Prosecution Insights
Last updated: April 19, 2026
Application No. 18/698,474

DATA-DRIVEN WTRU-SPECIFIC MIMO PRE-CODER CODEBOOK DESIGN

Non-Final OA §102§103
Filed
Apr 04, 2024
Examiner
BHATTI, HASHIM S
Art Unit
2475
Tech Center
2400 — Computer Networks
Assignee
InterDigital Patent Holdings, Inc.
OA Round
1 (Non-Final)
86%
Grant Probability
Favorable
1-2
OA Rounds
2y 4m
To Grant
92%
With Interview

Examiner Intelligence

Grants 86% — above average
86%
Career Allow Rate
340 granted / 396 resolved
+27.9% vs TC avg
Moderate +6% lift
Without
With
+6.3%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
27 currently pending
Career history
423
Total Applications
across all art units

Statute-Specific Performance

§101
3.7%
-36.3% vs TC avg
§103
46.2%
+6.2% vs TC avg
§102
28.0%
-12.0% vs TC avg
§112
18.1%
-21.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 396 resolved cases

Office Action

§102 §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 . Claim Rejections - 35 USC § 102 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 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. Claim(s) 15, 17, 22, 23, 25, 29 and 30 are rejected under 35 U.S.C. 102a2 as being anticipated by Chavva et al. US 2021/0351885 A1. Claims 15 and 23: Chavva discloses a wireless transmit/receive unit (WTRU) comprising, a processor configured to (See fig. 6A, UE comprising processor 602): determine precoder space selection information, wherein the precoder space selection information comprises WTRU-specific precoder action space information (See fig. 8 step 801, the method includes receiving a feedback configuration, by the UE 601, from the gNB 607. The feedback configuration is relevant to reception of CSI-RS and/or SSB. The feedback configuration can be used by the UE 601 to send the CSI as a feedback report. The UE 601 can receive the feedback configuration in a RRC message. The RRC message includes CSI-MeasConfig, CSI-ResourceConfig, CSI-ReportConfig, and CodebookConfig", wherein the claimed "precoder space selection information" may be directly corresponded to the parameter "CodebookConfig", paragraph [149], and wherein the claimed "WTRU-specific precoder action space information" may be directly corresponded to any one of the remaining parameters, paragraph [149] (see, for example, the parameter "CSI-ReportConfig") disclosed in combination with the use of the "Neural Network 602c" for the prediction and reporting of CSI - see paras [116] and [124]) receive a first channel state information reference signal (CSI-RS) from a base station (See fig. 8 step 802, receive CSI-RS. Also see paras, 149-155); select a first precoder from the WTRU-specific precoder action space information (See fig. 8 step 803, the claimed "select first precoder" directly corresponds to the determination/prediction of PMI (i.e. Precoder Matrix Indicator), wherein PMI is disclosed as one of the determined/predicted/reported "feedback parameters", which is predicted by the Neural Network 602c according to the embodiments of figures 9-12 - see the output "PMI" of the neural network processing units depicted in figures 9-10 and 12. Also see paras, 149-155); determine a first reward value for the first precoder using a precoder prediction model, wherein the first reward value is associated with the first CSI-RS (See fig. 8 step 804, wherein the claimed "precoder prediction model" directly corresponds to any of the neural network models, figures 9-10 and 12, used for determining and predicting "feedback parameters", said feedback parameters comprising PMI/optimal beam - see, for example, also paragraph [142]: "The neural network 602c can predict the RSRP of all beams of the UE 601. The prediction allows the UE 601 to select optimal beams for transmitting and receiving data, as the optimality of a beam can be determined based on the RSRP associated with the beam. The neural network 602c can predict the optimal beam at a current time instance and beam(s) which are likely to be optimal at future time instances". The claimed "first reward value" may be corresponded, for example, to the predicted "RSRP" value for "all beams of the UE". See also the embodiment of figure 16 and paragraphs [187]-[189]:"At time instance 't+T', neural network 602c predicts that the RSRP associated with all the beams of the UE 601 and determines that the RSRP associated with a beam B_pred_1 is the highest. The beam B_pred_1 is having the highest RSRP amongst all the beams of the UE 601 at time instance 't+T"); determine whether a condition is satisfied based on the first reward value; and based on the determination of whether the condition is satisfied based on the first reward value, send an indication to the base station, wherein the indication indicates precoder information and reward value information (See fig. 8 steps 805-806, the claimed "send first indication to the base station" directly corresponds to a CSI report including predicted vales of "feedback parameters", said "feedback