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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/09/24, 11/20/24 & 07/28/2026 has been considered by the examiner.
EXAMINER’S NOTES:
The examiner notes that a portion of the IDs filed 07/09/24 has not considered, Specifically, “Cite No: 4. Publication Number: 22019021350 Publication date: 2019-07-11 and Name of Patentee or Applicant of cited Document: Vasseur et al.” has been crossed out and not considered because the cited publication number 22019021350 cannot be located as it appears to be incorrect.
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) 1-3, 5, 7-10, 12, 14-16, 18 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over NAKAGAWA (US Patent Publication 2025/0150920 herein after referenced as Naka).
Regarding claim 1 and claim 9 and claim 15, Naka discloses:
A method comprising: and A system comprising: a memory storage; and a processing unit coupled to the memory storage, wherein the processing unit is operative to: and A non-transitory computer-readable medium that stores a set of instructions which when executed perform a method executed by the set of instructions comprising: receiving traffic information (Naka, [0008] discloses According to an aspect of the present disclosure, a communication apparatus includes at least one memory storing instructions, and at least one processor configured to execute the instructions stored in the at least one memory to cause the communication apparatus to transmit (i.e. reads on receiving), to a server, an inference request including all or part of information about quality of a wireless channel, information indicating conditions of loads of a plurality of access points, information about a characteristic of traffic (i.e. reads on traffic information), and time-series data on any of the foregoing pieces of information in a unit of time, wherein the inference request requests inference of quality of communication with another communication apparatus in a case where traffic steering processing for tuning at least any one of a connection state and a communication path between the communication apparatus and the another communication apparatus is executed, acquire a result of inference (i.e. reads on sending a recommendation) of the quality of the communication from the server, determine whether to execute the traffic steering based on the result of the inference. One of ordinary skill in the art would recognize that it is inherent for complex devices such as the communication apparatus and the server to include a processor and memory storing instructions in order to be able to perform the disclosed functionalities).
Naka discloses in one embodiment that a server receives an inference request including traffic information and provides an inference result but fails to explicitly recite in the same embodiment, the limitations of “receiving traffic information from a plurality of Access Points (APs); based on the traffic information, modeling traffic associated with the plurality of APs; based on the modeled traffic, modeling a gain in AP efficiency for one or more APs of the plurality of APs when modifying Station (STA) traffic of a STA; and sending a recommendation to one or more recipient APs of the plurality of APs, wherein the recommendation indicates the gain in AP efficiency for the one or more APs when modifying the STA traffic”.
In a different embodiment, Naka discloses:
receiving traffic information from a plurality of Access Points (APs); (Naka, [0039] discloses The data collection server 105 accumulates data collected from the AP 101 and/or the other APs (i.e. reads on from a plurality of APs) in a data storage unit 321. The data collection server 105 transmits the accumulated data (i.e. reads on receiving traffic information) to the inference server 106 with the data collection/provision unit 322 as appropriate; Naka, [0047]-[0048] discloses Examples of the information about a load placed on the AP 101 include the number of connected STAs, a communication rate of traffic of each STA and the total of all STAs, and information about a processing load placed on a CPU and discloses The information about QoS traffic includes for example information about round trip latency RTT at both ends of the network over which the STA 102 has performed communication, a packet loss rate, a communication throughput, jitter fluctuation, and a priority level of a packet. These pieces of information are examples of the information about characteristics of traffic. The communication characteristics i.e., appropriate throughput, reliability, and minimum latency appropriate for the network service used by the user who owns the STA, which can be inferred and acquired from a priority level and a trend of traffic, may be included in the information about QoS of end-to-end traffic. The above-described pieces of information are examples of the information about characteristics of traffic; Naka, [0086] discloses In step S901, the inference server 106 initially determines whether a traffic steering inference request including metadata for input is received from the AP 101; Naka, [0092] discloses For example, the wireless communication system may be intended for an enterprise in which a plurality of APs is managed and controlled by an access point controller. In such a case, the learning processing and the inference processing may be executed by the access point controller).
