DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is response to communication: response to original application filed on 03/27/2025.
Claims 1-5 are currently pending in this application.
The IDS filed on 07/18/2025 has been accepted.
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.
Claim 1 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Claim elements “one device … and communicates over the network,” “channel selection controller … which provides data,” “software module… performing an action,” “rule network module … inputting a medium status,” “destination network module avoids the blocking,” “optimization module which allows the weights,” “data storage unit which is an experience memory unit,” “reward calculation module which calculates,” and “status module which generates status data” included in claim 1 are limitations that invokes 35 U.S.C. 112(f). However, the written description fails to clearly link or associate the disclosed structure, material, or acts to the claimed function such that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112 (f); or
(b) Amend the written description of the specification such that it clearly links or associates the corresponding structure, material, or acts to the claimed function without introducing any new matter (35 U.S.C. 132(a)); or
(c) State on the record where the corresponding structure, material, or acts are set forth in the written description of the specification and linked or associated to the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
In addition, as per claim 1, the claim recites “inputting a medium status.” The term “medium” in claim 1 is a relative term which renders the claim indefinite. The term “medium” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Further, claim 1 recites “which avoids the blocking of the evaluation.” There is no antecedent basis for the term “blocking” and “evaluation.” It is unclear what these unlbokcing steps are and what the evaluation refers to.
Furthermore, as per claim 1, the claim is directed toward improving the quality of service. However, the claim merely recites multiple modules which perform steps that do not seem related to improving the quality of service. The claim ultimately results in generating status data, and it is unclear how everything is tied together. There seems to be essential elements or steps missing. Applicants have failed to claim the applicant’s invention.
In sum, claim 1 is unclear and therefore indefinite. The claim will be interpreted as a system in a 802.11 network that utilizes machine learning and improves QoS.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention lacks patentable utility. As per claim 1, the claim is a directed toward a system with multiple modules and units. The preamble directs the claim to improve the quality of service. However, all the cited elements are cited for performing singular actions. There is minimal interaction between the elements, and it is unclear how these actions improve the quality of service. For example, elements and actions include 1), a device that communicates, 2) a controller that perfroms channel selection, 3) a module that performs an action to carry out channel selection, 4) a module that estimates probabilities for actions, 5) a module what avoids blocking of evaluation, 6) an optimization module which allows weights to be optimized, 7) a data storage unit that stores information, 8) a calculation module which calculates the success of channels to be selected, and 8) a module which generates status data. All such actions are well known activities that any general computer may perform and provides no patentable utility. No details on how such actions are performed are recited, and the actions that are recited provide no improvement to present systems. Thus, the claims are rejected under 101 as providing no utility.
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) 1 is rejected under 35 U.S.C. 102(a)(2) as being unpatentable over Lozano et al. US Patent Application Publication 2024/0214903 (Lozano).
As per claim 1, as best understood by the Examiner, Lozano teaches an opportunistic reinforcement learning-based system with computer-aided machine learning that includes at least one processor, which is developed for channel access and selection in 802.11 networks and allows users to improve the quality of service received from the network, characterized in that it comprises: at least one device (1) which is located in an 802.11 network and communicates over that network, at least one channel selection controller (2) based on opportunistic reinforcement learning, which provides data transmission in wireless communication and performs channel selection between the networks, at least one software module (3), which is a deep Q network (DQN) agent performing an action selection to carry out the channel selection, at least one rule network module (4), which is a deep neural network, inputting a medium status and estimating the probabilities for each action, at least one destination network module (5) which avoids the blocking of the evaluation of the updated network arising from the successive implementation of the actions applied to the medium, at least one optimization module (6), which allows the weights of the destination network module (5) to be optimized, at least one data storage unit (7), which is an experience memory unit in which the actions taken by the software module (3), which is a DQN agent, the rewards obtained, and the situations obtained by the medium in response to the action are recorded, at least one reward calculation module (8) which calculates the success (reward) of the channel (action) to be selected considering the channel density in data transmission, at least one status module (9), which generates status data using the device's (1) location data in the second and third dimensions, timestamp data, and signal values read from the channels. (see Lozano abstract and throughout with utilizing machine learning to steer client to access points to improve QoS; see paragraphs 42, 43, and throughout with 802.11 system).
Allowable Subject Matter
Claims 2-5 are allowed.
The following is an examiner’s statement of reasons for allowance: Below is the closest prior art the Examiner has found:
Lozanno et al. US Patent Application Publication 2024/0214903 teaches client steering in mesh networks by utilizing QoS packets, and accomplishes such features by utilizing machine learning and training the system to steer clients to the respective access points for increasing throughput of the network (abstract and throughout)
Anand US Patent Application Publication 2022/0182873 teaches a device selecting best networks to connect to and utilizies QoS while implementing machine learning techniques (see abstract), and further teaches utilizing 802.11 schemes and the selection of channels (paragraph 46), and further teaches training machine learning systems (paragraphs 58-59).
Overcash et al. US Patent No. 12,439,436 teaches a system which allows dynamic channel selection to improve speed and QoS (see abstract), and further teaches implementing them in 802.11 systems (see throughout reference).
Although the references above teach many aspects of the claimed, invention, the invention, as a whole, would not have been obvious over the cited art of record.
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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JASON KAI YIN GEE whose telephone number is (571)272-6431. The examiner can normally be reached on Monday-Friday 8:30-5:00 PST Pacific.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Farid Homayounmehr can be reached on (571) 272-3739. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JASON K GEE/Primary Examiner, Art Unit 2495
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