DETAILED ACTION
This Office action is in response to the amendment filed 21 November 2025. Claims 1-20 are pending in this application.
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 .
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.
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.
Claim(s) 1-2, 9-13, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Madadi et al. (US 2022/0338189) in view of Khan Beigi et al. (US 2025/0357982).
For Claims 1, 12, and 20, Madadi teaches a method performed by at least one processor of a user equipment (UE), a user equipment (UE) comprising: at least one memory configured to store computer program code; and at least one processor configured to access said at least one memory and operate as instructed by the computer program code (see paragraphs 8, 96), and a non-transitory computer readable medium having instructions stored therein (see paragraph 18); the method comprising:
receiving a set of resources from a base station (see abstract, paragraphs 6, 106, 110, and 125);
performing a first measuring of the set of resources based on a legacy mode that does not use an artificial intelligence machine learning (AI/ML) model to produce a first output (see paragraphs 1, 110-111, 116, 132);
performing a second measuring of the set of resources based on the AI/ML model to produce a second output (see paragraphs 110-111, 116, and 131-132);
reporting, to the base station, results corresponding to the first output and the second output (see paragraphs 116-117, 132; also Figure 4 item 404, Figure 6 item 604).
Madadi as applied above is not explicit as to, but Khan Beigi teaches receiving, from the base station during a first transmission mode, a first transmission using a first transmission parameter determined based on the first output, the first transmission not using a second transmission parameter determined based on the second output (see paragraph 10: with and without AI/ML; paragraph 124: configuration determined at BS side; paragraphs 85, 87, 121, 131, 144, 190-192, 199: TCI state activation for DL and UL transmissions based on transmission from BS; paragraph 127: conventional and AI/ML modeling for different TCI state measurements; the base station provides transmissions in different modes using different parameters determined based on conventional and ML methods); and
receiving, from the base station during a second transmission mode, a second transmission using the second transmission parameter determined based on the second output, the second transmission not using the first transmission parameter (see paragraph 10: with and without AI/ML; paragraph 124: configuration determined at BS side; paragraphs 85, 87, 121, 131, 144, 190-192, 199: TCI state activation for DL and UL transmissions based on transmission from BS; paragraph 127: conventional and AI/ML modeling for different TCI state measurements; the base station provides transmissions in different modes using different parameters determined based on conventional and ML methods).
Thus it would have been obvious to one of ordinary skill in the art at the time the application was filed to manage transmissions based on conventional and AI methods as in Khan Beigi when implementing the method of Madadi. The motivation would be to allow for the selection of optimal parameters for the different transmission modes.
For Claims 2 and 13, Madadi teaches the method,
wherein the set of resources from the base station includes one or more channel state information reference signal (CSI-RS) resources (see abstract, paragraphs 6, 106, 110, 131-132),
wherein the first output is an estimated CSI (see paragraphs 67, 118, 125), and
wherein the second output is another estimated CSI obtained from the input of compressed version of the one or more CSI-RS resources (see paragraphs 108, 132).
For Claim 9, Madadi teaches the method, further comprising:
receiving, from the base station, a measurement activation signal (see paragraph 110); and
performing the first measuring and the second measuring based on the reception of the measurement activation signal (see paragraphs 110-111, 132).
For Claim 10, Madadi teaches the method,
wherein the reporting of the results corresponding to the first output and the second output is performed at a predetermined timing (see paragraphs 13, 15, 107, 110-111: aperiodic, semi-persistent), and
wherein the first measuring and the second measuring are performed at a timing in accordance with the predetermined timing (see paragraphs 115-116).
For Claim 11, Madadi teaches the method, further comprising:
receiving, from the base station, an indication of which AI/ML model to use from a plurality of AI/ML models for the second measuring (see abstract, paragraphs 107, 129).
Response to Arguments
The amendment filed 21 November 2025 has been entered.
Previous rejections under 35 SUC 112 are withdrawn in light of the amendments.
Applicant’s arguments with respect to the rejections under 35 USC 102 have been fully considered, but are moot in view of the new grounds of rejection introduced herein. Claims 1-2, 9-13, and 20 remain rejected under 35 USC 103.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Guan et al. (US 2025/0168682) teaches a system using AI modeling for beam management. Tang (US 2022/0124836) teaches a system for managing feedback information using AI.
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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/CASSANDRA L DECKER/Examiner, Art Unit 2466 1/5/2026
/FARUK HAMZA/Supervisory Patent Examiner, Art Unit 2466