based on the traffic information, modeling traffic associated with the plurality of APs; (Naka, [0040] discloses The inference server 106 receives the acquired input information (i.e. reads on based on the traffic information) and the result data from the data collection server 105, and generates a learning model (i.e. reads on modeling traffic associated with the plurality of APs) by using a training data generation unit 332 and a training unit 333. The generated learning model is stored in the data storage unit 331. In response to a request for an inference value from the AP 101, the inference server 106 calculates the inference value through an inference unit 334 by using a learning result, and returns a calculation result to the AP 101; Naka, [0087] discloses In a case where the traffic steering inference request is received YES in step S901, the processing proceeds to step S902. In step S902, the inference server 106 performs input to the trained model based on the metadata for input).
based on the modeled traffic, modeling a gain in AP efficiency for one or more APs of the plurality of APs when modifying Station (STA) traffic of a STA; (Naka, [0069]-[0070] discloses The inference server 106 infers, based on the input data (i.e. reads on based on the modeled traffic) included in the traffic steering inference request transmitted from the AP 101, information about BSS of a transition destination of a link when traffic steering is executed e.g. a list of BSS transition candidates, and returns the information as an inference result. In step S504, the inference server 106 also infers a recommendation score (i.e. reads on modeling a gain in AP efficiency) of the link and information about addition and/or deletion of a link (i.e. reads on when modifying STA traffic) between the STA 102 (i.e. reads on of a STA) and AP 101 (i.e. reads on for one or more APs of the plurality of APs), and returns results as an inference result to the AP 101 and discloses The AP 101 determines whether to steer the traffic between the STA 102 and the AP 101 based on the traffic steering inference result received from the inference server 106. In a case where the AP 101 determines that traffic steering is to be performed, in step S505, the AP 101 transmits a traffic steering request to the STA 102 to steer the traffic between the STA 102 and the AP 101. In response to the STA 102 receiving the traffic steering request, the STA 102 performs the traffic steering on another AP based on the request; Naka, [0088] discloses In step S903, the inference server 106 acquires a traffic steering inference result from the learning model (i.e. reads on based on the modeled traffic). In step S904, the inference server 106 transmits the acquired inference result to the AP 101; Naka, [0052] discloses in addition to estimating the action to be taken next in order to improve the QoS value of the end-to-end traffic in the current situation, the recommendation score indicating a degree of improvement (i.e. reads on gain in AP efficiency) when that action is taken is also inferred; Naka, [0039] discloses The data collection server 105 accumulates data collected from the AP 101 and/or the other APs (i.e. reads on from a plurality of APs) in a data storage unit 321; Naka, [0005] discloses In an environment where a plurality of wireless access points hereinafter called “AP” is present, a communication efficiency can be presumably improved by connecting stations hereinafter, called “STA” in a distributed manner to APs having low loads while avoiding APs with high loads to which many STAs are connected. Thus, it is expected that STAs are appropriately distributed to be connected to APs, in view of the communication characteristics to be provided for the services used by the STAs. Through this distribution processing, efficiency can be presumably improved for the entire network (i.e. reads on gain in AP efficiency) while providing, to the respective STAs, the network having communication characteristics necessary for the corresponding STA. The technique for tuning a connection state and/or a communication path in view of the efficiency and the communication characteristics is called “traffic steering”).
