Prosecution Insights
Last updated: April 19, 2026
Application No. 17/827,285

SLOT AGGREGATION TRIGGERED BY BEAM PREDICTION

Final Rejection §103
Filed
May 27, 2022
Examiner
WHITAKER, JUSTIN MICHAEL
Art Unit
2415
Tech Center
2400 — Computer Networks
Assignee
Qualcomm Incorporated
OA Round
2 (Final)
89%
Grant Probability
Favorable
3-4
OA Rounds
3y 2m
To Grant
99%
With Interview

Examiner Intelligence

Grants 89% — above average
89%
Career Allow Rate
8 granted / 9 resolved
+30.9% vs TC avg
Strong +17% interview lift
Without
With
+16.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
46 currently pending
Career history
55
Total Applications
across all art units

Statute-Specific Performance

§101
1.1%
-38.9% vs TC avg
§103
71.9%
+31.9% vs TC avg
§102
15.2%
-24.8% vs TC avg
§112
11.5%
-28.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 9 resolved cases

Office Action

§103
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 . Response to Amendment Applicant’s amendment filed on 12/15/2025 has been entered. Independent Claims 1, 14, 28, and 30 have been amended. No dependent claims have been amended. No claims have been cancelled. No claims are new and have been entered. Claims 1-30 are still pending in this application. Response to Arguments Applicant’s arguments filed on 12/15/2025 on pages 10-12 of applicant’s remark regarding Claims 1, 14, 28, and 30. The applicant argues that the combination of Zhu in view of Guan does not teach the amended claim to claim that the slot aggregation configuration has the UE repeat the same slot over the subset of candidate beams, as the independent claims have been amended to say that. Applicant’s arguments with respect to claim(s) 1, 14, 28, and 30, under 35 USC § 103, are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specified challenged in the argument. Applicant’s arguments filed on 12/15/2025 on page 11 of applicant’s remark regarding Claim # under 35 USC § 103. The applicant argues that Zhu in view of Guan, and further with Sun fails to teach selecting a slot aggregation as opposed to a single, optimal, beam. However, slot aggregation is a known technique, and it would be reasonable for one of average skill in the art to implement the slot aggregation techniques of Sun using the optimized beam selection techniques of Zhu. A beam is just a direction for a message to be sent, and that message can be configured using well known techniques in the art. Thus, the applicant here fails to patentably distinguish the claimed invention of selecting a slot aggregation as opposed to a single, optimal, beam from the teachings of Zhu in view of Guan. The applicant’s arguments have been fully considered, but are not persuasive. 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. Claim(s) 1-5, 7, 9, 11-12, 14-16, 19, 21-22, 24, and 26-30 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhu (Pub. No.: US 20210058131 A1, hereafter “Zhu”) in view of Guan (Pub. No.: US 20250030612 A1, hereafter “Guan”), and even further in view of Sun (Pub. No.: US 20200145998 A1, hereafter “Sun”). Regarding Claim 1, Claim 14, Claim 28, and Claim 30 Zhu teaches a method and apparatus comprising A method for wireless communications (Zhu Fig. 1: 100) at a user equipment (UE) (Zhu Fig. 1: 111), comprising: receiving (Zhu ¶0515, (1): in the given beam codebook), from a network entity (Zhu Fig. 1: 101, Base Station), a set of reference signals (Zhu ¶0515, (1): candidate beams, e.g. beams selected from reference signal transmissions, see ¶0166) associated with a set of candidate beams (Zhu ¶0515, (1): subset of all candidate beams) for communications with the network entity (Zhu ¶0515, (1): used by the terminal; Zhu teaches the UE receiving a codebook of multiple beams, and selecting one or more beams from a set of candidate beams); performing (Zhu ¶0515, (2): UE probes), based at least in part on measurements (Zhu ¶0515, (2): necessary measurement) of the set of reference signals (Zhu ¶0515, (2): probes the selected beams), a beam prediction process for the set of candidate beams (Zhu ¶0515, (2): generate the corresponding performance metrics; Zhu teaches collecting necessary measurements and generating a performance metric); identifying (Zhu ¶0515, (4): selects), based at least in part on the beam prediction process (Zhu ¶0515, (3): measurement beams), a slot aggregation configuration (Zhu ¶0515, (4): selects one or beams) comprising a subset of candidate beams of the set of candidate beams (Zhu ¶0515, (4): from the candidate beams; Zhu teaches selecting a beam from the candidate beams based off of measurement beams), and communicating (Zhu ¶0515, (4): communicates) with the network entity (Zhu ¶0515, (4): base station) in accordance with the slot aggregation configuration (Zhu ¶0515, (4): from the candidate beams; Zhu teaches communicating with the base station from the selected candidate beams that was originally selected from the reference signal transmissions). Claim 14 differs by the following limitation, which is also taught by the prior art, Zhu does not explicitly teach transmitting, to a user equipment (UE), control signaling configuring a machine learning module for performing a beam prediction process at the UE; However, Guan teaches transmitting (Guan ¶0113: transmission), to a user equipment (UE) (Guan Fig. 2: 210), control signaling (Guan ¶0113: CSI-RS) configuring a machine learning module (Guan ¶0113: ML-based) for performing a beam prediction process at the UE (Guan ¶0113: beam selection; Guan teaches a CSI-RS transmission to the UE for an ML-based beam management selection at the UE); It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu by way of Guan, to include an element that teaches a CSI transmission to the UE for an ML-based beam management selection at the