CTNF 18/841,797 CTNF 84613 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. 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) 23-25, 28, 30, 31, 34, 35, 39 and 42 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pezeshki et al. (US 2023/0053589) . Regarding claims 23 and 42, Pezeshki et al. disclose a user device (Figures 2 and 4, UE 104) and a method, comprising: at least one processor (Figure 2, controller/processor 280) ; and at least one memory (Figure 2, memory 282) , the at least one memory storing instructions (Paragraph 182, Memories…282 may store data and program codes for…UE 104) , that when executed by the at least one processor (Paragraph 76, software components that are executed and run on one or more processors (e.g., controller/processor 280 of FIG. 2) for determining reliability of a beam prediction mechanism) , cause the user device at least to: perform both a reference signal measurement (Figure 4 and paragraph 63, In a second process 412, the UE 104 may measure the actual beam strength (e.g., an RSRP) of the first transmit beam used to transmit the second communication 410) and reference signal prediction (Figure 4 and paragraph 62, In a first process 408, the UE 104 may determine a predicted strength of a first transmit beam…the UE 104 may utilize a prediction mechanism to predict the strength of the first transmit beam…the prediction mechanism may predict the RSRP of the first transmit beam) for at least one time instance (Paragraph 62, at a second time (e.g., t) prior to the first time) for validating the reference signal prediction (Paragraph 27, for determining whether the beam-strength predictions of the prediction mechanism are reliable predictions; Paragraphs 76 and 98, for determining reliability of a beam prediction mechanism). Regarding claim 24, Pezeshki et al. disclose wherein the instructions, when executed by the at least one processor, further cause the user device at least to: receive, from a network device, an indication (Figure 4 and paragraph 52, the BS 102 may transmit, to the UE 104, a first communication 406 having a quality metric; Paragraphs 54-55, 59-61, communication 406 includes beam identification and metrics to be used by the UE 104 to determine reliability of beam prediction mechanism) to perform both the reference signal measurement (Figure 4 and paragraph 63, In a second process 412, the UE 104 may measure the actual beam strength (e.g., an RSRP) of the first transmit beam used to transmit the second communication 410) and reference signal prediction (Figure 4 and paragraph 62, In a first process 408, the UE 104 may determine a predicted strength of a first transmit beam…the UE 104 may utilize a prediction mechanism to predict the strength of the first transmit beam…the prediction mechanism may predict the RSRP of the first transmit beam) for the at least one time instance (Paragraph 62, at a second time (e.g., t) prior to the first time). Regarding claim 25, Pezeshki et al. disclose wherein the instructions, when executed by the at least one processor, further cause the user device at least to: determine that there is a success of reference signal prediction for the at least one time instance (Figure 4 and paragraph 64, In a third process 414, the UE 104 may determine whether a difference (e.g., absolute value of the difference) between the predicted strength and the actual strength of the first transmit beam satisfies the quality metric (e.g., whether a difference between the predicted strength and the actual strength of the first transmit beam is within a tolerance level) for the first transmit beam; Figure 5 and paragraph 75, UE 104 determines that the quality metric is satisfied [success]) ; and transmit to the network device a success indication of the reference signal prediction for the at least one time instance (Figure 4 and paragraph 65, In a third communication 416, the UE 104 may transmit, to the BS 102, statistics of whether the quality metric is satisfied…the statistics may include statistics regarding the percentage of time that the quality metric is satisfied at the UE 104 for one or more transmit beams; Figure 5 and paragraph 75, UE 104 determines that the quality metric is satisfied, then at a fifth block 518, the UE 104 may determine to store the difference between the predicted beam strength and the actual beam strength. The UE 104 may also transmit to the BS 102 an indication that the difference is within the tolerance level). Regarding claim 28, Pezeshki et al. disclose wherein the instructions, when executed by the at least one processor, further cause the user device at least to: determine that there is a failure of reference signal prediction for the at least one time instance (Figure 4 and paragraph 64, In a third process 414, the UE 104 may determine whether a difference (e.g., absolute value of the difference) between the predicted strength and the actual strength of the first transmit beam satisfies the quality metric (e.g., whether a difference between the predicted strength and the actual strength of the first transmit beam is within a tolerance level) for the first transmit beam; Figure 5 and paragraphs 71-74, UE determines that the quality metric is not satisfied [failure]) ; and transmit to the network device a failure indication of the reference signal prediction for the at least one time instance (Figure 4 and paragraph 65, In a third communication 416, the UE 104 may transmit, to the BS 102, statistics of whether the quality metric is satisfied; Figure 5 and paragraph 74, At a fourth block 516, the UE 104 may also send feedback to the BS, wherein the feedback provides statistics of whether the quality