CTNF 18/566,022 CTNF 86380 DETAILED ACTION This communication is response to the amendment filed 03/03/2026. Claims 31-56 are pending and presented for examination. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 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 06-52 AIA The information disclosure statement (IDS) submitted on 03/03/2026 was filed after the mailing date of the Non-Final Rejection on 12/04/2025 . 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 Rejections - 35 USC § 112 07-30-02 AIA The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. 07-34-01 Claims 31-56 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Regarding claims 31-56 , the term “machine learning model group” used in the claim is vague and unclear. It is unclear what is the meaning of “machine learning model group”. It is not clear on which basis ML models are grouped. For examination purposes, the term will be interpreted as group of ML models that are grouped on an arbitrary basis. Switching to the machine learning model group in response to receiving PDCCH is unclear and renders the claim indefinite. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-15-aia AIA Claim(s) 31-34, 36-47, and 49-56 is/are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by 2021/0160149 to MA et al. (hereafter Ma) . Regarding claim 1 , Ma discloses a method of wireless communication by a user equipment (UE) (see Ma, ¶ 0133: FIG. 13 is a signal flow diagram 1100 of an example of an over the air information exchange procedure for a training phase of machine learning components …..enabling device-specific tailoring/customization of an air interface, in accordance with an embodiment of this disclosure in which the training takes place jointly at the UE and BS.), comprising: receiving a physical downlink control channel (PDCCH) message comprising an indication of a machine learning model group (see Ma, ¶ 0136: the BS sends a training request to the UE at 1112 to trigger a training phase 1150. In some embodiments, the training request may be sent to the UE through DCI (dynamic signaling) on a downlink control channel or on a data channel. For example, in some embodiments the training request may be sent to the UE with UE specific or UE common DCI. For example, UE common DCI may be used to send a training request to all UEs or a group of UEs. In some embodiments, the training request may be set to the UE via RRC signaling. In some embodiments, the training request may include initial training setting(s)/parameter(s); ¶ 0140: The AI/ML related information may be sent as part of the training request sent at 1112……The AI/ML related information sent to the UE, such as information indicating AI/ML algorithm(s) and setting/parameters, may have been selected by the BS or another network device); the AI/ML algorithms of the AI/ML module to be trained correspond to the machine learning model group; and switching to the machine learning model group in response to receiving the PDCCH (see Ma, ¶ 0142: in some embodiments the BS notifies the UE which AI/ML module(s)/component(s) is/are to be trained by including information in the training request that identifies one or more AI/ML modules/components or by sending such information to the UE in a separate communication. By doing so, the BS informs the UE which AI/ML modules(s)/component(s) is/are to be trained based on the training signal transmitted by the BS at 1116; ¶ 0146: In other embodiments, the UE and/or the BS may be able to update the training setup and parameters autonomously based on their own training process at 1119 without the further information exchange indicated at 1120; ¶0159: In the signal flow diagram 1300, a UE and a BS or other network device are involved in an information exchange for an AI/ML re-training phase 1350. In this embodiment, the re-training phase may be triggered by the network, as indicated at 1310. In some embodiments, the BS may trigger the re-training by sending a training request to the UE, e.g., through DCI, RRC or MAC signaling as discussed earlier with reference to FIGS. 12 and 13). The cited phrases imply each that each time a (re)training is requested the UE must select/switch to the AI/ML module and the corresponding AI/ML algorithms and parameters indicated in the DCI carrying the training request and perform training of the selected AI/ML module/algorithm/parameters; it is noted that the wording; it is noted that the wording of claim 1 does not specify neither for which purpose the switching is performed nor for which procedure the ML algorithm groups are used. Regarding claim 32 , Ma discloses the method of claim 31, in which the indication is within a downlink control information (DCI) field conveyed by the PDCCH that is scheduling data transmission for the UE (see Ma, ¶ 0121: In some embodiments, the training request may be sent to the UE through DCI (dynamic signaling) on a downlink control channel or on a data channel. For example, in some embodiments the training request may be sent to the UE as UE specific or UE common DCI), transmission of the training request as a field within a DCI scheduling UE data or within an existing DCI not used for data scheduling is considered as minor implementation detail within general knowledge of the skilled. Regarding claim 33 , Ma discloses the method of claim 31, in which the indication is within a scheduling related field conveyed by the PDCCH that is not scheduling data transmission for the UE (see Ma, ¶ 0121: In some embodiments, the training request may be sent to the UE through DCI (dynamic signaling) on a downlink control channel or on a data channel. For example, in some embodiments the training request may be sent to the UE as UE specific or UE common DCI). Regarding claim 34 , Ma discloses the method of claim 31, in which a second downlink control information (DCI) message without a field comprising the indication includes padding and is a same size as a first DCI message that includes the field comprising the indication (see Ma, ¶ 0136: , the BS sends a training request to the UE at 1112 to trigger a training phase 1150. In some embodiments, the training request may be sent to the UE through DCI (dynamic signaling) on a downlink control channel or on a data channel. For example, in some embodiments the training request may be sent to the UE with UE specific or UE common DCI). Regarding claim 36 , Ma discloses the method of claim 31, in which the PDCCH further indicates a time period for using the machine learning model group (see Ma, ¶ 0147; ¶ 0142). Regarding claim 37 , Ma discloses the method of claim 36, further comprising switching to a second group of two machine learning model groups, after the time period expires (see Ma, ¶ 0147; ¶ 0142). Regarding claim 38 , Ma discloses the method of claim 36, further