Prosecution Insights
Last updated: July 17, 2026
Application No. 18/547,285

REPORTING BEAM SEQUENCE FOR WIRELESS COMMUNICATION

Final Rejection §103§112
Filed
Aug 21, 2023
Priority
Feb 19, 2021 — provisional 63/151,604 +1 more
Examiner
ANDERSON, MARGARET MARIE
Art Unit
2412
Tech Center
2400 — Computer Networks
Assignee
Lenovo (United States) Inc.
OA Round
2 (Final)
70%
Grant Probability
Favorable
3-4
OA Rounds
1m
Est. Remaining
89%
With Interview

Examiner Intelligence

Grants 70% — above average
70%
Career Allowance Rate
38 granted / 54 resolved
+12.4% vs TC avg
Strong +19% interview lift
Without
With
+18.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
28 currently pending
Career history
90
Total Applications
across all art units

Statute-Specific Performance

§103
92.3%
+52.3% vs TC avg
§102
7.3%
-32.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 54 resolved cases

Office Action

§103 §112
MMADETAILED ACTION 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 . This action is responsive to patent application filed August 21, 2023, and response to office action filed April 13, 2026. Claims 1-15 are pending. Claims 8 and 14, 15 have been amended. Claims 17-20 have been added. Information Disclosure Statement The information disclosure statement (IDS) submitted on August 21, 2023 was in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Response to Arguments Applicant's arguments filed April 13, 2026 have been fully considered but they are not persuasive. Regarding Applicant’s arguments regarding 35 USC § 112, Applicant argues that the use of the word “best” is not a relative term but a “superlative” adjective which “selects an extreme value from a defined set” and “identifies the top-ranked element among a group of candidates according to whatever metric or criterion is contextually established.” However, Applicant’s specification does not provide contextual information, metric or criterion that enables one of ordinary skill in the art to inform “with reasonable certainty” what a “best” beam actually is in context of any other beams. In fact, each iteration of “best” uses the word “best” to define “best.” For example, para. [0056]: The remote unit 105 may be required to report the best radio resources (e.g., beams, TRPs) for communication by measuring one or more Channel State Information Reference Signals ("CSI-RS") transmitted by a base unit 121, determining a sequence of best beams (alternatively, a sequency of best TRPs) and transmitting a report 127 with the sequence of best beams (or best TRPs) to the base unit 121. In para. [0077]: Corresponding to each CSI report setting, at least one best beam is reported, i.e., CRI/SSBRI and corresponding duration for which the reported beam is applicable. In one implementation, the CSI reporting quantity associated with reporting a sequence of beams (e.g., parameter "cri-duration-RSRP" or "ssb-Index-duration-RSRP") is used to indicate the duration for which each of the indicated CRI/SSBRI is valid. In para. [0093]: Corresponding to each CSI report setting, at least one best beam/TRP is reported, i.e., CRI/SSBRI and corresponding duration for which the reported TRP is applicable. In para. [0178]: The processor 605 performs beam quality measurements on resources configured by the RAN (i.e., by receiving and determines a sequence of beams based on the measurements, where the sequence of beams comprises a series of best beams for a period of time. It is not clear how a “best” beam or “series of best beams” is defined or differentiated from any other beam or TRP. Examiner further notes that the issue of “best” was litigated in the Federal Circuit Court of Appeals in Akamai Technologies, Inc. v. Mediapoint, Inc., (2024-1571) and in precedential opinion on November 25, 2025, the court rules that claims using the words “optimal” and “best” were invalid for indefiniteness. Although MediaPointe argued that “best” and “optimal routes” should be construed to mean a path determined to be among the most favorable under the circumstances based on one or more characteristics, the court ruled that since there was no detail to explain how to consistently use reliability information to determine “optimal/best” and the specification “does not include bounds for the terms “best” and “optimal”” the claims were indefinite. Here, as in Akamai, the specification lacks “bounds for the term ‘best’” and is indefinite. Regarding Applicant’s arguments regarding the rejection of claim 1 that Kaya does not teach that “the UE determine a sequence of beams based on the measurements, wherein the sequence of beams comprises a series of best beams for a period of time” and that “the UE reports the