Prosecution Insights
Last updated: April 19, 2026
Application No. 18/906,370

INFORMATION EXCHANGE METHOD AND RELATED APPARATUS

Non-Final OA §103§112
Filed
Oct 04, 2024
Examiner
HOANG, HIEU T
Art Unit
2449
Tech Center
2400 — Computer Networks
Assignee
Huawei Technologies Co., Ltd.
OA Round
1 (Non-Final)
80%
Grant Probability
Favorable
1-2
OA Rounds
3y 1m
To Grant
97%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allow Rate
513 granted / 637 resolved
+22.5% vs TC avg
Strong +17% interview lift
Without
With
+16.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
15 currently pending
Career history
652
Total Applications
across all art units

Statute-Specific Performance

§101
9.2%
-30.8% vs TC avg
§103
44.8%
+4.8% vs TC avg
§102
18.5%
-21.5% vs TC avg
§112
16.1%
-23.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 637 resolved cases

Office Action

§103 §112
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 . 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 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. This office action is in response to the communication filed on 10/04/2024. Claims 1-20 are pending. Claim Objections Claims 13-16 are objected to because of the following informalities: “the apparatus” lacks antecedent basis and should refer back to “a first communication apparatus”. Claims 17-20 are objected to because of the following informalities: “the apparatus” lacks antecedent basis and should refer back to “a second communication apparatus”. Appropriate correction is required. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 17-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The claims recite “a second communication apparatus” but there is no recitation of “a first communication apparatus.” The claims are indefinite because it is not clear if there is one or two communication apparatuses. Claim Rejections - 35 USC § 103 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) 1-5, 7, 8, 11-15, 17-19 is/are rejected under AIA 35 U.S.C. 103 as being unpatentable over Henry et al. (US 2020/0260431) in view of Khastoo et al. (NeuRA: Using Neural Networks to Improve WiFi Rate Adaptation, 11/2020). As to claim 1, Henry discloses an information exchange method, comprising: sending, by a first communication apparatus, function request information, wherein the function request information is used to request to enable a function (fig. 3A, 3B, 7, [0019], [0036], a probe request from a client device to an access point AP for enabling a wireless feature); and receiving, by the first communication apparatus, function response information, wherein the function response information is used to respond to a request of the function request information (fig. 3A, 3B, 7, [0036], a probe response from the AP to the client device about the wireless feature requested in the probe request). Henry does not disclose the function is an artificial intelligence AI-assisted rate adaptation function or an AI-assisted rate adaptation joint channel access function. Khastoo discloses an artificial intelligence AI-assisted rate adaptation function or an AI-assisted rate adaptation joint channel access function by an access point (abstract, wireless access point neural networks for WiFi rate adaptation) It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to apply Khastoo’s AI-assisted rate adaptation function to Henry’s teachings of signaling between devices and access points including request and response for enabling a certain wireless function in order to enable or disable AI-assisted rate adaptation function for a particular device. As to claim 13, Henry discloses a first communication apparatus, wherein the apparatus comprises a processor and a transceiver (fig. 3A, 3B, 7, client device with a processor and a transceiver), and the processor is configured to control the transceiver to perform the following steps: sending function request information, wherein the function request information is used to request to enable a function (fig. 3A, 3B, 7, [0019], [0036], a probe request from a client device to an access point AP for enabling a wireless feature); and receiving function response information, wherein the function response information is used to respond to a request of the function request information (fig. 3A, 3B, 7, [0036], a probe response from the AP to the client device about the wireless feature requested in the probe request). Henry does not disclose the function is an artificial intelligence AI-assisted rate adaptation function or an AI-assisted rate adaptation joint channel access function. Khastoo discloses an artificial intelligence AI-assisted rate adaptation function or an AI-assisted rate adaptation joint channel access function by an access point (abstract, wireless access point neural networks for WiFi rate adaptation) It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to apply Khastoo’s AI-assisted rate adaptation function to Henry’s teachings of signaling between devices and access points including request and response for enabling a certain wireless function in order to enable or disable AI-assisted rate adaptation function for a particular device. As to claim 17, Henry discloses a second communication apparatus, wherein the apparatus comprises a processor and a transceiver (fig. 3A, 3B, 7, access point with a processor and a transceiver), and the processing unit is configured to control the transceiver unit to perform the following steps: receiving function request information, wherein the function request information is used to request to enable a function (fig. 3A, 3B, 7, [0019], [0036], a probe request from a client device to an access point AP for enabling a wireless feature); and sending function response information, wherein the function response information is used to respond to a request of the function request information (fig. 3A, 3B, 7, [0036], a probe response from the AP to the client device about the wireless feature requested in the probe request). Henry does not disclose the function is an artificial intelligence AI-assisted rate adaptation function or an AI-assisted rate adaptation joint channel access function. Khastoo discloses an artificial intelligence AI-assisted rate adaptation function or an AI-assisted rate adaptation joint channel access function by an access point (abstract, wireless access point neural networks for WiFi rate adaptation) It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to apply Khastoo’s AI-assisted rate adaptation function to Henry’s teachings of signaling between devices and access points including request and response for enabling a certain wireless function in order to enable or disable AI-assisted rate adaptation function for a particular device. As to claim 2, Henry-Khastoo discloses the function response information indicates