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 .
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.1 14, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.1 14. Applicant's submission filed on 5/26/2026 has been entered.
Claims 1-34 are presented for further examination.
DETAILED ACTION
Response to Arguments
Applicant's arguments filed 5/26/2026 have been fully considered but they are not persuasive.
Applicant states that the references fail to disclose the amended limitations.
Examiner respectfully disagrees.
Campbell (US 10,778,755) in view of Samadi (US 2021/0344582) specifically Cambell discloses the following:
In Claim 1: Campbell discloses ….simulating network feedback representing expected feedback from a second system (“the gather data under performance test with respect to the target nodes, to what performance may be expected/predicted accuracy for the UE devices/particular node/second system remotely from the first system at the geolocation”, refer to Col 17, Lines 1-3, Col 2, Lines 43-61, Col 14, Lines 1-15, Col 16, Lines 5-15, Lines 65- Col 17, Lines 10, Lines 42-50, Col 17, Lines 60- Col 18, Lines 5 and Col 21, Lines 4) for at least one communication channel (refer to Fig 4, and Col 8, Lines 30-65 and Col 14, Lines 30- Col 15, Lines 10, Col 16, Lines 40-65 and Col 17, Lines 1-16), wherein the simulated network feedback includes at least one simulated network parameter (gathered data/performance , refer to Col 17, Lines 1-5), … wherein the second system communicates with a first system via at least one network, wherein the at least one value is synthetically generated (refer to Col 17, Lines 42- Col 18, Lines 20, Col 15, Lines 32-35 particular node is determined to be supporting a particular amount of network traffic); wherein each decision-making process is configured to determine decisions for the first system based on network feedback data (refer to Col 21, Lines 45- Col 22, Lines 5, Col 25, Lines 1-20).
In Claim 4: Campbell discloses ….wherein the first set of network feedback is generated locally to the first system, wherein the second set of network feedback is generated by the second system remotely from the first system (the feedback is generated by the UE device and another from the outside system/node, refer to Col 18, Lines 1-60: round way trip, and one way trip for measuring delays for either sending or receiving timestamps at the communication systems/devices and Col 19 ,Lines 1-18, Col 22, Lines 15-31).
In Claim 34: Campbell discloses applying at least one generative artificial intelligence model in order to generate a set of simulation results, wherein the simulation network feedback is based on the generated set of simulation results (performance be process with machine learning/other technologies, refer to col 21, Lines 10-20, and process within each node/device, refer to Col 19, 60-67 and Col 21, Lines 65-67, Col 25, Lines 1-20).
Therefore, arguments are not persuasive and the rejection is therefore maintained.
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) 1-34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Campbell et al hereinafter Campbell (US 10,778,755) in view of Samadi (US 2021/0344582).
Referring to Claim 1. Campbell discloses a method for network feedback simulation injection (to conduct performance test, refer to abstract), comprising: simulating network feedback representing expected feedback from a second system (“the gather data under performance test with respect to the target nodes, to what performance may be expected/predicted accuracy for the UE devices/particular node/second system remotely from the first system at the geolocation”, refer to Col 17, Lines 1-3, Col 2, Lines 43-61, Col 14, Lines 1-15, Col 16, Lines 5-15, Lines 65- Col 17, Lines 10, Lines 42-50, Col 17, Lines 60- Col 18, Lines 5 and Col 21, Lines 4) for at least one communication channel (refer to Fig 4, and Col 8, Lines 30-65 and Col 14, Lines 30- Col 15, Lines 10, Col 16, Lines 40-65 and Col 17, Lines 1-16), wherein the simulated network feedback includes at least one simulated network parameter (gathered data/performance , refer to Col 17, Lines 1-5), each simulated network parameter indicating at least one value of a corresponding network performance metric (refer to Col 6 Lines 20-25, Col 10, Lines 40-55, Col 25, Lines 1-5, Col 17, Lines 40-50) wherein the second system communicates with a first system via at least one network, wherein the at least one value is synthetically generated (refer to Col 17, Lines 42- Col 18, Lines 20, Col 15, Lines 32-35 particular node is determined to be supporting a particular amount of network traffic); and injecting the simulated network feedback into at least one decision-making process, wherein each decision-making process is configured to determine decisions for the first system based on network feedback data (refer to Col 21, Lines 45- Col 22, Lines 5, Col 25, Lines 1-20).
Samadi, in analogous art, is introduce to further expedite the prosecution by demonstrate it is well known in the art to simulate network feedback and provide the feedback into decision-making process (refer to par 0138, 0151)
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Cambell with Samadi because Samadi’s teaching would allow the system of Cambell to improve system performance without delay.
Referring to Claim 2. Cambell with Samadi disclosed the method of claim 1, Campbell discloses wherein each decision-making process is configured to determine decisions for the first system based on the network feedback data, wherein the simulated network feedback is based on a simulation of network performance for network communications between the first system and the second system (refer to Col 16, Lines 40- Col 17, Lines 15).
Referring to Claim 3. Cambell with Samadi disclosed the method of claim 2, Campbell discloses detecting a simulation trigger including transmission of data from the first system to the second system, wherein the simulation is initiated when the simulation trigger is detected (refer to Col 3, Lines 3-5, Col 14, Lines 24-31).
