DETAILED ACTION
This Office Action is in response to the Preliminary Amendment filed on 11 March 2026.
Claims 2-8 are presented for examination.
Claims 2-8 are new.
Claim 1 is canceled.
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 3 October 2024. 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 2-8 is/are objected to because of the following informalities:
Claim 2, line 2 recites the acronym “UE”. The acronym should be written out before the acronym is used and the acronym should be in parenthesis the first time it is used.
Claim 2, line 4 recites the acronym “AI/LM”. The acronym should be written out before the acronym is used and the acronym should be in parenthesis the first time it is used.
Claim 2, line 6 recites the acronym “RRC. The acronym should be written out before the acronym is used and the acronym should be in parenthesis the first time it is used.
Appropriate correction is required.
Dependent claims 3-8 are also objected to since they are dependent upon the objected to claims set forth above.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 2 and 7 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Park et al (KR 10-2023-0069210), where English Language of the convenient translation of (US 2024/0284314 A1), per MPEP 901.05.
Regarding Claim 2, Park discloses a method performed by a terminal (see Figure 1, UE 120), the method comprising:
receiving (see Figures 1 and 4, step S310 and paragraphs 68 and 80; receiving/base station 110 transmits), from a base station (see Figures 1 and 4, step S310 and paragraphs 68 and 80; from a base station/base station 110), a UE capability enquiry message (see Figures 1 and 4, step S310 and paragraphs 68 and 80; a UE capability enquiry message/UE capability enquiry);
transmitting (see Figures 1 and 4, step S330 and paragraphs 69 and 80; transmitting/UE 120 reports), to the base station (see Figures 1 and 4, step S330 and paragraphs 69 and 80; to the base station/base station 110), a UE capability information message comprising capability information on AI/ML features or models supported by the terminal (see Figures 1 and 4, step S330 and paragraphs 69-70 and 80; a UE capability information message/(UE capability information) comprising/include capability information on AI/ML features or models/(configuration information supported for each AI/ML functionality) supported/supported by the terminal/UE 120), in response to the UE capability enquiry message (see Figures 1 and 4, step S310 and paragraphs 68 and 76; in response to the UE capability enquiry message/UE capability enquiry);
receiving (see Figures 1 and 5, step S410 and paragraphs 71 and 81; receiving/base station 110 transmits), from the base station (see Figures 1 and 5, step S410 and paragraphs 71 and 81; from the base station/base station 110), an RRC reconfiguration message comprising configuration information related to an AI/ML operation (see Figures 1 and 5, step S410 and paragraphs 71 and 81; an RRC reconfiguration message/(RRC (Re)configuration) comprising configuration information/configurations related to an AI/ML operation/AI/ML functionality-related network configurations);
determining an applicability status of the AI/ML operation based on the configuration information (see paragraph 88; determining/determining an applicability status/(AI/ML models suitable for the current local environment) of the AI/ML operation/(AI/ML operation) based on the configuration information/AI/ML functionality-related network supported configurations); and
transmitting (see Figure 1, step S430 and paragraph 82; transmitting/Figure 1, step S430 shows UE 120 transmitting to base station 110), to the base station (see Figure 1, step S430 and paragraph 82; to the base station/base station 110), an RRC reconfiguration complete message comprising an applicability report for the AI/ML operation based on the determined applicability status (see Figure 1 and paragraphs 82, 88 and 133; an RRC reconfiguration complete message/(RRC (Re)configuration Complete) comprising an applicability report/(AI/ML models suitable for the current local environment) for the AI/ML operation/(AI/ML operation) based on the determined/determining applicability status/AI/ML models suitable for the current local environment).
Regarding Claim 7, Park discloses the, further comprising:
performing a life cycle management (LCM) operation comprising at least one of selection, activation, deactivation, for the AI/ML model (see Figure 1 and paragraph 75; performing/perform a life cycle management (LCM) operation/(operate or perform life cycle management (LC)) comprising at least one of selection/(model selection), activation/(model activation), deactivation/(model deactivation) model/AI/ML model), based on a performance monitoring result by the terminal or the base station (see Figure 1 and paragraphs 75, 138 and 165; based on a performance/perform monitoring result/(model selection and model monitoring) by the base station/base station 110).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park in view of Echigo et al (WO 2025/009173 A1), hereinafter Echigo ‘173.
Regarding Claim 3, Park discloses the method, wherein the applicability report comprises:
an identifier for identifying a specific configuration or model associated with the AI/ML operation (see Figure 1 and paragraph 71; an identifier for identifying a specific model/(model identifier (ID) information) associated with the AI/ML operation/supported for each AI/ML functionality-related network configuration).
Although Park discloses an identifier for identifying a specific configuration or model associated with the AI/ML operation as set forth above,
Park does not explicitly disclose “an applicability status indicator indicating whether the specific configuration or model is applicable or inapplicable in a current radio environment”.
However, Echigo ‘173 discloses the method, wherein the applicability report comprises:
an applicability status indicator indicating whether the specific model is applicable or inapplicable in a current radio environment (see page 16, under Option 2 and pages 15-20; an applicability status indicator/(a bit sequence of 0 or 1) indicating whether the specific model/(model/functionality) is applicable/applicable or inapplicable/(is not applicable) in a current radio environment/ This allows the NW that receives the report to dynamically learn at each stage the applicable models/functionality that may be applicable (models/functionality that may be candidates for application) on page 15).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include “an applicability status indicator indicating whether the specific configuration or model is applicable or inapplicable in a current radio environment” as taught by Echigo ‘173 in the system of Park to utilize AI technology to improve channel state information (CSI) feedback (e.g., reducing overhead, improving accuracy, prediction), improve beam management (e.g., improving accuracy, prediction in the time/space domain), and improve position measurement (e.g., improving position estimation/prediction) (see page 2, paragraph 2 under Description of Embodiments of Echigo ‘173).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park in view of Cogalan et al (WO 2024/035641 A1), hereinafter Cogalan.
