Prosecution Insights
Last updated: April 18, 2026
Application No. 18/858,606

Neural Network Processing Management

Non-Final OA §102
Filed
Oct 21, 2024
Examiner
JEAN, FRANTZ B
Art Unit
2454
Tech Center
2400 — Computer Networks
Assignee
Apple Inc.
OA Round
1 (Non-Final)
90%
Grant Probability
Favorable
1-2
OA Rounds
2y 7m
To Grant
99%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allow Rate
753 granted / 837 resolved
+32.0% vs TC avg
Moderate +9% lift
Without
With
+8.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
17 currently pending
Career history
854
Total Applications
across all art units

Statute-Specific Performance

§101
12.4%
-27.6% vs TC avg
§103
25.5%
-14.5% vs TC avg
§102
33.2%
-6.8% vs TC avg
§112
10.0%
-30.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 837 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 . This is a first office action in response to the instant application for patent filed on 21 October 2024. Claims 1-20 are presented for examination. Information Disclosure Statement The information disclosure statement (IDS) submitted on 10/21/2024 was filed before the mailing date of the first office action on the merits. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. 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. Claim(s) 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Bao et al. hereinafter Bao PUB Number 20210185515A1. As per claim 1, Bao teaches a method, comprising: establishing a wireless link with a cellular base station (see par 0090, “each base station 105 may provide a coverage area 110 over which the UEs 115 and the base station 105 may establish one or more communication links 125”); determining neural network processing capability information for a wireless device (see paragraph 0082, “a UE and a base station may communicate capability information. For example, the UE may transmit capability information indicating neural network blocks supported by the UE. The base station may configure, based on the UE capability information, the base station capability information, or both, one or more neural network block parameters for the UE”); and providing the neural network processing capability information for the wireless device to the cellular base station (see para 0082, “a UE and a base station may communicate capability information. For example, the UE may transmit capability information indicating neural network blocks supported by the UE. The base station may configure, based on the UE capability information, the base station capability information, or both, one or more neural network block parameters for the UE. The base station may transmit the one or more neural network block parameters to the UE”). As per claim 2, Bao teaches the method of claim 1, wherein the neural network processing capability information includes an indication of a number of supported neural network processing units (NPUs) for the wireless device (see para 0082, “the UE may transmit capability information indicating neural network blocks supported by the UE; see fig 3 par 0068 “FIG. 3 illustrates an example of a neural network block that supports neural network configuration for wireless communication system assistance”; see also para 0137, “ UE 115-a may configure the supported neural network block using the neural network block parameters”). As per claim 3, Bao teaches the method of claim 1, wherein the neural network processing capability information includes an indication of a number of supported neural network processing units (NPUs) for the wireless device for each of one or more of: beam prediction in spatial domain; beam prediction in time domain; channel state information measurement and reporting; or positioning estimation (see par 0144, (CSI) channel state information compression block; par 0123, channel measurement and reporting). As per claim 4, Bao teaches the method of claim 1, wherein the neural network processing capability information includes availability information for neural network processing units (NPUs) for the wireless device (see par 0171, “, base station 105-b and UE 115-c may negotiate the availability of various neural network blocks for the UE 115-c, the base station 105-b, or both”). As per claim 5, Bao teaches the method of claim 4, wherein the availability information for NPUs for the wireless device includes one or more of: an indication that one or more NPUs for the wireless device are always available for neural network processing tasks associated with the wireless link; or an indication of one or more of a preferred on duration, a preferred off duration, or a preferred periodicity of availability for one or more NPUs for the wireless device (see par 0171, availability of various neural network blocks). As per claim 6, The method of claim 1, wherein the neural network processing capability information includes an indication of a number of layers and a number of nodes per layer with which the wireless device is capable of performing neural network processing for one or more neural network processing units (NPUs) for the wireless device (see par 0081, “ Neural network block parameters may include a number of layers, a number of nodes in each layer, a mapping between the respective nodes of each layer, an activation function for one or more of the nodes or submodules of the neural network block”; see also para 0231, 0270). As per claim 7, Bao teaches the method of claim 1, wherein the method further comprises: receiving information from the cellular base station configuring the wireless device to perform a neural network processing activity; determining a neural network processing unit occupancy duration for the neural network processing activity; and performing the configured neural network processing activity (see para 0080 which discusses functions and activities and 0197, timer). As per claim 8, Bao teaches the method of claim 7, wherein the neural network processing activity includes one or more of: beam prediction and reporting; channel state information measurement and reporting; or wireless device positioning estimation (see para 0097 for wireless positioning; see par 0144 in regard to CSI; par 0123, channel measurement and reporting). As per claim 9, Bao teaches the method of claim 7, wherein the method further comprises: determining that neural network processing activity greater than neural network processing capability for the wireless device is configured by the cellular base station; and determining one or more neural network processing activities to drop based at least in part on neural network processing activity configured by the cellular base station being greater than neural network processing capability for the wireless device (see para 0171, 0174 and 0178, wherein Bao discusses negotiation of the availability of various neural network blocks, activation and deactivation, and