comprising switching to a default group of three or more machine learning model groups, after the time period expires (see Ma, ¶ 0147; ¶ 0142). Regarding claim 39 , Ma discloses the method of claim 31, further comprising receiving a time period for how long to use the machine learning model group via radio resource control (RRC) signaling (see Ma, ¶ 0147). Regarding claim 40 , Ma discloses the method of claim 31, further comprising receiving a time period for how long to use the machine learning model group via DCI that selects one duration value of a set of duration values received via radio resource control (RRC) signaling (see Ma, ¶ 0147). Regarding claim 41 , Ma discloses the method of claim 31, further comprising: starting a timer in response to switching to the machine learning model group; and switching to another machine learning model group upon expiration of the timer (see Ma, ¶ 0147; ¶ 0142). Regarding claim 42 , Ma discloses the method of claim 31, in which the indication comprises a PDCCH parameter including one of a search space set, DCI type, or aggregation level (see Ma, ¶ 0136). Regarding claim 43 , Ma discloses the method of claim 31, in which the indication comprises a PDCCH parameter for a search space set group (see Ma, ¶ 0136). Regarding claim 44 , it is rejected for the same reasons as set forth in claim 31. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 31. Regarding claim 45 , it is rejected for the same reasons as set forth in claim 32. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 32. Regarding claim 46 , it is rejected for the same reasons as set forth in claim 33. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 33. Regarding claim 47 , it is rejected for the same reasons as set forth in claim 34. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 34. Regarding claim 49 , it is rejected for the same reasons as set forth in claim 36. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 36. Regarding claim 50 , it is rejected for the same reasons as set forth in claim 37. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 37. Regarding claim 51 , it is rejected for the same reasons as set forth in claim 38. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 38. Regarding claim 52 , it is rejected for the same reasons as set forth in claim 39. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 39. Regarding claim 53 , it is rejected for the same reasons as set forth in claim 40. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 40. Regarding claim 54 , it is rejected for the same reasons as set forth in claim 41. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 41. Regarding claim 55 , it is rejected for the same reasons as set forth in claim 42. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 42. Regarding claim 56 , it is rejected for the same reasons as set forth in claim 43. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 43 . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-23-aia AIA 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. 07-20-02-aia AIA 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. 07-21-aia AIA Claim (s) 35 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ma . Regarding claim 35 , Ma discloses the method of claim 34, further comprising determining whether the indication is within the first DCI message or the second DCI message based on a frequency domain resource assignment (FDRA) (see Ma, ¶ 0136: , the BS sends a training request to the UE at 1112 to trigger a training phase 1150. In some embodiments, the training request may be sent to the UE through DCI (dynamic signaling) on a downlink control channel or on a data channel. For example, in some embodiments the training request may be sent to the UE with UE specific or UE common DCI). Usage/definition of another DCI message that includes padding and has the same size as the UE specific/UE common DCI message carrying the training request is well-known in the art and considered as trivial features for the skilled person; usage of FDRA filled (e.g., of its content as all “0” or all “1”) for indication of the DCI purpose is considered as a well-known procedure for one of ordinary skill in the art. It would have been obvious to one of ordinary skilled in the art to implement the well-known teaching of using FDRA for efficient resource utilization. Regarding claim 48 , it is rejected for the same reasons as set forth in claim 35. Although phrased an apparatus claim, the claim is nevertheless simple repetitions of the subject matter of claim 35 . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2023/0119810 to KIM et al. discloses transmitting and receiving a physical downlink control channel (PDCCH) in a wireless communication system are disclosed. A method for receiving a PDCCH according to an embodiment of the present disclosure may comprise the steps of: receiving, from a base station, downlink control information (DCI) for scheduling a physical downlink shared channel (PDSCH) in the PDCCH; receiving the PDSCH from the base station; and transmitting, to the base station, acknowledgment (ACK) information in a physical uplink control channel (PUCCH), in response to the PDSCH. The PDCCH is repeatedly transmitted on a plurality of monitoring locations (MLs), the plurality of MLs are configured based on at least one control resource set (CORESET) and at least one search space set (SS), and a resource of the PUCCH is determined based on information on a control channel element (CCE) in one ML among the plurality of MLs and a PUCCH resource indicator in the DCI. US 2022/0417971 to VANKAYALA et al. discloses FIG. 10 is a flowchart illustrating an example method of intelligently decoding PDCCH data received from the BS based on ML model in a 4G wireless network system, according to various embodiments. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RASHEED GIDADO whose telephone number is (571)270-7645. The examiner can normally be reached Monday - Friday 8AM-5PM EST. Examiner interviews are available via telephone, in-person, and video conferencing 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, Ricky Ngo can be reached at 571-272-3139. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RASHEED GIDADO/ Primary Examiner, Art Unit 2464 Application/Control Number: 18/566,022 Page 2 Art Unit: 2464 Application/Control Number: 18/566,022 Page 3 Art Unit: 2464 Application/Control Number: 18/566,022 Page 4 Art Unit: 2464 Application/Control Number: 18/566,022 Page 5 Art Unit: 2464 Application/Control Number: 18/566,022 Page 6 Art Unit: 2464 Application/Control Number: 18/566,022 Page 7 Art Unit: 2464 Application/Control Number: 18/566,022 Page 8 Art Unit: 2464 Application/Control Number: 18/566,022 Page 9 Art Unit: 2464
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