CTNF 18/769,304 CTNF 75492 DETAILED ACTION 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 The information disclosure statement (IDS) submitted on 07/10/2024 The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Double Patenting 08-33 AIA The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg , 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman , 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi , 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel , 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. 08-35 Claims 1 and 17 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 8, 11, and 17 of copending Application No. 18/771,058 [PGPUB 2024/0364405] (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other (anticipatory). This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented. Instant Application 18/769,304 Application 18/771,058 Claim 1: A method for configuring a terminal device for a link recovery, comprising: Claim 1: 1. A method for machine learning based Channel State Information (CSI-RS) measurement and reporting, comprising: receiving, by the terminal device, a set of Channel State Information Reference Signal (CSI-RS) resources for a beam failure detection; Claim 1: receiving, by a terminal device, configuration information of a set of "N" CSI-RS resources; receiving, by the terminal device, "M" CSI RS resources out of the "N" CSI RS resources; receiving, by the terminal device, configuration information of a first neural network for the beam failure detection; Claim 8: The method according to claim 1, further comprising: receiving, by the terminal device, configuration information of the first neural network for beam measurement and reporting. performing, by the terminal device, a measurement on the set of CSI-RS resources; Claim 1: performing, by the terminal device, a measurement on the "M" CSI-RS resources; and and generating, by the terminal device, a beam failure detection result by applying the first neural network on a result of the measurement on the set of CSI-RS resources. Claim 1: generating, by the terminal device, a beam measurement result for the "N" CSI-RS resources by applying a first neural network on a result of the measurement on the "M" CSI-RS resources. Instant Application 18/769,304 Application 18/771,058 Claim 17: A system comprising: a processor; and a memory configured to store instructions, when executed by the processor, to: Claim 11: A system comprising: a processor; and a memory configured to store instructions, wherein the instructions, when executed by the processor, cause the processor to: receive, by the terminal device, a set of Channel State Information Reference Signal (CSI-RS) resources for a beam failure detection; Claim 11: receive configuration information of a set of "N" Channel State Information Reference Signal (CSI-RS) resources; receive "M" CSI RS resources out of the "N" CSI RS resources; receive, by the terminal device, configuration information of a first neural network for the beam failure detection; Claim 17: The system according to claim 11, wherein the instructions, when executed by the processor, cause the processor to: receive configuration information of the first neural network for beam measurement and reporting. performing, by the terminal device, a measurement on the set of CSI-RS resources; and Claim 11: perform a measurement on the "M" CSI-RS resources; and generate, by the terminal device, a beam failure detection result by applying the first neural network on a result of the measurement on the set of CSI-RS resources. Claim 11: generate a beam measurement result for the "N" CSI-RS resources by applying a first neural network on a result of the measurement on the "M" CSI-RS resources. 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 – 07-12-aia AIA (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. 07-15-03-aia AIA Claim s 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by LEE et al. (“Lee”) [PGPUB 2024/0292232] . Regarding claim 1, the Lee reference discloses a method for configuring a terminal device for a link recovery, comprising: receiving, by the terminal device, a set of Channel State Information Reference Signal (CSI-RS) resources for a beam failure detection [ie. set of candidate CSI-RS resources, in case of BFD (“Beam Failure Detection”); Lee; figures 2 and 13; paragraphs 0161-0162, 0174, 0199, and 0211-0212]; receiving, by the terminal device, configuration information of a first neural network for the beam failure detection [Lee; fig 13; para 0180-0181, 0186-0188, 0194, and 0214]; performing, by the terminal device, a measurement on the set of CSI-RS resources [ie. measure surrounding beams; Lee; fig 13 and 15; para 0189, 0213, and 0215]; and generating, by the terminal device, a beam failure detection result by applying the first neural network on a result of the measurement on the set of CSI-RS resources [ie. based on ML model and measurements of the optimal candidate beams; Lee; fig 4, 13, and 17; para 0189, 0215, 0241-0246, and 0254]. Regarding claim 3, the Lee reference further discloses the first neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-RSRP (Reference Signal Received Power) measured from the set of CSI-RS resources, L1-RSRQ (Reference Signal Received Quality) measured from the set of CSI-RS resources, and L1-RSSI (Received Signal Strength Indication) measured from the set of CSI-RS resources [ie. RSRP (“L1-RSRP”); Lee; fig 10, para 0141, 0162-0163, and 0173]. Regarding claim 5, the Lee reference further discloses the first neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-RSRP measured from a Physical Downlink Control Channel (PDCCH) transmission and L1-RSRQ measured from the PDCCH transmission [ie. candidate set is within PDCCH transmission (Layer 1 signaling) for L1-RSRP measurements; Lee; para 0078-0079, 0082, and 0173]. Regarding claim 7, the Lee reference further discloses the configuration information is received from a network device, and wherein the configuration information includes a current status of a communication link between the terminal