sequence of beams to the RAN”, Examiner respectfully disagrees. Kaya para. [0049] teaches that it is the UE that measures and reports the “best beams” to a base station: “Thus, the UE may be asked to measure a smaller set of beams (e.g., measure the next 7 beams/resources indicated in the predicted future beam sequence, instead of a larger set of beams/resources), and/or to report a smaller set of beams (e.g., report the RSRP of the best 2 beams, rather than reporting a best 4 beams) that are indicated in the predicted future beam sequence.” Response to Amendment The amendments to the specification and claims are appreciated and have been accepted. Claim Objections Claim 15 objected to because of the following informalities: Claim 15 has been amended to recite a base station with a processor coupled to memory and “configured to cause the UE to:” Examiner believes that the “cause the UE to” is a typo and what was intended was “cause the base station to” due to the structure of the claim and the lack of antecedent basis for “the UE”. Appropriate correction is required. Claim Rejections - 35 USC § 112 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. Claims 1, 14 and 15 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. The term “best” in claim 1, 14, and 15 is a relative term which renders the claims indefinite. The term “best” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The specification recites “best” eighteen times in a conclusory fashion such as “where the sequence of beams contains a series of best beams for a period of time” repeatedly, but the specification does not identify a standard for what is “best”. Additionally, Claim 15, lines 4-5 recites the limitation “a processor coupled with the memory and configured to cause the UE to: transmit, to a user equipment (“UE”), a configuration for reporting a sequence of beams that are applicable for wireless communication” There is insufficient antecedent basis for the first iteration of “UE” limitation in the claim. 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. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US Pat. App. 20230246785 to Marcus Grossmann et al. (hereinafter Grossman) in view of US Pat. Pub. 20220190883 to Aliye Ozge Kaya and Harish Viswanathan (herein after Kaya) . Regarding claim 1, Grossman in view of Kaya teaches a method at a User Equipment (UE), the method comprising: receiving a configuration from a radio access network ("RAN") to report a sequence of beams that are applicable for wireless communication; (Grossman para. [0029] teaches “the UE performs measurements on the DL RS resources according to the instructions provided by the network node or according to the instructions fixed in the specifications and the UE provides CSI quantities the network node has indicated to report in the CSI report.”) performing beam quality measurements on resources configured by the RAN; (Grossman para. [0077] teaches “Following the measurements, the UE sends a beam report to the gNB. The beam report comprises the indices of 1≤L≤4 configured DL RSs (essentially, L DL Tx beam directions, with each beam direction resulting from the use of a specific spatial filter at the gNB) along with the received power in each of the RSs [4]. With the help of the beam report, the gNB determines one or more suitable DL Tx beam direction(s), i.e., spatial filter(s) for the transmission of the PDCCH(s) and the PDSCH.”) Grossman does NOT specifically teach determining a sequence of beams based on the measurements, wherein the sequence of beams comprises a series of best beams for a period of time;. In the analogous art of 3GPP 5G wireless communications, Kaya teaches determining a sequence of beams based on the measurements, wherein the sequence of beams comprises a series of best beams for a period of time. (Kaya para. [0047]- [0049] teaches that a UE may be asked to report a sequence of best beams in which a “future beam sequence for a UE may indicate a predicted beam (e.g., identified with a specific beam index) and a probability, for each of a plurality of beam sampling intervals (e.g., for every 10 ms interval into the future)”. “Thus, the UE may be asked to measure a smaller set of beams (e.g., measure the next 7 beams/resources indicated in the predicted future beam sequence, instead of a larger set of beams/resources), and/or to report a smaller set of beams (e.g., report the RSRP of the best 2 beams, rather than reporting a best 4 beams) that are indicated in the predicted future beam sequence..) and reporting the sequence of beams to the RAN. (Kaya para. [0049] teaches that the best beams are reported) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 