UE, as taught by Guan in ¶0113, to improve ML models in air interface interactions, and improve detecting and handling any interface errors caused by the ML in a feedback loop. Zhu in view of Guan does not explicitly teach wherein the slot aggregation configuration indicates that the UE is to repeat transmission of a same slot over the subset of candidate beams; However, Sun teaches wherein the slot aggregation configuration (Sun ¶0038: configuration of slot aggregation) indicates that the UE (Sun ¶0038: UE receives from gNB) is to repeat transmission (Sun ¶0038: repeat PUSCH) of a same slot (Sun ¶0038: through aggregated slots) over the subset of candidate beams (Sun ¶0038: using different beams; Sun teaches a slot aggregation system for beam sweeping selection using the aggregated slot); It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu in view of Guan by way of Sun, to include an element that teaches a slot aggregation system for beam sweeping selection using the aggregated slot, as taught by Sun in ¶0038, to improve UE operation during a frequently changing environment, such as a crows or a moving vehicle, to optimize for that adjustment period. Claim 28 differs by the following limitation, which is also taught by the prior art, Zhu teaches a processor (Zhu Fig. 3: 340); memory coupled with the processor (Zhu Fig. 3: 360); and instructions stored in the memory and executable by the processor to cause the apparatus to (Zhu Fig. 3: 362; Zhu teaches a processor coupled to memory with application instructions inside of the memory): Regarding Claim 2, Claim 15, and Claim 29 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu further discloses identifying a first candidate beam of the set of candidate beams having a highest communications metric (Zhu ¶0521: best performance metrics) and a second subset of candidate beams (Zhu ¶0521: second tier of beam codewords) having a predicted communications metric satisfying a threshold (Zhu ¶0521: highest received signal powers), wherein the subset of candidate beams comprises the first candidate beam (Zhu ¶0526: first tier) and the second subset of candidate beams (Zhu ¶0526: hierarchical beam prediction; Zhu teaches a hierarchical beam prediction system in which there are two tiers of beam codewords that have performance metrics). Regarding Claim 3 and Claim 16 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu further discloses identifying a single candidate beam of the set of candidate beams having a predicted communications metric satisfying a threshold (Zhu ¶0515: best performance metric), wherein communicating with the network entity in accordance with the slot aggregation configuration comprises receiving a transmission in a slot via the single candidate beam (Zhu ¶0516: received signals; Zhu teaches using the best performance metric from the candidates to receive signals). Regarding Claim 4 and Claim 24 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu further discloses receiving, from the network entity, control signaling indicating a rule for identifying slot aggregation configurations (Zhu ¶0521: presented codebook) for sets of candidate beams based on the beam prediction process (Zhu ¶0521: beam codewords), wherein the identifying is based at least in part on the rule (Zhu ¶0521: selection method; Zhu teaches receiving a codebook with beam codewords to be selected from). Regarding Claim 5 and Claim 19 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu further discloses transmitting, to the network entity, a report indicating an output of the beam prediction process (Zhu ¶0543: update), the output comprising a second slot aggregation configuration (Zhu ¶0543: beam selection strategy) comprising a second subset of candidate beams of the set of candidate beams (Zhu ¶0543: beam selection; Zhu teaches communicating the base station the selected beam strategy to be used); and receiving, from the network entity and in response to the report, an indication of the slot aggregation configuration (Zhu ¶0543: terminal updates their beam selection strategy) comprising the subset of candidate beams different from the second slot aggregation configuration comprising the second subset of candidate beams (Zhu ¶0543: “type” of beam), wherein the identifying is based at least in part on the receiving the indication (Zhu ¶0543: update; Zhu teaches the base station updating their beam selection strategy by using the selected beam). Regarding Claim 7 and Claim 21 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu further discloses transmitting (Zhu ¶0543: update), to the network entity, a first message indicating the measurements of the set of reference signals (Zhu ¶0543: “type” of selection strategy; Zhu teaches the UE updating the base station the type of beams used for communication). Regarding Claim 9 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Guan teaches receiving, from the network entity, control signaling (Guan ¶0113: CSI-RS transmission) configuring a machine learning module (Guan ¶0113: ML-based), wherein performing the beam prediction process is based at least in part on the machine learning module (Guan ¶0113: beam selection; Guan teaches a transmission from the base station to the UE as a CSI-RS for the purpose for a machine learning system). It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu by way of Guan, to include an element that teaches a transmission from the base station to the UE as a CSI-RS for the purpose for a machine learning system, as taught by Guan in ¶0113, to improve ML models in air interface interactions, and improve detecting and handling any interface errors caused by the ML in a feedback loop. Regarding Claim 11 and Claim 26 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu further discloses