metric is satisfied. In some examples, the UE 104 may feedback the difference between the first RSRP value and the second RSRP value if the difference is greater than the quality metric (e.g., the difference does not satisfy [failure] the quality metric). In this case, the UE 104 may only provide feedback when the quality metric is not satisfied. In another example, the UE 104 may provide an indication of a number of times the quality metric has been satisfied and/or unsatisfied within a duration of time). Regarding claim 30, Pezeshki et al. disclose wherein the instructions, when executed by the at least one processor, further cause the user device at least to: receive, from a network device (Paragraph 65, the BS 102 may configure the UE 104 to transmit statistics; the UE 104 may transmit statistics in response to a BS 102 request for statistics) , an indication to report the number of measured time instances, the number of predicted time instances, and/or the number of measured and predicted time instances (Paragraph 65, the statistics may include statistics regarding the percentage of time that the quality metric is satisfied at the UE 104 for one or more transmit beams, such as over a time period. For example, UE 104 may indicate to the BS 102, every X measurement instances (e.g., where X is an integer such as 1, 2, 5, 20, etc.) a percentage of times the quality metric was satisfied over the X measurement instances. For example, if the quality metric was satisfied Y times over the X measurement instances, the UE 104 may report Y/X as the percentage to BS 102). Regarding claim 31, Pezeshki et al. disclose wherein the instructions, when executed by the at least one processor, further cause the user device at least to: determine assistance information for updating the number of measured time instances, the number of predicted time instances, and/or the number of measured and predicted time instances (Paragraph 50, historical beam information as previous strengths of beams measured by the UE 104 included in a table maintained by the UE, the previous measured strengths corresponding to one or previous time instances or periods, the historical beam information [assistance information] being sued to develop a function the number network can used to predict future beam strength; Paragraph 65, measurement time instances maintained by the UE 104 as percentage of times the quality metric was satisfied over the X measurement instances) ; transmit, to the network device, the assistance information for updating the number of measured time instances, the number of predicted time instances, and/or the number of measured and predicted time instances (Paragraph 65, UE 104 may indicate to the BS 102, every X measurement instances) ; and apply the assistance information in performing reference signal measurements and/or reference signal prediction for the at least one time instance (Paragraph 50, the historical beam information may be used to develop a function (ƒ) the neural network can use to predict a future beam strength associated with one or more BS 102 transmit beams). Regarding claim 34, Pezeshki et al. disclose a network device (Figures 2 and 4, BS 102) , comprising: at least one processor (Figure 2, controller/processor 240) ; and at least one memory (Figure 2, memory 242) , the at least one memory storing instructions (Paragraph 182, Memories 242…may store data and program codes for BS 102) , that when executed by the at least one processor (Paragraph 93, software components that are executed and run on one or more processors (e.g., controller/processor 240 of FIG. 2)) , cause the network device at least to: transmit an indication to a user device (Figure 4 and paragraph 52, the BS 102 may transmit, to the UE 104, a first communication 406 having a quality metric; Paragraphs 54-55, 59-61, communication 406 includes beam identification and metrics to be used by the UE 104 to determine reliability of beam prediction mechanism) to perform both a reference signal measurement (Figure 4 and paragraph 63, In a second process 412, the UE 104 may measure the actual beam strength (e.g., an RSRP) of the first transmit beam used to transmit the second communication 410) and reference signal prediction (Figure 4 and paragraph 62, In a first process 408, the UE 104 may determine a predicted strength of a first transmit beam…the UE 104 may utilize a prediction mechanism to predict the strength of the first transmit beam…the prediction mechanism may predict the RSRP of the first transmit beam) for at least one time instance (Paragraph 62, at a second time (e.g., t) prior to the first time) for validating the reference signal prediction (Paragraph 27, for determining whether the beam-strength predictions of the prediction mechanism are reliable predictions; Paragraphs 76 and 98, for determining reliability of a beam prediction mechanism). Regarding claim 35, Pezeshki et al. disclose wherein the instructions, when executed by the at least one processor, further cause the network device at least to: transmit an indication to the user device (Figure 4 and paragraph 52, the BS 102 may transmit, to the UE 104, a first communication 406 having a quality metric; Paragraphs 54-55, 59-61, communication 406 includes beam identification and metrics to be used by the UE 104 to determine reliability of beam prediction mechanism) to evaluate whether there is a success or failure of the reference signal prediction for the at least one time instance (Figures 4 and 5 and paragraphs 64-74, UE evaluating whether quality metric is satisfied [success] or not satisfied [failure] based on the quality metric indication received from the BS in step 