2, Grossman does NOT teach the method of claim 1, wherein reporting the sequence of beams comprises reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication, wherein the wireless communication comprises downlink reception, uplink transmission, or a combination thereof. In the analogous art of 3GPP 5G wireless communications, Kaya teaches reporting the sequence of beams comprises reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication, wherein the wireless communication comprises downlink reception, uplink transmission, or a combination thereof (Kaya teaches in para. [0067] for example teaches “Instead of making beam refinement measurement requests to the UE on a large set of beams, example embodiments may allow configuring of CSI-RS resources for beam refinement and measurement reports by predicting the set of beams that will most likely best serve the user/UE over a period of time, e.g., over the next several hundred milliseconds. Accurate prediction enables reduction in the set of beams for which measurement reporting will be needed.” Kaya para. [0057] teaches that the beam sequence is used as a basis for a transmit beam used by the BS for downlink transmission to the UE and by the BS for a receive beam for uplink reception.) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 3, Grossman does NOT teach the method of claim 2, wherein reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication comprises reporting a single duration that is applicable for each of the beams within the reported sequence. In the analogous art of 3GPP 5G wireless communications, Kaya teaches reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication comprises reporting a single duration that is applicable for each of the beams within the reported sequence. (Kaya teaches in para. [0078] and Fig. 6 reporting a beam index for each beam in a beam sequence according to 10 ms intervals wherein no switching occurs if a blockage lasts less than 5 ms: PNG media_image1.png 765 1064 media_image1.png Greyscale It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 4, Grossman does NOT teach the method of claim 2, wherein reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication comprises reporting a separate duration for each of the beams within the reported sequence. In the analogous art of 3GPP 5G wireless communication, Kaya teaches wherein reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication comprises reporting a separate duration for each of the beams within the reported sequence. (Kaya teaches as shown in Fig. 9 determining a sequence wherein the sequence generation includes as taught in para. [0085] as shown a duration for each of the beams includes a separate duration for each beam in the sequence and switching criteria: PNG media_image2.png 764 1090 media_image2.png Greyscale It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 5, Grossman does NOT teach the method of claim 2, wherein reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication comprises reporting a total duration within which the entire sequence of reported beams is applicable, wherein a separate duration for each of the beams is determinable based on a total number of beams in the sequence of beams and the total duration. In the analogous art of 3GPP 5G wireless communication, Kaya teaches wherein reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication comprises reporting a total duration within which the entire sequence of reported beams is applicable, wherein a separate duration for each of the beams is determinable based on a total number of beams in the sequence of beams and the total duration.(Kaya teaches in para. [0047] a separate duration of each of a set of beams can be determinable based on a known total number of beams in a predicted beam sequence “over a period of time that may be the same or very similar, or at least have a number of common beams that were used by UEs over time”). It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 6, Grossman does NOT teach the method of claim 1, wherein reporting the sequence of beams comprises indicating each of the reported beams within the sequence by a resource index value, said resource index value comprising one of: a Channel State Information Reference Signal Resource Index ("CR1"), and a Synchronization Signal/Physical Broadcast Channel Block Resource Index ("SSBRI"). In the analogous art of 3GPP 5G wireless communication, Kaya teaches wherein reporting the sequence of beams comprises indicating each of the reported beams within the sequence by a resource index value, said resource index value comprising one of: a Channel State Information Reference Signal Resource Index ("CRI"), and a Synchronization Signal/Physical Broadcast Channel Block Resource Index ("SSBRI"). (Kaya para. [0041] teaches that “CSI (channel state information) may include Channel Quality Indicator (CQI), precoding matrix indicator (PMI), CSI-RS resource indicator (CRI), SS/PBCH Block Resource indicator (SSBRI), layer indicator (LI), rank indicator (RI) and/or L1-RSRP (reference signal received power). The CSI-RS resources may be periodic, semi-persistent, or aperiodic, for example.” It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring including CRI and SSBRI . Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 7, Grossman teaches method of claim 1, wherein the reported sequence of beams corresponds to a sequence of Transmission Reception Points ("TRPs"), wherein each beam within the sequence of beams is associated with a different Transmission Reception Point ("TRP"). (Grossman para. [0082] teaches that “Link adaptation for multi-frequency band, multi-beam and/or multi-TRP/panel downlink-based transmissions requires knowledge of the CSI at the serving gNB from the UE with respect to each frequency band, beam and/or TRP.”) Regarding claim 8, Grossman does NOT teach the method of claim 1, wherein reporting the sequence of beams to the RAN comprises reporting at least one beam quality for each beam within the sequence of beams, the at least one beam quality comprising one or more of: Channel Quality Indicator ("CQI"), Rank Indicator ("RI"), Layer Indicator ("LI"), Precoding Matrix Indicator ("PMI"), Layer-1 Reference Signal Received Power ("L1-RSRP"), Layer-1 Signal-to-Interference- Plus-Noise Ratio ("Li-SINR"), or some combination thereof. In the analogous art of 3GPP 5G wireless communication, Kaya teaches wherein reporting the sequence of beams to the RAN comprises reporting at least one beam quality for each beam within the sequence of beam, the at least one beam quality comprising one or more of: Channel Quality Indicator ("CQI"), Rank Indicator ("RI"), Layer Indicator ("LI"), Precoding Matrix Indicator ("PMI"), Layer-1 Reference Signal Received Power ("L1-RSRP"), Layer-1 Signal-to-Interference- Plus-Noise Ratio ("Li-SINR"), or some combination thereof. (Kaya teaches in para. [0090] “a beam sequence (a past beam sequence) may be generated for a UE using the beam indices serving the UE in the past, or beam indices identified via UE measurement reports, which are then input to the beam sequence model or neural network to predict the next beam indices. These beam indices may be prioritized in L1-RSRP monitoring (e.g., beam indices input to the beam sequence model may use beams that were reported as having a highest RSRP for each of multiple sampling intervals, e.g., every 10 ms).”) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring including an L1-RSRP for each beam. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 9, Grossman does NOT teach the method of claim 1, wherein receiving the configuration from the RAN comprises receiving a configuration with one or more Channel State Information ("CSI") reporting settings with one or more CSI resources settings, wherein performing the beam quality measurements comprises performing CSI measurements on multiple configured CSI resources. In the analogous art of 3GPP 5G wireless communication, Kaya teaches wherein receiving the configuration from the RAN comprises receiving a configuration with one or more Channel State Information ("CSI") reporting settings with one or more CSI resources settings, wherein performing the beam quality measurements comprises performing CSI measurements on multiple configured CSI resources. (Kaya para. [0072] teaches “a BS may use CSI-RS feedback (e.g., measurement reports) during training phase to gather data. Thus, a source of this data may include measurement reports (and/or a list of beams actually used by a BS for a UE) for estimating the quality of different beams for a UE/user(s). When BSs are first deployed, they may be operated in a training mode where beam refinement procedures are implemented with extensive CSI-reporting configuration. During this time each UE may be requested to report a substantial number of measurement reports for estimating the quality e.g., based on a RSRP or other signal measurement) of different beams as the UE obtains service or is connected to the BS/gNB.”) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring including CSI reporting. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 10, Grossman teaches method of claim 9, wherein the UE is configured with a single CSI reporting setting with a single CSI resource setting, wherein a Quasi-Co-Location Type-D assumption of the configured CSI resources to perform CSI measurements is time varying. (Grossman teaches in para. [0077] the UE may receive an indication of Rx beams via a QCL-TypeD assumption with a CSI-RS. “In a beam sweeping procedure, the gNB configures a set of DL RSs (CSI-RS or SSB) via RRC for the UE to measure the set of DL RSs” Examiner interprets “time varying” as including a beam sweeping procedure for the measurements.) Regarding claim 11, Grossman teaches method of claim 9, wherein the UE is configured with a single CSI reporting setting with multiple CSI resource settings, wherein one of the beams within the sequence is associated with a CSI resource setting of the multiple CSI resource settings. (Grossman para. [0119] teaches a CSI report may include a subset or combination of CSI-RS resources in a single CSI report. Further Grossman para. [0110] teaches that CSI reporting may include reporting for “one or more TRP(s) or beams” to enable dynamic switching associated with a TRP/beam and UE based on the CSI reported by the UE.) Regarding claim 12, Grossman teaches method of claim 9, wherein the UE is configured with multiple CSI reporting settings, each report setting associated with multiple CSI resource settings, wherein each of the CSI reporting setting corresponds to one of the reported beams within the sequence. (Grossman para. [0132] teaches settings for CSI reporting for a combination of beams/TRPs “based on multiple subsets of resources or resource combinations” associated with a combination of beams or TRBS including a subset. para. [0133] includes a CSI report wherein the settings is individual different beams, such as only two.) Regarding claim 13, Grossman teaches method of claim 9, wherein each CSI reporting setting is associated with one or more of: a channel measurement resource setting, an interference measurements resource setting, or some combination thereof. (Grossman para. [0147] teaches that “In addition the CSI report configuration may include one or more sets of resources for interference measurement.” Examiner notes that the “or” languages negates requiring each element recited in the “one or more of” list.) Regarding claim 14, Grossman in view of Kaya teaches A user equipment (“UE”) for wireless communication, comprising: a memory; (Grossman Fig. 6, memory module 620) and a processor (Grossman para. [0272] and Fig. 6 processor 610) coupled with the memory and configured to cause the UE to: receive, from a radio access network (“RAN”), a configuration for reporting a sequence of beams that are applicable for wireless communication; (Grossman para. [0029] teaches “the UE performs measurements on the DL RS resources according to the instructions provided by the network node. Grossman para. [0077] teaches that in a beam sweeping procedure, the gNB configures a set of DL RSs (CSI-RS or SSB) via RRC for the UE to measure the set of DL RSs.) performs beam quality measurements on resources configured by the RAN; ; (Grossman para. [0077] teaches “Following the measurements, the UE sends a beam report to the gNB. The beam report comprises the indices of 1≤L≤4 configured DL RSs (essentially, L DL Tx beam directions, with each beam direction resulting from the use of a specific spatial filter at the gNB) along with the received power in each of the RSs [4]. With the help of the beam report, the gNB determines one or more suitable DL Tx beam direction(s), i.e., spatial filter(s) for the transmission of the PDCCH(s) and the PDSCH.”) Grossman does NOT specifically teach determine a sequence of beams based on the measurements, wherein the sequence of beams comprises a series of best beams for a period of time;. In the analogous art of 3GPP 5G wireless communications, Kaya teaches determine a sequence of beams based on the measurements, wherein the sequence of beams comprises a series of best beams for a period of time. (Kaya para. [0049] teaches reporting a sequence of best beams in which “measure the next 7 beams/resources indicated in the predicted future beam sequence, instead of a larger set of beams/resources), and/or to report a smaller set of beams (e.g., report the RSRP of the best 2 beams, rather than reporting a best 4 beams” Examiner interprets the “future” next 7 beams as being with respect to a period of time.) and transmit, to the RAN (Grossman para. [0272] and Fig. 6 transmitter circuit 650) that reports that indicate the sequence of beams to the RAN. (Kaya para. [0049] teaches that the best beams are reported) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 15, Grossman in view of Kaya teaches A base station for wireless communication, (Grossman para. [0276] and Fig. 7 network node 700), comprising: a memory; (Grossman Fig. 