Prosecution Insights
Last updated: May 29, 2026
Application No. 18/788,444

Methods for NW-Sided Model Data Collection with Low Measurement Reporting Overhead

Non-Final OA §103
Filed
Jul 30, 2024
Priority
Aug 11, 2023 — provisional 63/532,138
Examiner
HAILEGIORGIS, FITWI Y
Art Unit
2632
Tech Center
2600 — Communications
Assignee
Nokia Technologies Oy
OA Round
1 (Non-Final)
91%
Grant Probability
Favorable
1-2
OA Rounds
3m
Est. Remaining
74%
With Interview

Examiner Intelligence

Grants 91% — above average
91%
Career Allowance Rate
438 granted / 483 resolved
+28.7% vs TC avg
Minimal -16% lift
Without
With
+-16.3%
Interview Lift
resolved cases with interview
Fast prosecutor
2y 0m
Avg Prosecution
7 currently pending
Career history
494
Total Applications
across all art units

Statute-Specific Performance

§101
1.6%
-38.4% vs TC avg
§103
83.6%
+43.6% vs TC avg
§102
3.9%
-36.1% vs TC avg
§112
5.7%
-34.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 483 resolved cases

Office Action

§103
DETAILED 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 . Information Disclosure Statement The information disclosure statement (IDS) submitted on 10/29/2024 and 01/14/2025 have been considered and placed on record. Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 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) 1-6 and 10-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over QIAO et al. (US 2022/0337304 A1, hereinafter, “Qiao”) in view of WANG et al. (US 2024/0314606 A1, hereinafter, “Wang”). Consider claim 1, Qiao teaches an apparatus (figures 1 and 8) comprising: at least one processor (see at least figure 8 (802)); and at least one memory storing instructions (see at least figure 8 (803) and para. 329) that, when executed with the at least one processor, cause the apparatus at least to: transmit, to at least one user equipment, an indication of a measurement reporting scheme (see at least figure 3 (s301b2), paras. 122, 128 and 130, Qiao teaches the terminal device receives a notification message of measurement (i.e, RSSI measurement reporting scheme); transmit, to the at least one user equipment, at least one reference signal information for sending a reference signal on at least one first beam (see at least figure 3 (s302, s303), paras. 59, 135, 163 and 202, Qiao teaches transmit to the terminal at least one configuration information for sending a reference signal); receive, from the at least one user equipment, a set of reference signal received power measurements of one or more of the at least one reference signal, according to the measurement reporting scheme (see at least figure 3 (s310-s321), paras. 198, and 211, Qiao teaches the terminal transmits RSSI measurement report based on the at least one reference signal according to the report); and determine best beam(s) from a second set of beams based on the set of reference signal received power measurements (see at least figure 3 (s322b1), paras. 229 and 234-235, Qiao teaches determine best beam(s) from a first and/or second set of beams). Qiao teaches transmit, to the at least one user equipment, at least one reference signal information for sending a reference signal on at least one first beam (see above), however, did not explicitly teach transmit, to the at least one user equipment, at least one reference signal on at least one first beam. Wang teaches said limitation (see at figure 5 (502), figure 7 (710), paras. 83 and 131). It would have been obvious to one of ordinary skill in the art at the time of the application to modify the invention of Qiao and teach transmit, to the at least one user equipment, at least one reference signal on at least one first beam, as taught by Wang, thereby, allowing efficient beam management techniques. Qiao teaches determine best beam(s) from a second set of beams based on the set of reference signal received power measurements (see above), however, did not particularly teach provide the set of reference signal received power measurements to a machine learning model for prediction of best beams. Wang teaches said limitation (see at least paras. 24-25, 79 and 81, Wang teaches using power measurement values to predict best beam(s) using machine learning model). It would have been obvious to one of ordinary skill in the art at the time of the application to modify the invention of Qiao and teach provide the set of reference signal received power measurements to a machine learning model for prediction of best beams, as taught by Wang, thereby, allowing efficient beam management techniques. Consider claim 11: all of the limitations indicated in the method claim 11 are included in the apparatus claim 1, therefore, claim 11 is subjected to the same rejection applied to claim 1. Consider claim 16, Qiao teaches an apparatus (see at least figures 1, 7 and 8) comprising: at least one processor (see at least figures 7, 8 (802)); and at least one memory storing instructions that, when executed with the at least one processor (see figure 8 (802), para. 329) , cause the apparatus at least to: receive, from a network node, an indication of a measurement reporting scheme (see at least figure 3 (s301b2), paras. 