receiving a same first transmission in a set of slots via the subset of candidate beams (Zhu ¶0510: second tier beam codewords): or transmitting a same second transmission in the set of slots via the subset of candidate beams (Not given patentable weight due to non-selective option in the claim; Zhu teaches a second tier of beam codewords sent in the same message as the first). Regarding Claim 12 and Claim 27 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu further discloses and transmitting, to the network entity, a report (Zhu ¶0543: measurement report) indicating the second measurements of the set of demodulation reference signals (Zhu ¶0535: second tier beam codewords; Zhu teaches the measurement report contains the second tier beam codeword measurements). Regarding Claim 22 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 21. Zhu further discloses performing, based at least in part on the measurements of the set of reference signals (Zhu ¶0532: measurement), a second beam prediction process for the set of candidate beams (Zhu ¶0531: second tier beam codewords), wherein the identifying is based at least in part on the second beam prediction process (Zhu ¶0531: selects), and wherein the second beam prediction process is the same as the beam prediction process at the UE (Zhu ¶0531: similar to Type-IV(a); Zhu teaches beam measurement based on the second tier of beam codewords, and the selecting method is similar to the first beam selection process). Claim(s) 6, 8, 10, 13, 17-18, 20, 23, and 25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhu (Pub. No.: US 20210058131 A1, hereafter “Zhu”) in view of Guan (Pub. No.: US 20250030612 A1, hereafter “Guan”), even further in view of Sun (Pub. No.: US 20200145998 A1, hereafter “Sun”), and further in view of Chen (Pub. No.: US 20220095307 A1, hereafter “Chen”). Regarding Claim 6 and Claim 20 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Zhu teaches transmitting, to the network entity, a report (Zhu ¶0543: measurement report) indicating the subset of candidate beams (Zhu ¶0543: updates) based at least in part on the beam prediction process for the set of candidate beams (Zhu ¶0543: beam section strategy; Zhu teaches a measurement report for the purposes of updating a beam selection strategy); Zhu in view of Guan, further in view of Sun does not explicitly teach and receiving, from the network entity, an acknowledgment message for the report, wherein communicating with the network entity in accordance with the slot aggregation configuration is based at least in part on receiving the acknowledgment message a defined period of time before the communicating However, Chen teaches transmitting (Chen ¶0077: feedback information), to the network entity, a report indicating the subset of candidate beams based at least in part on the beam prediction process for the set of candidate beams (Chen ¶0077: beam selection information); and receiving, from the network entity, an acknowledgment message for the report (Chen ¶0085: ACK/NACK), wherein communicating with the network entity in accordance with the slot aggregation configuration (Chen ¶0089: slot aggregation format for ACK/NACK information) is based at least in part on receiving the acknowledgment message a defined period of time before the communicating (Chen ¶0085: ACK/NACK reporting time; Chen teaches feedback information, including the beam selection information, in an ACK/NACK within a slot aggregation format, and within a set time). It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu in view of Guan, further in view of Sun, further by way of Chen, to include an element that teaches feedback information, including the beam selection information, in an ACK/NACK within a slot aggregation format, and within a set time, as taught by Chen in ¶0085, to improve transmission performance during data transmission efficiently and the problems of low data transmission flexibility and low transmission efficiency caused by less powerful aggregated slots from related art. Regarding Claim 8 and Claim 17 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 7. Chen teaches receiving, from the network entity and in response to the first message (Chen Fig. 2: S202), a second message comprising an indication of the slot aggregation configuration (Chen Fig. 2: S206) comprising the subset of candidate beams (Chen ¶0077: beam selection information), wherein the identifying is based at least in part on the receiving the indication (Chen ¶0077: indication information; Chen teaches receiving feedback and a second message that includes a slot aggregation configuration containing beam information). It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu in view of Guan, further in view of Sun, further by way of Chen, to include an element that teaches receiving feedback and a second message that includes a slot aggregation configuration containing beam information, as taught by Chen in Fig. 2 and ¶0077, to improve transmission performance during data transmission efficiently and the problems of low data transmission flexibility and low transmission efficiency caused by less powerful aggregated slots from related art. Regarding Claim 10 and Claim 25 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 1. Guan teaches transmitting, to the network entity, a first control message indicating a capability of the UE to identify slot aggregation configurations for sets of candidate beams (Guan ¶0104: capability-related information) based on the beam prediction process performed at the UE (Guan Fig. 2: 210; Guan teaches the UE transmitting capability-related information towards the base station); It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu by way of Guan, to include an element that teaches the UE transmitting