device and the network device [ie. channel state information; Lee; para 0069, 0073, and 0141-0142]. Regarding claim 9, the Lee reference discloses a method for configuring a terminal device for a link recovery, comprising: receiving, by the terminal device, a first set of Channel State Information Reference Signal (CSI-RS) resources for a beam failure detection [“for a beam failure detection” is intended use of the resources; ie. set of candidate CSI-RS resources, in case of BFD (“Beam Failure Detection”); Lee; figures 2 and 13; paragraphs 0161-0162, 0174, 0199, and 0211-0212]; receiving, by the terminal device, a second set of CSI-RS resources and Synchronization Signal and Physical Broadcast Channel Blocks (SSBs) for candidate beam RS [“for candidate beam RS” is intended use of the resources; ie. set of candidate CSI-RS/SSB resources, in case of BFD and a need for a candidate beam RS; Lee; figures 2 and 13; paragraphs 0139-0143, 0151, and 0211-0212]; receiving, by the terminal device, configuration information of a second neural network for determining new candidate beam RS [Lee; fig 13; para 0180-0181, 0186-0188, 0194, and 0214]; performing, by the terminal device, a first measurement on the first set of CSI-RS resources for the beam failure detection [“for a beam failure detection” is intended use of the measurement; ie. measure surrounding beams; Lee; fig 13 and 15; para 0189, 0213, and 0215]; performing, by the terminal device, a second measurement on the second set of CSI-RS resources and SSBs for determining new candidate beam RS [“for a beam failure detection” is intended use of the measurement; ie. measure surrounding beams; Lee; fig 13 and 15; para 0189, 0213, and 0216]; and determining, by the terminal device, a candidate CSI-RS or SSB from the second set of CSI-RS resources and SSBs by applying the second neural network on results of the first and second measurements [ie. based on ML model and measurements (“first and second measurements”) for the optimal candidate beams; Lee; fig 4, 13, and 17; para 0165, 0173, 0189, 0215, 0241-0246, and 0254]. Regarding claim 11, the Lee reference further discloses the second neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-RSRP measured from the second set of CSI-RS resources and SSBs, L1-RSRQ measured from the second set of CSI-RS resources and SSBs, and L1-RSSI measured from the second set of CSI-RS resources and SSBs [ie. RSRP (“L1-RSRP”); Lee; fig 10, para 0141, 0162-0163, and 0173]. Regarding claim 13, the Lee reference further discloses the second neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-RSRP measured from a PDCCH transmission or L1-RSRQ measured from the PDCCH transmission [ie. candidate set is within PDCCH transmission (Layer 1 signaling) for L1-RSRP measurements; Lee; para 0078-0079, 0082, and 0173]. Regarding claim 15, the Lee reference further discloses the configuration information is received from a network device, and wherein the configuration information includes a current status of a communication link between the terminal device and the network device [ie. channel state information; Lee; para 0069, 0073, and 0141-0142]. Regarding claims 17, 19, and 20, the apparatus of claims 17, 19, and 20 perform the similar steps as the method of claims 1, 3, and 5. The Lee reference teaches the method of claims 1, 3, and 5, as referenced above. The additional limitations of a “processor” and a “memory” are rejected with the citation of figure 23 and paragraph 0315 of Lee. Therefore, claims 17, 19, and 20 are rejected using the same art and rationale set forth above in the rejection of claims 1, 3, and 5, by the teachings of Lee . 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. 07-21-aia AIA Claim s 2, 4, 6, 8, 10, 12, 14, 16, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of BI et al. (“Bi”) [PGPUB 2023/0309174] . Regarding claim 2, the Lee reference further discloses a base station and BFD but does not specifically disclose the beam failure detection is for one carrier component (CC). However, in the same field of endeavor, the Bi reference discloses the beam failure detection is for one carrier component (CC) [Bi; para 0072 and 0101-0102]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of the terminology of CC, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to have a simple substitution of one known element for another to obtain predictable result [KSR; MPEP 2141 (III)]. Regarding claim 4, the Lee reference does disclose measurements from the set of CSI-RS resources [Lee; fig 13 and 15; para 0189, 0213, and 0215] but does not specifically disclose the first neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR (Signal to Interference Noise Ratio) measured from the set of CSI-RS resources, a time stamp of the measurement on the set of CSI-RS resources, and BLER (Block Error Rate) measured from the set of CSI-RS resources. However, in the same field of endeavor, the Bi reference discloses the first neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR (Signal to Interference Noise Ratio) measured from the set of CSI-RS resources, a time stamp of the measurement on the set of CSI-RS resources, and BLER (Block Error Rate) measured from the set of CSI-RS resources [Bi; para 0102-0104 and 0149]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of measuring BLER, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to have another measurement for BFD. Regarding claim 6, the Lee reference does disclose measurements from the set of CSI-RS resources [Lee; fig 13 and 15; para 0189, 0213, and 0215] but does not specifically disclose the first neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR measured from a PDCCH transmission and BLER measured from the PDCCH transmission. However, in the same field of endeavor, the Bi reference discloses the first neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR measured from a PDCCH transmission and BLER measured from the PDCCH transmission. [Bi; para 0102-0104 and 0149]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of measuring BLER, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to