Prosecution Insights
Last updated: October 16, 2026
Application No. 18/989,036

EARLY PREDICTED MEASUREMENTS AND REPORTING

Non-Final OA §102§103
Filed
Dec 20, 2024
Examiner
RANDHAWA, MANDISH K
Art Unit
2477
Tech Center
2400 — Computer Networks
Assignee
InterDigital Inc.
OA Round
1 (Non-Final)
65%
Grant Probability
Favorable
1-2
OA Rounds
1y 9m
Est. Remaining
92%
With Interview

Examiner Intelligence

Grants 65% — above average
65%
Career Allowance Rate
368 granted / 563 resolved
+7.4% vs TC avg
Strong +27% interview lift
Without
With
+27.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
34 currently pending
Career history
616
Total Applications
across all art units

Statute-Specific Performance

§101
3.2%
-36.8% vs TC avg
§103
61.8%
+21.8% vs TC avg
§102
18.5%
-21.5% vs TC avg
§112
10.3%
-29.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 563 resolved cases

Office Action

§102 §103
DETAILED ACTION Notice of Pre-AIA or AIA Status 1. 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 2. 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. 3. 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 – (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. 4. Claims 1, 3-8, 10, 11, 13-18 and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kim (US 2026/0239041 A1) Regarding claims 1 and 11, Kim teaches a wireless transmit/receive unit (WTRU) comprising: a transceiver: and a processor (fig. 14) configured to: send, via the transceiver, an indication of a measurement prediction capability (figs. 1, 2, 3, ¶ [0086], ¶ [0087], ¶ [0129], ¶ [0247], When the network requests UE to report UE capability information by sending UE CapabilityEnquiry message, the UE can send UEcapabilityInformation message including the capability of AI/ML functionality support.¶ [ [0543], ¶ [0544]); receive, via the transceiver, a message comprising: instructions for the WTRU to enter an idle state or an inactive state (figs. 2-4, ¶ [0247], UEs in RRC IDLE state and RRC INACTIVE state can report the results corresponding to the configured request (e.g. AI/ML configuration) which was configured in RRC CONNECTED state by RRCRelease message including mode change indication from RRC CONNECTED to RRC IDLE/RRC INACTIVE state or by RRCReconfiguration message. ¶ [0260]); configuration information associated with measurements to be performed while the WTRU is in the idle state or the inactive state (¶ [0792], The MeasConfig, ReportConfigNR, MeasResults, CSI-MeasConfig, CSIReportConfig, and MeasurementReport are the configuration information for measurement. ¶ [0793], The measObjectID can be used to indicate each measObject. When the network configures AI/ML configuration to UE (or the network entity), the measObject in MeasConfigAIML can indicate the AI/ML model (e.g. can be used for AI/ML model identifier to configure AI/ML configuration for multiple AI/ML models) or the same information for measurement. ¶ [0795], The ReportConfigNR includes the detailed information for reporting (e.g. which type of results should be reported or periodicity or time/frequency resources or when to trigger a reporting, i.e. events, etc). When the network configures AI/ML configuration to UE (or the network entity), the ReportConfigNRAIML includes the detailed information for reporting (e.g. which type of results should be reported or periodicity or time/frequency resources or when to trigger a reporting, i.e. events, etc). The ReportConfigIDAIML can be used to indicate each ReportConfigNRAIML ¶ [0176], ¶ [0248], ¶ [0261], ¶ [0263], ¶ [0271], ¶ [0285], ¶ [0288], ¶ [0416] Performs idle/inactive measurements for idle/inactive measurement configured UEs. ¶ [0788]). configuration information associated with measurements to be predicted while the WTRU is in the idle state or the inactive state (figs. 2, 3, ¶ [0248], Step 1-2: NG-RAN node 1 configures AI/ML configuration to UE (e.g. the measurement information on the UE side) and sends configuration message (e.g RRCReconfiguation, RRCSetup, or RRCResume or RRCRelease message or newly defined message) to UE to perform AI/ML functionality (e.g. measurement procedure and reporting). ¶ [0260]-¶ [0265]. ¶ [0417] Performs AI/ML functionality (e.g. collection of AI/ML data or measurements for AI/ML data or reporting AI/ML data) configured UEs. ¶ [0792], ¶ [0793], When the network configures AI/ML configuration to UE (or the network entity), the measObject in MeasConfigAIML can indicate the AI/ML model .¶ [0795]); enter the idle state or the inactive state (figs. 2-4, ¶ [0247], ¶ [788], ¶ [0789]); while in the idle state or the inactive state, perform measurements based on the received configuration information ( figs. 2, 3, ¶ [0247], ¶ [0248], ¶ [0788] NOTE: If timer T331 is running, the UE continues to perform idle/inactive measurements according to 5.7.8. ¶ [0789] NOTE: If timer Txxx (configured timer for AI/ML operation) is running, the UE continues to perform AI/ML operation (e.g. collection of AI/ML data or perform measurement) according to AI/ML configuration. ¶ [0416] Performs idle/inactive measurements for idle/inactive measurement configured UEs. ¶ [0788], ¶ [0795]); while in the idle state or the inactive state, based on a trigger condition, predict measurements based on the received configuration information and the performed measurements (¶ [0260]-¶ [0263], ¶ [0264], The network can configure a timer (e.g. T3xx) to UE by RRC message (e.g. RRCReconfiguration or RRCRelease message). When the timer is configured, UE can start the timer and can collect AI/ML data (or perform measurement) while the timer is running. After the expiry of the timer, UE can stop it. An area information can be configured to make UE collect AI/ML data (i.e. perform measurement) within the configured area ¶ [0265], ¶ [0795], When the network configures AI/ML configuration to UE (or the network entity), the ReportConfigNRAIML includes the detailed information for reporting (e.g. which type of results should be reported or periodicity or time/frequency resources or when to trigger a reporting, i.e. events, etc). The ReportConfigIDAIML can be used to indicate each ReportConfigNRAIML. ¶ [0321] Scenario 1. AI/ML Model Training and AI/ML Model Inference are both located in the UE); transition to a connected state (figs. 2, 3, ¶ [0247], In another embodiment, when UE performs AI/ML data reporting, UE in RRC IDLE or RRC INACTIVE state can send the results (or indication of availability of the results) after setting up RRC connection with the network (going to RRC CONNECTED state) by RRC message (e.g. RRCSetupComplete or RRCResumeComplete) in RRC CONNECTED state ); and send, via the transceiver, at least one of an indication of the performed measurements or an indication of the predicted measurements ( ¶ [0247], ¶ [0265]-¶ [0267], ¶ [0268], ¶ [0795], The ReportConfigNR includes the detailed information for reporting (e.g. which type of results should be reported or periodicity or time/frequency resources or when to trigger a reporting, i.e. events, etc). The ReportConfigID can be used to indicate each ReportConfigNR. When the network configures AI/ML configuration to UE (or the network entity), the ReportConfigNRAIML includes the detailed information for reporting ) Regarding claims 3 and 13, Kim teaches the WTRU of claim 1, wherein the measurement prediction capability is sent in a radio resource control (RRC) message (¶ [0544] the UE performs a UE capability report procedure, the RRC message (e.g., non-access stratum (NAS) message or access stratum (AS) message) for reporting UE capability may include some or multiple pieces of information for AI/ML functionality). Regarding claims 4 and 14, Kim teaches the WTRU of claim 1, wherein the message comprises a radio resource control release (RRCRelease) message (figs. 2, 3, ¶ [0247], (e.g. AI/ML configuration) which was configured in RRC CONNECTED state by RRCRelease message including mode change indication from RRC CONNECTED to RRC IDLE/RRC INACTIVE state or by RRCReconfiguration message). Regarding claims 5 and 15, Kim teaches the WTRU of claim 1, wherein the configuration information comprises at least one of a carrier associated with measurement performance, a frequency associated with measurement performance, a measurement duration, a measurement validity duration, or a validity area (figs. 1-3, ¶ [0248], The NG-RAN node 1 can also configures the UE to provide AI/ML data (e.g. measurements and/or location information, RRM measurements, MDT measurements, velocity, position, time information for measurement, measurement duration, sequence number for reordering training data, or CSI (e.g. aperiodic CSI or periodic CSI) or measurement results for frequency (or cell identity or beam or SSB)), ¶ [0416], ¶ [0788]. ¶ [0792], The MeasConfig, ReportConfigNR, MeasResults, CSI-MeasConfig, CSIReportConfig, and MeasurementReport are the configuration information for measurement. ¶ [0793], The measObject in MeasConfig includes the detailed information (e.g. time/frequency radio resource) for the target frequency. ¶ [0794]. ¶ [0800]-¶ [0804]). Regarding claims 6 and 16, Kim teaches the WTRU of claim 1, wherein the configuration information comprises at least one of a carrier associated with measurement prediction, a frequency associated with measurement prediction, a prediction duration, a prediction validity duration, or a prediction model (figs. 1-3, ¶ [0248], The NG-RAN node 1 can also configures the UE to provide AI/ML data (e.g. measurements and/or location information, RRM measurements, MDT measurements, velocity, position, time information for measurement, measurement duration, sequence number for reordering training data, or CSI (e.g. aperiodic CSI or periodic CSI) or measurement results for frequency (or cell identity or beam or SSB)). ¶ [0164], ¶ [0249], ¶ [0250]). Regarding claims 7 and 17, Kim teaches the WTRU of claim 1, wherein the trigger condition comprises an expiration of a validity duration ( ¶ [0270] Step 2: the UE collects AI/ML data upon the expiry of timer, ¶ [0149] AI/ML configuration including measurement configuration (e.g. intra-frequency, inter-frequency and inter-RAT measurements, time information (measurement duration or timing for measurement). ¶ [0248], The NG-RAN node 1 can also configures the UE to provide AI/ML data (e.g. measurements and/or location information, RRM measurements, MDT measurements, velocity, position, time information for measurement, measurement duration, ¶ [0263], UE can start or stop to collect AI/ML data met the conditions configured by the network) Regarding claims 8 and 18, Kim teaches the WTRU of claim 1, wherein the trigger condition comprises a location of the WTRU being within a threshold distance from a reference location (¶ [0248], The NG-RAN node 1 can also configures the UE to provide AI/ML data (e.g. measurements