406 of figure 4; Paragraph 62, at a second time (e.g., t) prior to the first time). Regarding claim 39, Pezeshki et al. disclose wherein the instructions, when executed by the at least one processor, further cause the network device at least to: transmit an indication to the user device (Paragraph 65, the BS 102 may configure the UE 104 to transmit statistics; Paragraph 66, the UE 104 may transmit statistics in response to a BS 102 request for statistics) to report the number of measured time instances, the number of predicted time instances, and/or the number of measured and predicted time instances (Paragraph 65, the statistics may include statistics regarding the percentage of time that the quality metric is satisfied at the UE 104 for one or more transmit beams, such as over a time period. For example, UE 104 may indicate to the BS 102, every X measurement instances (e.g., where X is an integer such as 1, 2, 5, 20, etc.) a percentage of times the quality metric was satisfied over the X measurement instances. For example, if the quality metric was satisfied Y times over the X measurement instances, the UE 104 may report Y/X as the percentage to BS 102) . 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. 07-22-aia AIA Claim (s) 29, 38 and 40 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pezeshki et al . as applied to claim s 28, 34 and 39 above, and further in view of Pezeshki et al. (US 2022/0216938), hereinafter referred to as Pezeshki II . Regarding claim 29, Pezeshki et al. disclose the claimed invention above as well as wherein the instructions, when executed by the at least one processor, further cause the user device at least to maintain performing reference signal prediction for the at least one time instance (Pezeshki et al., Figure 5 and paragraphs 72-73, at a third block 514 the UE 104 may determine to retrain or update the prediction mechanism [maintaining performing reference signal prediction] used in the first block 504…the UE 104 determining that the quality metric is not satisfied…retraining or updating the neural network may include retraining the prediction mechanism with additional samples of beam measurement information 502, additional classifiers (e.g., a classifier corresponding to the UE's mobility status), and/or any suitable information for improving the prediction mechanism's ability to predict a transmit beam RSRP…UE 104 may advance to the third block 514 and retrain or update the prediction mechanism, such as based at least in part on the difference between the first RSRP and the second RSRP not being within the first tolerance level for a threshold number of times or more than the threshold number of times). Pezeshki et al. do not disclose the following limitations that are disclosed by Pezeshki II: the UE receiving, from a network device, indication to maintain and performing reference signal prediction according to the indication (Pezeshki II, Paragraph 136 and figure 7, if at operation 750, the UE 104 determines that the triggering condition has occurred, at operation 760, the UE 104 can retrain the neural network 500 per operations 660 [receive a command to retrain, i.e. receive an indication to maintain] and 670 of FIG. 6 described above; Paragraph 122, Examples of such triggering conditions can further include…channel estimation errors when a reference signal is used for channel estimation (e.g., when channel estimation error reaches and/or exceeds a configurable threshold more than a number of times over a period of time…). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Pezeshki et al. with the cited disclosure from Pezeshki II in order to accurately tune (Pezeshki II, Paragraph 110) the prediction mechanism of Pezeshki et al. Regarding claim 38, Pezeshki et al. disclose the claimed invention above as well as wherein the instructions, when executed by the at least one processor, further cause the network device at least to: receive, from the user device, a failure indication of the reference signal prediction for the at least one time instance (Pezeshki et al., Figure 4 and paragraph 65, In a third communication 416, the UE 104 may transmit, to the BS 102, statistics of whether the quality metric is satisfied; Figure 5 and paragraph 74, At a fourth block 516, the UE 104 may also send feedback to the BS, wherein the feedback provides statistics of whether the quality metric is satisfied. In some examples, the UE 104 may feedback the difference between the first RSRP value and the second RSRP value if the difference is greater than the quality metric (e.g., the difference does not satisfy [failure] the quality metric). In this case, the UE 104 may only provide feedback when the quality metric is not satisfied. In another example, the UE 104 may provide an indication of a number of times the quality metric has been satisfied and/or unsatisfied within a duration of time) and the user device to maintain performing reference signal prediction for the at least one time instance (Pezeshki et al., Figure 5 and paragraphs 72-73, at a third block 514 the UE 104 may determine to retrain or update the prediction mechanism [maintaining performing reference signal prediction] used in the first block 504…the UE 104 determining that the quality metric is not satisfied…retraining or updating the neural network may include retraining the prediction mechanism with additional samples of beam measurement information 502, additional classifiers (e.g., a classifier corresponding to the UE's mobility status), and/or any suitable information for improving the prediction mechanism's ability to predict a transmit beam RSRP…UE 104 may advance to the third block 514 and retrain