adjustment parameters for neural network block upon encountering issues and discrepancy between activities and capability of the neural network blocks). As per claim 10, Bao teaches the method of claim 9, wherein the one or more neural network processing activities to drop are determined based at least in part on priority indications for the one or more neural network processing activities, wherein neural network processing activities with lowest priority indications are dropped until a remaining number of neural network processing activities configured by the cellular base station is within the neural network processing capability for the wireless device (see para 0171, 0174 and 0178, wherein Bao discusses negotiation of the availability of various neural network blocks, activation and deactivation, and adjustment parameters for neural network block upon encountering issues and discrepancy between activities and capability of the neural network blocks). As per claim 11, Bao teaches the method of claim 10, wherein the priority indications for the one or more neural network processing activities are received by the wireless device via one or more of: radio resource control (RRC) signaling; media access control (MAC) control element (CE) signaling; or downlink control information (DCI) signaling (see par 0083, DCI, MAC, RRC, CE). As per claim 12, Bao teaches a method, comprising: establishing a wireless link with a wireless device (see par 0090, “each base station 105 may provide a coverage area 110 over which the UEs 115 and the base station 105 may establish one or more communication links 125”); receiving neural network processing capability information from the wireless device (see paragraph 0082, “a UE and a base station may communicate capability information. For example, the UE may transmit capability information indicating neural network blocks supported by the UE. The base station may configure, based on the UE capability information, the base station capability information, or both, one or more neural network block parameters for the UE”); and configuring one or more neural network processing activities for the wireless device, wherein the one or more neural network processing activities are configured based at least in part on the neural network processing capability information (see paragraph 0082, “a UE and a base station may communicate capability information. For example, the UE may transmit capability information indicating neural network blocks supported by the UE. The base station may configure, based on the UE capability information, the base station capability information, or both, one or more neural network block parameters for the UE”). As per claim 13, Bao teaches the method of claim 12, wherein the neural network processing capability information includes an indication of a number of supported neural network processing units (NPUs) for the wireless device, wherein configuring one or more neural network processing activities for the wireless device based at least in part on the neural network processing capability information includes limiting number and type of neural network processing activities configured for the wireless device to be within neural network processing capability for the wireless device (see para 0080 which discusses functions and activities). As per claim 14, Bao teaches the method of claim 13, wherein the method further comprises: determining neural network processing unit occupancy duration for the one or more neural network processing activities configured for the wireless device, wherein limiting number and type of neural network processing activities configured for the wireless device to be within neural network processing capability for the wireless device is further based at least in part on the determined neural network processing unit occupancy duration for the one or more neural network processing activities configured for the wireless device (see para 0197, a timer for the occupancy time duration). As per claim 15, Bao teaches the method of claim 12, wherein the neural network processing capability information includes availability information for neural network processing units (NPUs) for the wireless device, wherein the method further comprises: determining an availability pattern for NPUs for the wireless device based at least in part on the availability information for NPUs for the wireless device; and providing an indication of the availability pattern for NPUs for the wireless device to the wireless device (see par 0171, “, base station 105-b and UE 115-c may negotiate the availability of various neural network blocks for the UE 115-c, the base station 105-b, or both”). As per claim 16, Bao teaches the method of claim 12, wherein the neural network processing capability information includes an indication of a number of layers and a number of nodes per layer with which the wireless device is capable of performing neural network processing for one or more neural network processing units (NPUs) for the wireless device (see par 0081 “ Neural network block parameters may include a number of layers, a number of nodes in each layer, a mapping between the respective nodes of each layer, an activation function for one or more of the nodes or submodules of the neural network block”, see also para 0231, 0270). As per claim 17, Bao teaches the method of claim 12, wherein the method further comprises: providing priority information for the one or more neural network processing activities to the wireless device, wherein the priority information for the one or more neural network processing activities is provided via one or more of: radio resource control (RRC) signaling; media access control (MAC) control element (CE) signaling; or downlink control information (DCI) signaling (see par 0083, DCI, MAC, RRC, CE). As per claims 18-20, they are apparatus of the method claims 12-14. They contain the same limitations. Therefore, they are rejected under the same rationale. Furthermore, Bao teaches processor and memory (see fig 9, elements 930 and 940). Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANTZ B JEAN whose telephone number is (571)272-3937. The examiner can normally be reached 8-5 M-F. 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, Glenton B. Burgess can be reached at 5712723949. 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. /FRANTZ B JEAN/Primary Examiner, Art Unit 2454
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Prosecution Timeline

Oct 21, 2024
Application Filed
Mar 19, 2026
Non-Final Rejection — §102 (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
90%
Grant Probability
99%
With Interview (+8.6%)
2y 7m
Median Time to Grant
Low
PTA Risk
Based on 837 resolved cases by this examiner. Grant probability derived from career allow rate.

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