capability-related information towards the base station, as taught by Guan in Fig. 2 and ¶0104, to improve ML models in air interface interactions, and improve detecting and handling any interface errors caused by the ML in a feedback loop. Zhu in view of Guan, further in view of Sun does not explicitly teach and receiving, from the network entity and in response to the first control message, a second control message configuring the UE to identify the slot aggregation configurations for sets of candidate beams based on the beam prediction process performed at the UE. However, Chen teaches and receiving, from the network entity and in response to the first control message, a second control message (Chen ¶0067: DCI) configuring the UE to identify the slot aggregation configurations for sets of candidate (Chen ¶0067: slot aggregation subgroup) beams based on the beam prediction process performed at the UE (Chen ¶0067: slot aggregation process, e.g. beam selection, see ¶0077; Chen teaches a DCI used to configure the slot aggregation subgroup for the subgroup aggregation process, which includes beam selection). It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu in view of Guan, further in view of Sun, further by way of Chen, to include an element that teaches a DCI used to configure the slot aggregation subgroup for the subgroup aggregation process, which includes beam selection, as taught by Chen in ¶0067 and ¶0077, to improve transmission performance during data transmission efficiently and the problems of low data transmission flexibility and low transmission efficiency caused by less powerful aggregated slots from related art. Regarding Claim 13 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 12. Zhu further discloses receiving, from the network entity and in response to the report (Chen ¶0077: feedback information), a control message indicating a termination of the slot aggregation configuration (Chen ¶0077: slot aggregation structure) and a selection of a first beam of the subset of candidate beams (Chen ¶0077: beam selection information; Chen teaches the feedback information includes the slot aggregation structure and beam selection information). It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu in view of Guan, further in view of Sun, even further by way of Chen, to include an element that teaches the feedback information includes the slot aggregation structure and beam selection information, as taught by Chen in ¶0077, to improve transmission performance during data transmission efficiently and the problems of low data transmission flexibility and low transmission efficiency caused by less powerful aggregated slots from related art. Regarding Claim 18 Zhu in view of Guan, further in view of Sun and further in view of Chen teach the method and apparatus as explained above in Claim 17. Chen further teaches transmitting, to the UE and in response to the report (Chen ¶0077: feedback information), an indication of the slot aggregation configuration (Chen ¶0077: slot aggregation structure) comprising the subset of candidate beams different from the second slot aggregation configuration comprising the second subset of candidate beams (Chen ¶0077: beam selection information; Chen teaches the feedback information containing the slot aggregation structure and the beam selection information). It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu in view of Guan, further in view of Sun, even further by way of Chen, to include an element that teaches the feedback information containing the slot aggregation structure and the beam selection information, as taught by Chen in ¶0077, to improve transmission performance during data transmission efficiently and the problems of low data transmission flexibility and low transmission efficiency caused by less powerful aggregated slots from related art. Regarding Claim 23 Zhu in view of Guan, further in view of Sun teach the method and apparatus as explained above in Claim 21. Chen further teaches transmitting, to the UE and in response to the second message, a third message (Chen Fig. 1: S106) comprising an indication of the slot aggregation configuration comprising the subset of candidate beams (Chen ¶0077: feedback information; Chen teaches a different message containing feedback information). It would have been obvious for one skilled in the art, before the effective filing date of the claimed invention, to modify Zhu in view of Guan, further in view of Sun, even further by way of Chen, to include an element that teaches a different message containing feedback information, as taught by Chen in ¶0077, to improve transmission performance during data transmission efficiently and the problems of low data transmission flexibility and low transmission efficiency caused by less powerful aggregated slots from related art. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any 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. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JUSTIN MICHAEL WHITAKER whose telephone number is (703)756-4763. The examiner can normally be reached Monday - Thursday 7:30am - 4:00pm. 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, Jeffrey Rutkowski can be reached on (571) 270-1215. 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. /JUSTIN MICHAEL WHITAKER/Examiner, Art Unit 2415 /Sudesh M. Patidar/Primary Examiner, Art Unit 2415
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Prosecution Timeline

May 27, 2022
Application Filed
Sep 03, 2025
Non-Final Rejection — §103
Dec 15, 2025
Response Filed
Feb 13, 2026
Final Rejection — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
89%
Grant Probability
99%
With Interview (+16.7%)
3y 2m
Median Time to Grant
Moderate
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