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 .
Response to Arguments
Applicant's arguments filed 5/22/2026 have been fully considered but they are moot in view of a new grounds of rejection.
Claim Rejections - 35 USC § 102
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 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 13, and 15 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by You (WO2023/221111 A1)
Regarding Claim 1, You teaches a network node which communicates with a user equipment (UE) over a radio interface (Fig.1 and Page 4:lines28-30, gNB communicates with UE), the network node comprising: transmission circuitry configured to transmit a message which requests the UE to report UE capability (Fig.1 and Page 4:lines28-30, “UE capability reporting process: gNB triggers this process to request the UE to report capability information”); and reception circuitry configured to receive run-time Artificial Intelligence/Machine Learning (AI/ML) capability of a channel state information (CSI) functionality from the UE (Page 5:lines 1-4, “Use AI to optimize related use cases, including positioning, beam management, channel state information (Channel State Information, CSI), etc.” and Page 8:lines 5-7, “UE capability reporting may be reporting the capability of each supported AI function use case, or the capability of a single AI function use case”, note: CSI functionality or use case capability is reported and run-time interpreted as… at the time of the report), the run-time AI/ML capability being associated with a UE condition (Page 5:lines 22-26 and Page 11:lines 13-16, “When the available battery power of the UE rises above the second threshold, or drops below the second threshold, the UE reports to the network device. UE capabilities are used for network equipment to update the corresponding AI model”) and a network configuration (Page 9:lines 24-33, “UE reports the UE capabilities to the network device based on the configuration of the network device” and “UE receives configuration information sent by the network device, and the configuration information is used to configure the reporting resources of the UE capability. Optionally, the UE reports the UE capabilities based on the reporting resources configured by the network device” and Page 9:lines 44-46 and Page 10:lines 13-24, ““the first condition is… configured by the network device” and “at least one capability is…configured by the network device”), wherein the run-time AI/ML capability of the CSI functionality varies dynamically based on an evaluation of the UE condition and the network configuration (Page 5:lines 22-26, Page 14:lines 37-50, Page 9:lines 24-46, and Page 10:lines 13-24).
Regarding Claim 13 and 15, You teaches a user equipment (UE) which communicates over a radio interface with a radio access network (Fig.1 and Page 4:lines28-30, gNB communicates with UE), the UE comprising: reception circuitry configured to receive, from the radio access network, at least one message which requests the UE to report UE capability (Fig.1 and Page 4:lines28-30, “UE capability reporting process: gNB triggers this process to request the UE to report capability information”); processing circuitry configured to: generate at least one report message comprising run-time Artificial Intelligence/Machine Learning (AI/ML) capability of a channel state information (CSI) functionality (Page 5:lines 1-4, “Use AI to optimize related use cases, including positioning, beam management, channel state information (Channel State Information, CSI), etc.” and Page 8:lines 5-7, “UE capability reporting may be reporting the capability of each supported AI function use case, or the capability of a single AI function use case”, note: CSI functionality or use case capability is reported and run-time interpreted as… at the time of the report), the run-time AI/ML capability being associated with a UE condition (Page 5:lines 22-26 and Page 11:lines 13-16, “When the available battery power of the UE rises above the second threshold, or drops below the second threshold, the UE reports to the network device. UE capabilities are used for network equipment to update the corresponding AI model”) and a network configuration (Page 9:lines 24-33, “UE reports the UE capabilities to the network device based on the configuration of the network device” and “UE receives configuration information sent by the network device, and the configuration information is used to configure the reporting resources of the UE capability. Optionally, the UE reports the UE capabilities based on the reporting resources configured by the network device” and Page 9:lines 44-46 and Page 10:lines 13-24, ““the first condition is… configured by the network device” and “at least one capability is…configured by the network device”), and control execution of the CSI functionality based on the run-time AI/ML capability (Page 4:lines 16-30, coordinates capability information between UE and base station, hence controlling execution and Page 6:line 20 “power that the UE can provide for running the AI model”); and transmission circuitry configured to transmit the report message to the radio access network (Page 8:lines 5-7 and Page 9:lines 27-28), wherein the run-time AI/ML capability of the CSI functionality varies dynamically based on an evaluation of the UE condition and the network configuration (Page 5:lines 22-26, Page 14:lines 37-50, Page 9:lines 24-46, and Page 10:lines 13-24).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
CHENG WO 2024/040476 – Par.88-89, gNB sends UECapabilityEnquiry to UE for its AI capability. UE reports its capability information (UECapabilityINformation) to the gNB regarding use cases (e.g. CSI feedback enhancement). UE can report preference and UE may be capable to perform AI/ML training or inference, but it is not willing to because of battery status.
WANG US 2025/0048085 – Par.76-102 and Par.388-408: Capability request sent by a network device to a UE. The request contains configuration information and the request and feedback can be related to AI/ML capability of CSI (Par.102). Teaches Life cycle management (Par.197).
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/WESLEY L KIM/Supervisory Patent Examiner, Art Unit 2648
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