or update the prediction mechanism, such as based at least in part on the difference between the first RSRP and the second RSRP not being within the first tolerance level for a threshold number of times or more than the threshold number of times). Pezeshki et al. do not disclose the following limitations that are disclosed by Pezeshki II: the network device determining, based on the failure indication, to maintain (Pezeshki II, Paragraph 122, retraining command transmitted upon detection of triggering condition, the condition including channel estimation errors [failure indication] of a reference signal) and the network device transmitting an indication to the user device to maintain (Pezeshki II, Paragraph 136 and figure 7, if at operation 750, the UE 104 determines that the triggering condition has occurred, at operation 760, the UE 104 can retrain the neural network 500 per operations 660 [receive a command to retrain, i.e. receive an indication to maintain] and 670 of FIG. 6 described above; Paragraph 122, Examples of such triggering conditions can further include…channel estimation errors when a reference signal is used for channel estimation (e.g., when channel estimation error reaches and/or exceeds a configurable threshold more than a number of times over a period of time…). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Pezeshki et al. with the cited disclosure from Pezeshki II in order to accurately tune (Pezeshki II, Paragraph 110) the prediction mechanism of Pezeshki et al. Regarding claim 40, Pezeshki et al. disclose the claimed invention above as well as wherein the instructions, when executed by the at least one processor, further cause the network device at least to: receive, from the user device, assistance information for updating the number of measured time instances, the number of predicted time instances, and/or the number of measured and predicted time instances (Pezeshki et al., Paragraph 50, historical beam information as previous strengths of beams measured by the UE 104 included in a table maintained by the UE, the previous measured strengths corresponding to one or previous time instances or periods, the historical beam information [assistance information] being sued to develop a function the number network can used to predict future beam strength; Paragraph 65, measurement time instances maintained by the UE 104 as percentage of times the quality metric was satisfied over the X measurement instances; Paragraph 65, UE may indicate to the BS the measurement instances) Pezeshki et al. do not disclose the following limitations that are disclosed by Pezeshki II: the network device applies the assistance information (Pezeshki II, Paragraph 145 and figure 9, at operation 960, the base station 102 retrains the neural network 500 per operations 660 and 670 of FIG. 6 described above; Paragraph 122, Examples of such triggering conditions can further include…channel estimation errors when a reference signal is used for channel estimation (e.g., when channel estimation error reaches and/or exceeds a configurable threshold more than a number of times over a period of time…). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Pezeshki et al. with the cited disclosure from Pezeshki II in order to accurately tune (Pezeshki II, Paragraph 110) the prediction mechanism of Pezeshki et al . Allowable Subject Matter 12-151-08 AIA 07-43 12-51-08 Claim s 26, 27, 32, 33, 36, 37 and 41 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. 13-03-01 AIA The following is a statement of reasons for the indication of allowable subject matter: Regarding claims 26 and 36, the prior art does not disclose or adequately suggest an indication received/transmitted from a network device to perform reference signal prediction and stop reference signal measurement for a time instance after reference signal prediction has been successful; Regarding claims 27 and 37, the prior art does not disclose or adequately suggest an indication received/transmitted from a network device to perform both reference signal prediction and reference signal measurement for a second time instance after reference signal prediction has been successful; Regarding claims 32 and 41, the prior art discloses assistance information for updating the number of measurement time instances and/or predicted time instances, the assistance information being transmitted to the network device by the user device (See rejection of claim 29 above), but does not disclose or adequately suggest that the user device receives from the network device a confirmation to apply the assistance information; Regarding claim 33, the prior art discloses assistance information for updating the number of measurement time instances and/or predicted time instances, the assistance information being transmitted to the network device by the user device (See rejection of claim 29 above), but does not disclose or adequately suggest that the user device receives from the network device an indication to apply to use the updated number of measurement time instances and/or predicted time instances . Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to OTIS L THOMPSON, JR whose telephone number is (571)270-1953. The examiner can normally be reached Monday - Friday, 6:30am - 7:00pm. 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, Chirag G. Shah can be reached at (571)272-3144. 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. /OTIS L THOMPSON, JR/Primary Examiner, Art Unit 2477 June 12, 2026 Application/Control Number: 18/841,797 Page 2 Art Unit: 2477 Application/Control Number: 18/841,797 Page 3 Art Unit: 2477
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