and/or location information, RRM measurements, MDT measurements, velocity, position, time information for measurement, measurement duration). ¶ [0828], eventD1-r17 distanceThreshFromReference1-r17 INTEGER distanceThreshFromReference2-117 INTEGER, referenceLocation1-r17 ReferenceLocation-r17, referenceLocation2-r17 ReferenceLocation-r17. DistanceThreshFromReference2 Distance from a reference location configured with referenceLocation1 or referenceLocation2.). Regarding claim 10 and 20, Kim teaches the WTRU of claim 1, wherein the transition to the connected state is based upon at least one of receipt of a paging message comprising an indication of downlink (DL) data, detection of uplink (UL) data, receipt of a radio resource control (RRC) setup request message, or receipt of an RRC resume request message (figs. 2-4, ¶ [0247], ¶ [0646], UE goes to RRC CONNECTED state upon the reception of RRCResume (or RRCReconfiguration). ¶ [0676]. ¶ [0123]). Claim Rejections - 35 USC § 103 5. 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. 6. 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. 7. 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. 8. Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable Kim in view of Lee et al. (WO 2025/234628 A1, hereinafter “Lee”) Regarding claims 2 and 12, Kim teaches the WTRU of claim 1. Kim does not explicitly teach wherein the measurement prediction capability comprises at least one of a frequency associated with the measurement prediction, a cell associated with the measure prediction, a time associated with the measurement prediction, a location associated with the measurement prediction, or a confidence level associated with the measurement prediction. Lee teaches wherein the measurement prediction capability comprises at least one of a frequency associated with the measurement prediction, a cell associated with the measure prediction, a time associated with the measurement prediction, a location associated with the measurement prediction, or a confidence level associated with the measurement prediction (page 10, a new terminal capability information variable (e.g., dataInactivityPredictionReport-rxx) indicating whether the terminal can predict a data inactivity interval and report the predicted data inactivity interval to the base station (105) in one of the methods of FIG. 1d may be defined in the UECapabilityInformation message. In addition, variables indicating information such as the maximum time interval length during which the terminal (100) can perform data inactivity interval prediction (in other words, a time value indicating how far in the future the prediction can be made from the current time point), the maximum number of inactivity intervals that can be predicted, etc. may be defined together. ) Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to include, in the measurement prediction capability message, at least one of a frequency associated with the measurement prediction, a cell associated with the measure prediction, a time associated with the measurement prediction, a location associated with the measurement prediction, or a confidence level associated with the measurement prediction in the system of Kim to further improve industrial applicability. 9. Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable Kim in view of Soldati et al. (WO 2024/179933 A1, hereinafter “Soldati”) Regarding claim 9, Kim teaches the WTRU of claim 1, wherein the trigger condition comprises a time measured at the WTRU and/or a time window (¶ [0346], ¶ 0149] AI/ML configuration including measurement configuration (e.g. intra-frequency, inter-frequency and inter-RAT measurements, time information (measurement duration or timing for measurement). Kim does not explicitly teach wherein the trigger condition comprises an absolute time measured at the WTRU being within a time window. It is well known in the art that a trigger condition comprises an absolute time measured within a time window, evidenced by Soldati (figs. 3, 4, Page 6: for each prediction of the one or more predictions requested or configured by the first message, the reference prediction time indicates both: (a) an offset time or an absolute time in the future and (b) a time interval to which the prediction refers). Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the invention, to use an absolute time measured at the WTRU being within a time window as the trigger condition/timing for measurement in the system of Kim. The motivation for doing this is a matter of design choice. Conclusion 10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANDISH RANDHAWA whose telephone number is (571)270-5650. The examiner can normally be reached Monday-Thursday (9 AM-7 PM). 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 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. /MANDISH K RANDHAWA/Primary Examiner, Art Unit 2477
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Prosecution Timeline

Dec 20, 2024
Application Filed
Oct 02, 2026
Non-Final Rejection mailed — §102, §103 (current)

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Prosecution Projections

1-2
Expected OA Rounds
65%
Grant Probability
92%
With Interview (+27.1%)
3y 7m (~1y 9m remaining)
Median Time to Grant
Low
PTA Risk
Based on 563 resolved cases by this examiner. Grant probability derived from career allowance rate.

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