Regarding Claim 5, Park discloses the method, further comprising:
receiving AI/ML model update information from the base station via RRC signaling or user plane data (see Figure 5, step S550 and paragraphs 134; receiving AI/ML model update/updated information/(AI/ML Model information is updated) from the base station/(base station 110) via RRC signaling/AI/ML Model Enquiry).
Although Park discloses receiving AI/ML model update information from the base station via RRC signaling or user plane data as set forth above,
Park does not explicitly disclose “wherein the AI/ML operation comprises storing the received AI/ML model data in the terminal and performing inference based on the AI/ML model data”.
However, Cogalan discloses the method, further comprising:
wherein the AI/ML operation comprises storing the received AI/ML model data in the terminal and performing inference based on the AI/ML model data (see paragraphs 5-6; wherein the AI/ML operation/(AI/ML models) comprises storing/storage the received AI/ML model/(AI/ML models) data in the terminal and performing inference/inference based on the AI/ML model data/AI/ML models).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include “wherein the AI/ML operation comprises storing the received AI/ML model data in the terminal and performing inference based on the AI/ML model data” as taught by Cogalan in the system of Park to enhance the measurements and logging procedure to enable the network to efficiently utilize the available measurements at the WTRU (see paragraph 4 of Cogalan).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park in view Lo et al (US 2023/0337036 A1), hereinafter Lo, and further in view of Echigo et al (US 2024/0349092 A1), hereinafter Echigo ‘092.
Regarding Claim 6, Although Park discloses the as set forth above,
Park does not explicitly disclose “wherein the AI/ML operation comprises storing the received AI/ML model data in the terminal and performing inference based on the AI/ML model data”.
However, Lo discloses the method, wherein the AI/ML operation is for beam management or channel state information (CSI) prediction (US 2023/0337036, see paragraph 5; wherein the AI/ML operation/(machine learning (ML) is for channel state information (CSI) prediction/CSI prediction).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include “wherein the AI/ML operation comprises storing the received AI/ML model data in the terminal and performing inference based on the AI/ML model data” as taught by Lo in the system of Park to provide channel state information (CSI) report configuration for CSI predictions in one or more domains (see page 1, paragraph 2 of Lo).
Although the combination of Park and Lo discloses the AI/ML operation comprises storing the received AI/ML model data in the terminal and performing inference based on the AI/ML model data as set forth above,
The combination of Park and Lo does not explicitly disclose “and wherein the terminal performs a physical layer (L1) measurement on reference signals, and generates predicted beam information or predicted channel state information by using a result of the measurement as an input of an AI/ML model”.
However, Echigo ‘092 discloses the method,
and wherein the terminal performs a physical layer (L1) measurement on reference signals (see paragraphs 176, 183 and 201; and wherein the terminal/UE performs a physical layer (L1) measurement/(physical layer5) on reference signals/RRC signaling), and generates predicted beam information or predicted channel state information by using a result of the measurement as an input of an AI/ML model. (see Figure 4 and paragraphs 38, 71-75, 93 and 102; and generates predicted/predict beam information/(predicts future beam failure) by using a result of the measurement/measurement as an input of an AI/ML model).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include “and wherein the terminal performs a physical layer (L1) measurement on reference signals, and generates predicted beam information or predicted channel state information by using a result of the measurement as an input of an AI/ML model” as taught by Echigo ‘092 in the combined system of Park and Lo utilize AI-aided estimation for AI-aided beam management (see page 1, paragraph 5 of Echigo ‘092).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park in view Ly et al (US 2025/0310214 A1), hereinafter Ly.
Regarding Claim 8, Although Park discloses the method as set forth above,
Park does not explicitly disclose “wherein the AI/ML operation comprises a data collection operation for network-side model training, and wherein the data collection operation is started and stopped by network control in a gNB-centric manner or an Operation, Administration, and Maintenance (OAM)-centric manner”.
However, Ly discloses the method, wherein the AI/ML operation comprises a data collection operation for network-side model training (see Figure 5 and paragraphs 121; wherein the AI/ML operation/(AI/ML operation) comprises a data collection operation/(data collection process) for network-side model training/model training), and wherein the data collection operation is started and stopped by network control in an Operation, Administration, and Maintenance (OAM)-centric manner. (US 2025/0310214, see Figure 6, step 285a and paragraph 38, 40, 129; and wherein the data collection operation/(data collection, AI/ML operations) is started/start and stopped /(N.sub.nwdaf_AnalyticsSubscription_Notify i) by network control/(NWDAF 211) in an Operation, Administration, and Maintenance (OAM)-centric manner/ Operation, Administration, and Maintenance (OAM) system).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include “wherein the AI/ML operation comprises a data collection operation for network-side model training, and wherein the data collection operation is started and stopped by network control in a gNB-centric manner or an Operation, Administration, and Maintenance (OAM)-centric manner” as taught by Ly in the system of Park to provide methods, systems, and devices that may assist in AI/ML communication (see page 1, paragraph 14 of Ly).
Allowable Subject Matter
Claim 4 is 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.
Wirth et al (US 2026/0075408 A1) discloses UE Capability Reporting and Handling of Artificial Intelligence/Machine Learning Models. Specifically, see paragraphs 80-84, 97 and 126-128.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LATRESA A McCALLUM whose telephone number is (571)270-5385. The examiner can normally be reached M-F 7:00am-4pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, IAN N MOORE can be reached at 571-272-3085. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/L.A.M/Examiner, Art Unit 2469 /Ian N Moore/Supervisory Patent Examiner, Art Unit 2469
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