Referring to Claim 4. Cambell with Samadi disclosed the method of claim 2, Campbell discloses wherein the simulated network feedback is a first set of network feedback, wherein the first system receives a second set of network feedback from the second system, wherein the first set of network feedback is utilized by the at least one decision-making process until the second set of network feedback is received by the first system (refer to Col 16, Lines 40- Col 17, Lines 15, Col 26, Lines 15-25) wherein the first set of network feedback is generated locally to the first system, wherein the second set of network feedback is generated by the second system remotely from the first system (the feedback is generated by the UE device and another from the outside system/node, refer to Col 18, Lines 1-60: round way trip, and one way trip for measuring delays for either sending or receiving timestamps at the communication systems/devices and Col 19 ,Lines 1-18, Col 22, Lines 15-31).
Referring to Claim 5. Cambell with Samadi disclosed the method of claim 4, Campbell discloses injecting the second set of network feedback into the at least one decision-making process (refer to Col 21, Lines 10-15).
Referring to Claim 6. Cambell with Samadi disclosed the method of claim 1, further comprising: Campbell discloses detecting a simulation trigger based on passage of a predetermined amount of time since a most recent receipt of network feedback, wherein the simulation is initiated when the simulation trigger is detected (refer to Col 13, Lines 60-67).
Referring to Claim 7. Cambell with Samadi disclosed the method of claim 1, Campbell discloses wherein the simulated network feedback further includes simulated content of the simulated network feedback (refer to Col 8, Lines 10-31, Col 7, Lines 20-28, Col 14, Lines 5-10).
Referring to Claim 8. Cambell with Samadi disclosed the method of claim 1, Campbell discloses wherein the simulated network feedback further includes a simulated timing for the simulated network feedback (refer to Col 6, Lines 1--12).
Referring to Claim 9. Cambell with Samadi disclosed the method of claim 1, Campbell discloses wherein the at least one simulated network parameter is at least a portion of at least one network feedback aspect to be simulated, further comprising: determining the at least one network feedback aspect to be simulated based on historical network feedback (also based on historical data, refer to Col 8, Lines 10-31, Col 14, Lines 5-10), wherein the at least one simulated network parameter is at least one type of network parameter which is represented in the historical network feedback (refer to Col 8, Lines 20-31).
Referring to Claim 10. Cambell with Samadi disclosed the method of claim 9, further comprising: Campbell discloses determining the at least one network feedback aspect to be simulated based further on a decision-making process type for each of the at least one decision-making process (refer to Col 10, Lines 10-15, 40-61 and refer to Col 21, Lines 45- Col 22, Lines 5, Col 25, Lines 1-20).
Referring to Claim 11. | Cambell with Samadi disclosed the method of claim 9, further comprising: Campbell discloses establishing at least one simulation parameter based on the determined at least one network feedback aspect to be simulated, wherein establishing the at least one simulation parameter further comprises applying a simulation establishment machine learning model to features extracted from data transmitted by a system (refer to Col 21, Lines 45- Col 22, Lines 5, Col 25, Lines 1-20).
Referring to Claim 12. Cambell with Samadi disclosed the method of claim 11, Campbell discloses wherein simulating the network feedback further comprises:
applying at least one simulator machine learning model to the established at least one simulation parameter, wherein the simulated network feedback is based further on outputs of the at least one simulator machine learning model (refer to Col 21, Lines 15-30, Col 25, Lines 1-20).
Referring to Claim 13. | Cambell with Samadi disclosed the method of claim 1, Campbell discloses wherein the at least one communication channel is a plurality of communication channels, wherein simulating the network feedback further comprises:
running a simulation for each of the plurality of communication channels, wherein the simulated network feedback is based on simulation results for the simulation of each of the plurality of communication channels (refer to Col 8, Lines 45-60).
Referring to Claim 14. Cambell with Samadi disclosed the method of claim 1, Campbell discloses wherein the at least one simulated network parameter includes at least one of latency, jitter, and packet loss (refer Fig 8 and Col 2, Lines 45-55, Col 3, Lines 4-11which the performance metric includes the latency, and performance related data, Col 5, Lines 60-67).
Referring to Claim 15. | Cambell with Samadi disclosed the method of claim 1, Campbell discloses determining, using the at least one decision-making process, the decisions for a system based on the simulated network feedback (refer to Fig 9, steps 904 and 909); and controlling the system based on the determined decisions (refer to Col 4, Lines 40-50).
Referring to Claim 16. Cambell with Samadi disclosed the method of claim 15, Campbell discloses wherein the system is a vehicle, wherein the determined decisions include driving decisions for the vehicle, wherein controlling the system further comprises driving the vehicle based on the driving decisions (refer to Col 14, Lines 20-45, and Col 4 Lines 40-50).
Referring to Claims 17-33, claims are rejected under similar rational as claims 1-16.
Referring to Claim 34. Cambell with Samadi disclosed the method of claim 15, Campbell discloses applying at least one generative artificial intelligence model in order to generate a set of simulation results, wherein the simulation network feedback is based on the generated set of simulation results (performance be process with machine learning/other technologies, refer to col 21, Lines 10-20, and process within each node/device, refer to Col 19, 60-67 and Col 21, Lines 65-67, Col 25, Lines 1-20).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KAREN C TANG whose telephone number is (571)272-3116. The examiner can normally be reached 5:30am - 2pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Joon H Hwang can be reached at (571) 272-4036. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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KAREN C. TANG
Primary Examiner
Art Unit 2447
/KAREN C TANG/Primary Examiner, Art Unit 2447
Prosecution Insights