have another measurement for BFD. Regarding claim 8, the Lee reference does disclose the current status of the communication link [Lee; para 0069, 0073, 0141-0142, and 0295] but does not specifically disclose the current status of the communication link includes a first indicator "failed" or a second indicator "non-failed”. However, in the same field of endeavor, the Bi reference discloses the current status of the communication link includes a first indicator "failed" or a second indicator "non-failed” [ie. beam direction (“non-failed”) Bi; para 0123 and 0128-0129]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of an indicator, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to give the beam direction status to the UE. Regarding claim 10, the Lee reference further discloses a base station and BFD but does not specifically disclose the beam failure detection is for one carrier component (CC). However, in the same field of endeavor, the Bi reference discloses the beam failure detection is for one carrier component (CC) [Bi; para 0072 and 0101-0102]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of the terminology of CC, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to have a simple substitution of one known element for another to obtain predictable result [KSR; MPEP 2141 (III)]. Regarding claim 12, the Lee reference does disclose measurements from the set of CSI-RS resources [Lee; fig 13 and 15; para 0189, 0213, and 0215] but does not specifically disclose the second neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR measured from the second set of CSI-RS resources and SSBs, a time stamp of the second measurement, or BLER measured from the second set of CSI-RS resources and SSBs. However, in the same field of endeavor, the Bi reference discloses the second neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR measured from the second set of CSI-RS resources and SSBs, a time stamp of the second measurement, or BLER measured from the second set of CSI-RS resources and SSBs [Bi; para 0102-0104 and 0149]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of measuring BLER, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to have another measurement for BFD. Regarding claim 14, the Lee reference does disclose measurements from the set of CSI-RS resources [Lee; fig 13 and 15; para 0189, 0213, and 0215] but does not specifically disclose the second neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR measured from a PDCCH transmission or BLER measured from the PDCCH transmission. However, in the same field of endeavor, the Bi reference discloses the second neural network is configured to consider one or more following measurements when generating the beam failure detection result: L1-SINR measured from a PDCCH transmission or BLER measured from the PDCCH transmission [Bi; para 0102-0104 and 0149]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of measuring BLER, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to have another measurement for BFD. Regarding claim 16, the Lee reference does disclose the current status of the communication link [Lee; para 0069, 0073, 0141-0142, and 0295] but does not specifically disclose the current status of the communication link includes a first indicator "failed" or a second indicator "non-failed". However, in the same field of endeavor, the Bi reference discloses the current status of the communication link includes a first indicator "failed" or a second indicator "non-failed” [ie. beam direction (“non-failed”) Bi; para 0123 and 0128-0129]. The Lee and Bi references are analogous art, since they have similar problem solving area in being able to manage beam failure recovery. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of an indicator, taught by Bi, into the system, taught by Lee. The motivation for doing so would have been to give the beam direction status to the UE. Regarding claim 18, the apparatus of claim 18 performs the similar steps as the method of claim 2. The combination of Lee-Bi teaches the method of claim 2, as referenced above. The additional limitations of a “processor” and a “memory” are rejected with the citation of figure 23 and paragraph 0315 of Lee. Therefore, claim 18 is rejected using the same art and rationale set forth above in the rejection of claim 2, by the teachings of Lee-Bi . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Va et al. [PGPUB 2022/0038163] describes selecting a child narrow beam based on measurement report. Park et al. [PGPUB 2025/0008347] describes model training for beam selection. Zheng et al. [USPAT 12,526,028] describes beam selection based on measurements. Zhu et al. [PGPUB 2025/0007597] describes beam prediction based on machine learning (“neural network”). 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JASON D CARDONE/Primary Examiner, Art Unit 2458 Application/Control Number: 18/769,304 Page 2 Art Unit: 2458 Application/Control Number: 18/769,304 Page 3 Art Unit: 2458 Application/Control Number: 18/769,304 Page 4 Art Unit: 2458 Application/Control Number: 18/769,304 Page 5 Art Unit: 2458 Application/Control Number: 18/769,304 Page 6 Art Unit: 2458 Application/Control Number: 18/769,304 Page 7 Art Unit: 2458 Application/Control Number: 18/769,304 Page 8 Art Unit: 2458 Application/Control Number: 18/769,304 Page 9 Art Unit: 2458 Application/Control Number: 18/769,304 Page 10 Art Unit: 2458 Application/Control Number: 18/769,304 Page 11 Art Unit: 2458 Application/Control Number: 18/769,304 Page 12 Art Unit: 2458 Application/Control Number: 18/769,304 Page 13 Art Unit: 2458 Application/Control Number: 18/769,304 Page 14 Art Unit: 2458 Application/Control Number: 18/769,304 Page 15 Art Unit: 2458 Application/Control Number: 18/769,304 Page 16 Art Unit: 2458 Application/Control Number: 18/769,304 Page 17 Art Unit: 2458 Application/Control Number: 18/769,304 Page 18 Art Unit: 2458 Application/Control Number: 18/769,304 Page 19 Art Unit: 2458 Application/Control Number: 18/769,304 Page 20 Art Unit: 2458
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