Prosecution Insights
Last updated: October 02, 2026
Application No. 18/846,116

METHOD FOR TRAINING AND DEPLOYING MODEL AND COMMUNICATION DEVICE

Non-Final OA §102
Filed
Sep 11, 2024
Priority
Mar 11, 2022 — nonprovisional of PCTCN2022080478
Examiner
CHOI, EUNSOOK
Art Unit
Tech Center
Assignee
Beijing Xiaomi Mobile Software Co., Ltd.
OA Round
1 (Non-Final)
90%
Grant Probability
Favorable
1-2
OA Rounds
5m
Est. Remaining
98%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allowance Rate
785 granted / 871 resolved
+30.1% vs TC avg
Moderate +8% lift
Without
With
+7.5%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
20 currently pending
Career history
884
Total Applications
across all art units

Statute-Specific Performance

§101
6.2%
-33.8% vs TC avg
§103
44.5%
+4.5% vs TC avg
§102
23.2%
-16.8% vs TC avg
§112
11.8%
-28.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 871 resolved cases

Office Action

§102
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 . Claim Rejections - 35 USC § 102 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. Claims 1, 5, 9, 17, 20 and 30 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Timo et al. (US 20240275519). Regarding claims 1, 17 and 30, Timo teaches obtaining capability information reported by a user equipment (UE), the capability information being configured to indicate at least one of an artificial intelligence (Al) supporting capability or a machine learning (ML) supporting capability ([0001] the network decoder and/or UE encoder use artificial intelligence (AI) and/or machine learning (ML) techniques) of the UE (Fig. 7, 710 and [0151] where the RAN node can receive, from each of the one or more UEs, an indication of UE DL channel feedback encoding capabilities); generating an encoder model and a decoder model based on the capability information; and sending model information of the encoder model to the UE, the model information of the encoder model being configured to deploy the encoder model (Fig. 7, 715 and [0150] the RAN node can send the one or more configurations to the one or more UEs. Each configuration includes the following: … an identifier of one of the UE encoders). Regarding claims 5 and 20, Timo teaches wherein the model information of the encoder model comprises at least one of following information: a first model information indicating a kind of the encoder model; or a second model information indicating a model parameter of the encoder model ([0150] the RAN node can send the one or more configurations to the one or more UEs. Each configuration includes the following: … an identifier of one of the UE encoders). Regarding claim 9, Timo teaches updating the encoder model and the decoder model to generate an updated encoder model and an updated decoder model ([0106]-[0109] The network can then deploy the trained decoder in the network to operate as needed with the UE encoder, which may be given a unique identifier that is known to both UE and network). 3. (Canceled) 8. (Canceled) 14. (Canceled) 16. (Canceled) 19. (Canceled) 23. (Canceled) 25. (Canceled) 27-29. (Canceled) Allowable Subject Matter Claims 2, 4, 6, 7, 10-13, 15, 18, 21, 22, 24, 26 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 EUNSOOK CHOI whose telephone number is (571)270-1822. The examiner can normally be reached on 8am-4:30pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hassan Phillips can be reached on 5712723940. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /EUNSOOK CHOI/Primary Examiner, Art Unit 2467
Read full office action

Prosecution Timeline

Sep 11, 2024
Application Filed
Aug 26, 2026
Non-Final Rejection mailed — §102 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

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Patent 12720354
USER EQUIPMENT MEASUREMENT GAP CONFIGURATION IN A WIRELESS COMMUNICATIONS SYSTEM (WCS)
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Patent 12713445
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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
90%
Grant Probability
98%
With Interview (+7.5%)
2y 6m (~5m remaining)
Median Time to Grant
Low
PTA Risk
Based on 871 resolved cases by this examiner. Grant probability derived from career allowance rate.

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