireless devices 130. The request may be, e.g., a subscription request, Soldati242, [0120]-[0135], Fig. 6).
As to claim 6, Soldati242-Soldati029 discloses the method according to claim 1, wherein before the determining, based on the first resource, whether to send first information to the second communication apparatus, the method further comprises: receiving, from the second communication apparatus. at least one of processing resource indication information or second indication information, wherein the processing resource indication information indicates a proportion of processing resources that can be used by the second communication apparatus to execute the first AI model, and the second indication information indicates to adjust a value of a proportion of the first resource consumed by the second communication apparatus for executing the first AI model (Soldati242, [0179]-[0229], Fig. 7).
As to claim 7, Soldati242-Soldati029 discloses the method according to claim 6, wherein the determining, based on the first function and information about a first AI model, a first resource consumed by the second communication apparatus for executing the first AI model comprises: determining, based on the first function, the information about the first AI model, and at least one of the resource indication information or the second indication information, the first resource consumed by the second communication apparatus for executing the first AI model (Soldati029, [0081]-[0106], [0203]-[0298]). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to report resource consumption as taught by Soldati029 to modify the method of Soldati242-Soldati029 in order to provide an ability to request, if needed, specific information to be used to train or execute the AI/ML algorithm and to avoid reception of unnecessary information.
As to claim 8, Soldati242-Soldati029 discloses the method according to claim 1, wherein the method further comprises: obtaining a second function configured to evaluate a resource consumed by a fourth communication apparatus for executing an AI model (Soldati242, [0179]-[0229], Fig. 7. In view of Soldati029); determining, based on the second function and information about a fourth AI model, a second resource consumed by the fourth communication apparatus for executing the fourth AI model (Soldati029, [0081]-[0106], [0203]-[0298]); and when determining, based on the first resource, to send the first information to the second communication apparatus, and determining, based on the second resource, to send fourth information to the fourth communication apparatus, determining, based on the second function and the first function, a first task executed by the second communication apparatus and a second task executed by the fourth communication apparatus, wherein the first task and the second task meet a first rule (Soldati242, [0179]-[0229], Fig. 7).
As to claim 9, Soldati242-Soldati029 discloses the method according to claim 8, wherein the first rule comprises at least one of:
execution of the first task and execution of the second task are completed simultaneously;
execution of the first task and execution of the second task are completed based on a predefined time sequence (An indication of whether the execution of the AIML model (i.e., inference) meets the given execution time requirement(s), e.g., the average and/or maximum time for inference is/are below (a) specified threshold(s) for a certain test/verification dataset. If not, an indication of why and/or how much execution time of the AIML model violates the given requirement(s), for example, the execution time was exceeded by 0.1 ms on average and 0.5 ms at maximum due to (e.g., temporarily) limited compute resources, Soldati029, [0203]-[0298]). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to report resource consumption as taught by Soldati029 to modify the method of Soldati242-Soldati029 in order to provide an ability to request, if needed, specific information to be used to train or execute the AI/ML algorithm and to avoid reception of unnecessary information.
a preset time difference exists between a moment at which execution of the first task is completed and a moment at which execution of the second task is completed;
energy required for completing execution of the first task is equal to energy required for completing execution of the second task;
a proportion of energy required for completing execution of the first task to energy required for completing execution of the second task meets a preset proportion requirement; or
a preset energy difference exists between energy required for completing execution of the first task and energy required for completing execution of the second task.
As to claims 10-17, the same reasoning applies mutatis mutandis to the corresponding method claims 10-13 and apparatus claims 14-17 (Note: claimed processor and memory are disclosed by Soldati242 in [0377]). Accordingly, claims 10-17 are rejected under 35 U.S.C. 103 as being unpatentable over Soldati242 in view of Soldati029.
Conclusion
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/RUOLEI ZONG/Primary Examiner, Art Unit 2449 6/24/2026
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