DETAILED ACTION
Response to Amendment
This Office Action is responsive to applicant’s remarks and amendments filed on April 07, 2026 after the non-final rejection of the application.
The Amendment filed April 07, 2026 has been entered. Claims 1-17 were canceled. Claims 18-25 are pending for examination, of which claims 18-20 were amended and claims 21-25 were newly added.
Response to Arguments
Applicant's arguments filed on 4/7/26 have been fully considered and entered.
With respect to the applicant’s argument, Applicant states that Chai is silent as to the features that a training set identifier (TSI) is configured, that an artificial intelligence model is designated as being mapped to the TSI, that indication information including the TSI is received, and that a first signal based on the TSI is received – as recited in claim 18.
Examiner respectfully disagrees.
Chai, from his disclosure, states the base station sends information on training set identifier (TSI) configuration information to the terminal and indicates the terminal device to perform artificial intelligence {AI} model training using training sets [0099]. Chai further explains the model training includes following steps: in response to AI model being used for channel estimation or prediction, the base station sends a demodulation reference signal {DMRS} or a channel state information reference signal {CSI-RS} to the terminal, based on which, the terminal determines pieces of training data or training data set.
Thus, Chai does not differ from Feature 1 of Claim 18.
Applicant’s arguments, with respect to the rejection(s) of amended claim 18 has been considered but are moot in view of the new ground of rejection necessitated by the addition of limitations “the TSI indicates an association between data collection for training and application of the artificial intelligence model using at least one reference signal (hereinafter, referred to as "Feature 2". The rejection is as below.
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 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 non-obviousness.
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 18 and 21-25 are rejected under 35 U.S.C. 103(a) as being unpatentable over Chai et al. (US 20240211770 A1), hereinafter referred to as Chai, in view of Jia et al. (US 20240414073 A1), hereinafter referred to as Jia.
Regarding claim 18:
Chai discloses an operation method of a terminal in a communication system (method of performing model training by a terminal [0097]), comprising:
receiving, from a base station, training set identifier (TSI) configuration information including at least one TSI (receiving, from base station, indication information of three training sets, each of which includes pieces of training data [0099]);
designating an artificial intelligence model mapped to the at least one TSI according to the TSI configuration information (designing artificial intelligence {AI} model based on training data configured by base station [0087]);
receiving, from the base station, indication information including the at least one TSI (receiving, from base station, information on training data [0003]) ;
receiving, from the base station, a first signal based on the at least one TSI (receiving, from base station, a reference signal, e.g., first signal, wherein reference signal is used to generate N pieces of training data, [0115]).
Also, Chai states the first information further indicates a correspondence between the plurality of training sets and the plurality of first AI models [0125, lines 23-25].
Chai does not clearly disclose wherein the at least one TSI indicates an association between data collection for training the artificial intelligence model using at least one reference signal and application of the artificial intelligence model using the at least one reference signal.
Jia, from the same field of endeavor, teaches one TSI indicates an association between data collection for training the artificial intelligence model using at least one reference signal and application of the artificial intelligence model using the at least one reference signal (information on collected data associated with reference signal identifier, cell identity (ID), AI model ID, task ID [0037-0038,0044-0047], wherein AI model is used to predict channel quality, e.g., AI model applications [0032]).
Therefore, it would have been obvious to one of ordinary skills in the art at the time before the claimed invention was filed to train the AI model mapped to TSI which indicates an association between data collection and application of AI model by using received reference signal; thus ensuring delay and accuracy of AI model training/ learning from training datasets -- Jia [0036].
Regarding claim 21:
Chai in view of Jia discloses all features of claim 18, and –
Chai does not, while Jia teaches Transmission and Reception Point {TRP} is connected to terminal (network-side device is connected to terminal, [0021, lines 1-35 or elements 12, 11 in Fig.1)] and is represented with ID [0044]) and determining a reference signal is sent from second communication device (reference signal is sent from second communication device [0085])
Therefore, it would have been obvious to one of ordinary skills in the art at the time before the claimed invention was filed to associate one reference signal with Transmission and Reception Point (TRP) assigned with a specific ID; thus being able to know exactly which TRP is transmitting/ receiving the reference signal for further processing.