parameters" comprising the predicted PMI/optimal beam, as well as the corresponding RSRP value (see figures 9B and 12, wherein the RSRP is directly disclosed to be one of the output "feedback parameters" of the neural network). The claimed "determine if a condition is satisfied on the first reward value" is disclosed in D1 in respect of the selection of particular predicted PMI/optimal beam based on its corresponding RSRP value (see paragraph [188]: "determines that the RSRP associated with a beam B_pred_1 is the highest"). It is understood in said selection, that other/remaining PMI/beams are not selected and are not reported/indicated based on their RSRP not being the highest)). Claims 17 and 25: Chavva discloses that the precoder prediction model is a machine learning model (See para 81, “the at least one parameter is computed and/or predicted using at least one Machine Learning (ML) based learning model”). Claims 21 and 29: Chavva discloses based on a determination that the condition is satisfied based on the first reward value, the precoder information indicates the first precoder, the reward value information indicates the first reward value, and the indication further indicates that the condition is satisfied (See fig. 8 steps 805-806, the claimed "send first indication to the base station" directly corresponds to a CSI report including predicted vales of "feedback parameters", said "feedback parameters" comprising the predicted PMI/optimal beam, as well as the corresponding RSRP value (see figures 9B and 12, wherein the RSRP is directly disclosed to be one of the output "feedback parameters" of the neural network). The claimed "determine if a condition is satisfied on the first reward value" is disclosed in D1 in respect of the selection of particular predicted PMI/optimal beam based on its corresponding RSRP value (see paragraph [188]: "determines that the RSRP associated with a beam B_pred_1 is the highest"). It is understood in said selection, that other/remaining PMI/beams are not selected and are not reported/indicated based on their RSRP not being the highest)). Claims 22 and 30: Chavva discloses receive a second CSI-RS from the base station; determine a predicted precoder using the second CSI-RS and the precoder prediction model; and generate a codebook based on the first precoder and the predicted precoder (See fig. 2, receiving second CSI-RS and sending CSI report including PMI and RI in the codebook. Also see para 124, sending PMI and RI according to the Codebook config.). 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) 18 and 26 are rejected under 35 U.S.C. 103 as being unpatentable over Chavva et al. in view of Chen et al. US 20220210676 A1. Claims 18 and 26: Chavva doesn’t discloses that the processor is further configured to: send a sounding reference signal (SRS) to the base station, wherein the SRS is associated with establishing the WTRU-specific precoder action space information with the base station. Chen discloses that the processor is further configured to: send a sounding reference signal (SRS) to the base station, wherein the SRS is associated with establishing the WTRU-specific precoder action space information with the base station (See para 53, “the UE should be configured with an association between the SRS resource set to be used to transmit SRS(s) precoded using the precoder matrix U (e.g., SRS(s) for reporting analog CSF) and the set of downlink CSI-RSs to be used to determine the precoder matrix U. With this configuration, the UE can determine the precoder matrix U from the associated set of downlink CSI-RSs and can use the precoder matrix U to precode the SRS(s) transmitted on the SRS resource set, and the base station can properly derive the PMI from the precoded SRS(s)”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Chavva with the teachings of Chen to improve the method disclosed by Chavva by including the feature of sending SRS is associated with precoder. The motivation to combine would have been to enable base station can properly derive the PMI from the precoded SRS(s). Allowable Subject Matter Claims 16, 19, 20, 21, 24, 27 & 28 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 HASHIM S BHATTI whose telephone number is (571)270-7748. The examiner can normally be reached Mon-Fri 9:00am-5:30pm. 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, Khaled Kassim can be reached at 571-270-3770. 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. HASHIM S. BHATTI Primary Examiner Art Unit 2472 /HASHIM S BHATTI/Primary Examiner, Art Unit 2475
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Prosecution Timeline

Apr 04, 2024
Application Filed
Feb 27, 2026
Non-Final Rejection — §102, §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
86%
Grant Probability
92%
With Interview (+6.3%)
2y 4m
Median Time to Grant
Low
PTA Risk
Based on 396 resolved cases by this examiner. Grant probability derived from career allow rate.

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