122, 128 and 130, Qiao teaches the terminal device receives a notification message of measurement (i.e., RSSI measurement reporting scheme)); receive one reference signal information for a reference signal on at least one first beam (see at least figure 3 (s302, s303), paras. 59, 135, 141-144, Qiao teaches receive at least one configuration information for sending a reference signal); generate a set of reference signal received power measurements of one or more of the at least one reference signal based, at least partially, on the measurement reporting scheme (see at least figure 3 (s320), paras. 198, and 211, Qiao teaches the terminal perform RSSI measurement report based on the at least one reference signal according to the report); and transmit, to the network node, the set of reference signal received power measurements (see at least figure 3 (s321), paras. 198, and 211, Qiao teaches the terminal transmits RSSI measurement report based on the at least one reference signal according to the report). Qiao teaches receive one reference signal information for a reference signal on at least one first beam (see above), however, did not particularly teach measure at least one reference signal on at least one first beam. Wang teaches said technique (see at least figure 5 (502-504), figure 6 (620-630) and paras. 83-84). It would have been obvious to one of ordinary skill in the art at the time of the application to modify the invention of Qiao and teach measure at least one reference signal on at least one first beam, as taught by Wang, thereby, allowing efficient beam management techniques. Consider claims 2, 12 and 17, Qiao in view of Wang teaches the measurement reporting scheme comprises a scheme for reporting reference signal received power measurements of beams that are above a preconfigured threshold value (see at least para. 230 in Qiao). Consider claims 3, 13 and 18, Qiao in view of Wang teaches the measurement reporting scheme comprises a scheme for reporting a predetermined number of highest reference signal received power measurements of beams (see at least paras. 54, 304-305, Qiao teaches ‘quantize sum of RSSI measurements to the to-be-measured beams’). Consider claims 4, 14 and 19, Qiao in view of Wang teaches the measurement reporting scheme comprises a scheme for reporting reference signal received power measurements of beams that cover a predetermined percentage of a total received power measured from a plurality of beams (see at least paras. 11 and 55-58, Qiao teaches the scheme does not need to perform RSSI measurements in all directions, only selected to-be-measured beam(s), thus, predetermined number/percentage of total power). Consider claims 5, 15 and 20, Qiao in view of Wang teaches the set of reference signal received power measurements excludes a measurement for one or more of the at least one first beam (see at least paras. 11 and 55-58, Qiao teaches the scheme does not need to perform RSSI measurements in all directions). Consider claim 6, Qiao in view of Wang teaches providing the set of reference signal received power measurements to the machine learning model comprises the at least one memory (see at least paras. 5-6 and 9 in Wang) stores instructions that, when executed with the at least one processor (see at least para. 9 in Wang), cause the apparatus to: process the set of reference signal received power measurements (see at least figure 3 (310), paras. 24-25 in Wang); and provide the set of processed reference signal received power measurements to the machine learning model (see at least figure 3 (325) and paras. 24-25 and 81, Wang teaches ML model receiving and processing RSRP values). Consider claim 10, Qiao in view of Wang teaches the second set of beams comprises one of: downlink transmission beams, or downlink transmission beams and downlink reception beams (see at least paras. 47-51 and figure 3 in Qiao). Allowable Subject Matter Claims 7-9 are 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. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FITWI Y HAILEGIORGIS whose telephone number is (571)270-1881. The examiner can normally be reached M-F 10AM-6PM. 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, Chieh Fan can be reached at 571-272-3042. 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. FITWI Y. HAILEGIORGIS Primary Examiner Art Unit 2632 /FITWI Y HAILEGIORGIS/ Examiner, Art Unit 2632
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Prosecution Timeline

Jul 30, 2024
Application Filed
Apr 08, 2026
Non-Final Rejection mailed — §103 (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

1-2
Expected OA Rounds
91%
Grant Probability
74%
With Interview (-16.3%)
2y 0m (~3m remaining)
Median Time to Grant
Low
PTA Risk
Based on 483 resolved cases by this examiner. Grant probability derived from career allowance rate.

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