Regarding claim 22:
Chai in view of Jia discloses all features of claim 18, and –
Chai further discloses applying the trained artificial intelligence model based on the at least one TSI (performing model training based on pieces of training data based on DMRS, e.g., TSI [0115]).
Regarding claim 23:
Chai in view of Jia discloses all features of claim 18, and –
Chai further discloses receiving, from the base station, a second signal including the at least one TSI (receiving CSI-RS [0115]); and applying the trained artificial intelligence model mapped to the at least one TSI based on the received second signal (performing model training based on pieces of training data based on CSI-RS, e.g., TSI [0115]).
Regarding claim 24:
Chai in view of Jia discloses all features of claim 23, and –
Chai in view of Jia does not further discloses the at least one TSI is mapped to at least one specific beam direction (input data is in a beam domain dimension [0088]).
Regarding claim 25:
Chai in view of Jia discloses all features of claim 23, and –
Chai further discloses the at least one TSI is mapped to at least one physical channel (alternatively, in a receiver enhancement or decoder enhancement scenario, a channel that carries data or control information is used to generate N pieces of training data, e.g., a physical downlink data channel {physical downlink shared channel, PDSCH}, a physical downlink control channel {physical downlink control channel, PDCCH}, or a physical broadcast channel physical broadcast channel, PBCH}” [0115, lines 20-37]).
Claims 19-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Chai in view of Jia, as applied to claim 18 above, in view of Kim (US 20230344505 A1), hereinafter referred to as Kim.
Regarding claim 19:
Chai in view of Jia discloses all features of claim 18, and –
Chai further discloses that AI model can be applied to beam management or prediction scenario [0115, lines 26-37].
Chai in view of Jia does not disclose the at least one reference signal is associated with at least one specific beam direction.
Kim, from the same field of endeavor, discloses receiving channels and signals, e.g., PDSCH, CSI-RS, DMRS, etc., in Rx beam directions [0288]-[0290].
Therefore, it would have been obvious to one of ordinary skills in the art at the time before the claimed invention was filed to map TSI to physical channel in one beam direction; thus efficiently performing a specific operation, e.g., channel estimation, by using proper training data -- Kim [0085-0086].
Regarding claim 20:
Chai in view of Jia discloses all features of claim 18, and –
Chai in view of Jia does not further discloses wherein the at least one reference signal is associated with at least one physical channel.
Kim, from the same field of endeavor, discloses receiving channels and signals, e.g., PDSCH, CSI-RS, DMRS, etc., in Rx beam directions [0288]-[0290].
Therefore, it would have been obvious to one of ordinary skills in the art at the time before the claimed invention was filed to map TSI to a reference signal in a beam direction; thus efficiently performing a specific operation, e.g., channel estimation, by using proper training data Kim [0085-0086].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Pihuir (US-11341429-B1 [ col.6, 7-12]),
Tian (US-20240022455-A1 [0075), and
Yerramalli (US-20230336950-A1 [0135])
are all cited to show that training the AI model mapped to TSI, which indicates an association between data collection and application of AI model by using received reference signal – would ensure delay and accuracy of AI model training/ learning from training datasets-- similar to the claimed invention.
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAMQUYEN THAI whose telephone number is (571)270-7245. The examiner can normally be reached on 9:00am-5:00pm. Examiner interviews are available via telephone, in-person, and videoconferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at: http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ayman A. Abaza can be reached on 571-270-0422. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/C.Q.T./
Examiner, Art Unit 2465
/John Pezzlo/
Primary Patent Examiner, AU 2465B
14 July 2026
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