7 memory module 720) and a processor coupled with the memory and configured to cause the UE to: (Grossman para. [0276] and Fig. 7 processor 710) transmit to a user equipment (“UE”), a configuration for reporting a sequence of beams that are applicable for wireless communication; (Grossman para. [0029] teaches “the UE performs measurements on the DL RS resources according to the instructions provided by the network node or according to the instructions fixed in the specifications and the UE provides CSI quantities the network node has indicated to report in the CSI report.”) transmit one or more reference signals using one or more resources configured by radio access network (“RAN”); (Grossman para. [0276] teaches that the network node transmits and receives signals to/from the UE. Grossman para. [0038] – [0044] teaches the network node provides CSI report configurations/settings and CSI resource settings to the UE). and Grossman does NOT teach receive from the UE, a report that indicates a sequence of beams, wherein the sequence of beams comprises a series of best beams for a period of time. In the analogous art of 3GPP 5G wireless communications, Kaya teaches the receiver receives a sequence of beams from the UE, wherein the sequence of beams comprises a series of best beams for a period of time. (Kaya para. [0049] teaches the network node receiving a sequence of best beams which “measure the next 7 beams/resources indicated in the predicted future beam sequence, instead of a larger set of beams/resources), and/or receives a report of a smaller set of beams (e.g., report the RSRP of the best 2 beams, rather than reporting a best 4 beams” Examiner interprets the “future” next 7 beams as being with respect to a period of time.) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 16, Grossman in view of Kaya teach The base station of claim 15 as stated. Grossman does NOT teach wherein the report further indicates a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication, wherein the wireless communication comprises downlink reception, uplink transmission, or a combination thereof. In the analogous art of 3GPP 5G wireless communications, Kaya teaches reporting the sequence of beams comprises reporting a duration for which each of the beams in the reported sequence are applicable to be used for wireless communication, wherein the wireless communication comprises downlink reception, uplink transmission, or a combination thereof (Kaya teaches in para. [0067] for example teaches “Instead of making beam refinement measurement requests to the UE on a large set of beams, example embodiments may allow configuring of CSI-RS resources for beam refinement and measurement reports by predicting the set of beams that will most likely best serve the user/UE over a period of time, e.g., over the next several hundred milliseconds. Accurate prediction enables reduction in the set of beams for which measurement reporting will be needed.” Kaya para. [0057] teaches that the beam sequence is used as a basis for a transmit beam used by the BS for downlink transmission to the UE and by the BS for a receive beam for uplink reception.) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 17, Grossman in view of Kaya teach The base station of claim 15 as stated. Grossman does NOT teach wherein the report further indicates each of the reported beams within the sequence using resource index value, wherein the resource index value comprises one or more of: a Channel State Information Reference Signal Resource Index ("CRI"), or a Synchronization Signal/Physical Broadcast Channel Block Resource Index ("SSBRI"). In the analogous art of 3GPP 5G wireless communication, Kaya teaches wherein the report further indicates each of the reported beams within the sequence using resource index value, wherein the resource index value comprises one or more of: a Channel State Information Reference Signal Resource Index ("CRI"), or a Synchronization Signal/Physical Broadcast Channel Block Resource Index ("SSBRI"). . (Kaya para. [0041] teaches that “CSI (channel state information) may include Channel Quality Indicator (CQI), precoding matrix indicator (PMI), CSI-RS resource indicator (CRI), SS/PBCH Block Resource indicator (SSBRI), layer indicator (LI), rank indicator (RI) and/or L1-RSRP (reference signal received power). The CSI-RS resources may be periodic, semi-persistent, or aperiodic, for example.” Examiner further notes that the UE is directed to report the CSI-RS, see para. [0040] “to be measured by the UE”). It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring including CSI-RS . Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 18, Grossman in view of Kaya teaches The base station of claim 15 as stated. Grossman further teaches wherein the reported sequence of beams corresponds to a sequence of Transmission Reception Points ("TRPs"), wherein each beam within the sequence of beams is associated with a different Transmission Reception Point ("TRP"). (Grossman para. [0110] teaches that CSI reporting may include reporting for “one or more TRP(s) or beams” to enable dynamic switching associated with a TRP/beam and UE based on the CSI reported by the UE. By stating “TRP/beam”, each TRP is associated with a different beam.) Regarding claim 19, Grossman in view of Kaya teach The base station of claim 15 as stated. Grossman does NOT teach wherein the report further comprises at least one beam quality for each beam within the sequence of beams, wherein the at least one beam quality comprises one or more of: a Channel Quality Indicator ("CQI"), a Rank Indicator ("RI"), Layer Indicator ("LI"), a Precoding Matrix Indicator ("PMI"), a Layer-1 Reference Signal Received Power ("L1-RSRP") value, a Layer-1 Signal-to-Interference- Plus-Noise Ratio ("L1-SINR"), or some combination thereof. In the analogous art of 3GPP 5G wireless communication, Kaya teaches wherein the further comprises at least one beam quality for each beam within the sequence of beams, wherein the at least one beam quality comprises one or more of: a Channel Quality Indicator ("CQI"), Rank Indicator ("RI"), Layer Indicator ("LI"), Precoding Matrix Indicator ("PMI"), Layer-1 Reference Signal Received Power ("L1-RSRP"), Layer-1 Signal-to-Interference- Plus-Noise Ratio ("Li-SINR"), or some combination thereof. (Kaya teaches in para. [0090] “a beam sequence (a past beam sequence) may be generated for a UE using the beam indices serving the UE in the past, or beam indices identified via UE measurement reports, which are then input to the beam sequence model or neural network to predict the next beam indices. These beam indices may be prioritized in L1-RSRP monitoring (e.g., beam indices input to the beam sequence model may use beams that were reported as having a highest RSRP for each of multiple sampling intervals, e.g., every 10 ms).”) It would have been obvious to one of ordinary skill in that art to have combined Grossman and Kaya to teach beam sequence reporting and measuring including an L1-RSRP for each beam. Each of Grossman and Kaya are in the field of wireless communications and beam management. One of ordinary skill in the art would have been motivated to combine Kaya with Grossman in order to reduce the number of beam reports and improve the accuracy of the beam sequence as taught in para. [0049] of Kaya. Regarding claim 20, Grossman in view of Kaya teach The base station of claim 15 as stated. wherein the configuration further comprises one or more Channel State Information ("CSI") reporting settings associated with one or more CSI resources settings, wherein the sequence of beams is based on one or more CSI measurements associated with multiple configured CSI resources. (Grossman para. [0132] teaches settings for CSI reporting for a combination of beams/TRPs “based on multiple subsets of resources or resource combinations” associated with a combination of beams or TRPS including a subset. para. [0133] includes a CSI report wherein the settings is individual different beams, such as only two.) Conclusion THIS ACTION IS MADE FINAL. 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. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure includes US Pat. 10,075,852 to Maziar Nekovee “Apparatus and Method for Scheduling Beam Scheduling in Wireless Communications Network for teaching a beam sequence in a unique order within a set of beams based on link quality. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARGARET MARIE ANDERSON whose telephone number is (703)756-1068. The examiner can normally be reached M-F. 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, Charles Jiang can be reached at 571-270-7191. 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. /MARGARET MARIE ANDERSON/Examiner, Art Unit 2412 /CHARLES C JIANG/Supervisory Patent Examiner, Art Unit 2412
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Prosecution Timeline

Aug 21, 2023
Application Filed
Dec 12, 2025
Non-Final Rejection mailed — §103, §112
Apr 13, 2026
Response Filed
Jun 12, 2026
Final Rejection mailed — §103, §112 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
70%
Grant Probability
89%
With Interview (+18.8%)
3y 0m (~1m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 54 resolved cases by this examiner. Grant probability derived from career allowance rate.

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