that the request of the function request information is agreed (Henry, fig. 7, agree response); and after the receiving, by the first communication apparatus, function response information, the method further comprises: receiving, by the first communication apparatus, a first frame, wherein the first frame comprises first indication information, the first indication information indicates input information of a neural network, and the neural network corresponds to the function that is requested to be enabled by the function request information (Khastoo, 3.1, inputs to the model as throughputs, 3.3, Input features (rates)). As to claim 3, Henry-Khastoo discloses the input information of the neural network comprises one or more of the following: a carrier sense result, received power, a modulation and coding scheme MCS used for a data packet, a number of multiple input multiple output MIMO data streams, a channel bandwidth, a queuing delay, an access delay, channel access behavior, a data packet transmission result, or channel information, wherein the channel access behavior comprises access or non-access (Khastoo, table 2, channel bandwidth, section 3.3, feature selection to maximize power). As to claim 4, Henry-Khastoo discloses the input information of the neural network further comprises one or more of the following: a packet loss rate, a throughput, or duration from a current moment to time of previous successful transmission of the first communication apparatus (Khastoo, section 3.2, TR(N,w(t)) represents the expected throughput (in Mbps) from aggregating N packets when using rate R in time window w(t).). As to claim 5, Henry-Khastoo discloses the first frame further comprises second indication information, and the second indication information indicates a number of pieces of input information of the neural network (Khastoo, 3.3, feature selection, N input features). As to claim 7, Henry-Khastoo discloses the function response information indicates that the request of the function request information is agreed (Henry, fig. 7, agree response); and after the receiving, by the first communication apparatus, function response information, the method further comprises: receiving, by the first communication apparatus, a second frame, wherein the second frame comprises third indication information, the third indication information indicates at least one of an output layer structure of the neural network and a manner of selecting a decision result of the neural network, and the neural network corresponds to the function that is requested to be enabled by the function request information (Khastoo, 3.1, Each hidden layer contains 64 neurons and the output layer contains a neuron for each supported rate). As to claim 8, Henry-Khastoo discloses the output layer structure of the neural network comprises one or more of the following: a number of neurons or an activation function used by a neuron (Khastoo, 3.1, Each hidden layer contains 64 neurons and the output layer contains a neuron for each supported rate). As to claim 11, Henry-Khastoo discloses the function request information is carried in an information element, or the function request information is carried in an aggregated control subfield of a high throughput HT control field (Henry, fig. 3B, information fields of a probe request). As to claim 12, Henry-Khastoo discloses the function response information indicates that the request of the function request information is agreed (Henry, fig. 7, agree response); and the function response information further comprises fourth indication information, wherein the fourth indication information indicates a hidden layer structure of the neural network, and the neural network corresponds to the function that is requested to be enabled by the function request information (Khastoo, 3.1, Each hidden layer contains 64 neurons and the output layer contains a neuron for each supported rate). As to claims 14, 15, the claims are rejected for the same rationale in claims 2, 7 respectively. As to claim 18, 19, the claims are rejected for the same rationale in claims 2, 7 respectively. Claim(s) 6 is/are rejected under AIA 35 U.S.C. 103 as being unpatentable over Henry-Khastoo in view of Queiros et al. (Wi-Fi Rate Adaptation using a Simple Deep Reinforcement Learning Approach, 02/2022). As to claim 6, Henry-Khastoo does not disclose the first frame further comprises information indicating a dimension of the input information. Queiros discloses the first frame further comprises information indicating a dimension of the input information (Queiros, III-B, III-C, dimension of inputs). It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to apply Queiros’s AI-assisted rate adaptation function to Henry-Khastoo’s teachings in order to adopt a certain framework of AI-assisted rate adaptation such as dimension states and actions. Allowable Subject Matter and Reasons for Allowance Claims 9, 10, 16, 20 would be allowable if rewritten to include all of the limitations of the base claim and any intervening claims. The following is an examiner's statement of reasons for allowance: By interpreting the claims in light of the Specification, the Examiner finds the claimed invention to be patentably distinct from the prior art of records. Specifically, the prior art of records, individually or in combination, fail to explicitly teach, suggest or render obvious the claimed invention as recited, including receiving, by the first communication apparatus, a parameter of the neural network, wherein the parameter of the neural network comprises at least one of a bias and a weight that are of a neuron, and the neural network corresponds to the function that is requested to be enabled by the function request information. Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled "Comments on Statement of Reasons for Allowance." Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is included in form PTO 892. Any inquiry concerning this communication or earlier communications from the examiner should be directed to HIEU T HOANG whose telephone number is (571) 270-1253. The examiner can normally be reached Mon-Fri 9 AM -5 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, Vivek Srivastava can be reached on 571-272-7304. 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. /HIEU T HOANG/Primary Examiner, Art Unit 2449
Read full office action

Prosecution Timeline

Oct 04, 2024
Application Filed
Jun 03, 2025
Response after Non-Final Action
Feb 09, 2026
Non-Final Rejection — §103, §112 (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
80%
Grant Probability
97%
With Interview (+16.7%)
3y 1m
Median Time to Grant
Low
PTA Risk
Based on 637 resolved cases by this examiner. Grant probability derived from career allow rate.

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