and sending a recommendation to one or more recipient APs of the plurality of APs, wherein the recommendation indicates the gain in AP efficiency for the one or more APs when modifying the STA traffic (Naka, [0069]-[0070] discloses The inference server 106 infers, based on the input data included in the traffic steering inference request transmitted from the AP 101, information about BSS of a transition destination of a link when traffic steering is executed e.g. a list of BSS transition candidates, and returns the information as an inference result. In step S504, the inference server 106 also infers a recommendation score (i.e. reads on the gain in AP efficiency) of the link and information about addition and/or deletion of a link (i.e. reads on when modifying the STA traffic) between the STA 102 and AP 101 (i.e. reads on for the one or more APs), and returns results as an inference result (i.e. reads on sending a recommendation and reads on wherein the recommendation indicates) to the AP 101 (i.e. reads on to one or more recipient APs of the plurality of APs) and discloses The AP 101 determines whether to steer the traffic between the STA 102 and the AP 101 based on the traffic steering inference result received from the inference server 106. In a case where the AP 101 determines that traffic steering is to be performed, in step S505, the AP 101 transmits a traffic steering request to the STA 102 to steer the traffic between the STA 102 and the AP 101. In response to the STA 102 receiving the traffic steering request, the STA 102 performs the traffic steering on another AP based on the request; Naka, [0052] discloses in addition to estimating the action to be taken next in order to improve the QoS value of the end-to-end traffic in the current situation, the recommendation score indicating a degree of improvement (i.e. reads on gain in AP efficiency) when that action is taken is also inferred; Naka, [0039] discloses The data collection server 105 accumulates data collected from the AP 101 and/or the other APs (i.e. reads on from a plurality of APs) in a data storage unit 321; Naka, [0005] discloses In an environment where a plurality of wireless access points hereinafter called “AP” is present, a communication efficiency can be presumably improved by connecting stations hereinafter, called “STA” in a distributed manner to APs having low loads while avoiding APs with high loads to which many STAs are connected. Thus, it is expected that STAs are appropriately distributed to be connected to APs, in view of the communication characteristics to be provided for the services used by the STAs. Through this distribution processing, efficiency can be presumably improved for the entire network (i.e. reads on gain in AP efficiency) while providing, to the respective STAs, the network having communication characteristics necessary for the corresponding STA. The technique for tuning a connection state and/or a communication path in view of the efficiency and the communication characteristics is called “traffic steering”).
Therefore, at the time before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to modify the invention of Naka to incorporate the teachings of the different embodiments for the purpose of conforming to the intent of the invention to modify and combine the various different embodiment (Naka, [0100] & [0104]) to make the system more dynamic and adaptable by providing the system with various different alternatives in design and functionality, thereby allowing the system to handle a number of various different combination of specific design structure and scenarios and preventing the system from being limited to a single specific design structure and scenario and furthermore, one of ordinary skill in the art would recognize based on the guidelines to rationales supporting a conclusion of obviousness seen on MPEP 2143, that the modification would involve use of a simple substitution of one known element and base device (i.e. performing a process of an embodiment of a server receiving an inference request including traffic information and providing an inference result as taught by Naka) with another known element and comparable device utilizing a known technique (i.e. performing a process of a similar embodiment of a server receiving an inference request including traffic information and providing an inference result with additional and/or alternative features and functionalities of the other embodiments as taught by Naka) to improve the similar devices in the same way and to obtain the predictable result of the system performing a process of an embodiment of a server receiving an inference request including traffic information and providing an inference result (i.e. as taught by Naka) and is dependent upon the specific intended use, design incentives, needs and requirements (i.e. such as due to teachings of a known standard, current technology, conservation of resources, personal preferences, economic considerations, etc.) of the user and the system as has been established in MPEP 2144.04.
Regarding claim 2 and claim 10 and claim 16, Naka discloses:
The method of claim 1, (see claim 1) and The system of claim 9, (see claim 9) and The non-transitory computer-readable medium of claim 15, (see claim 15).
wherein modifying the STA traffic comprises any one of (i) removing the STA traffic from a current AP of the plurality of APs, (ii) moving the STA traffic to a new AP of the plurality of APs, (Naka, [0070] discloses The AP 101 determines whether to steer the traffic between the STA 102 and the AP 101 based on the traffic steering inference result received from the inference server 106. In a case where the AP 101 determines that traffic steering is to be performed, in step S505, the AP 101 transmits a traffic steering request to the STA 102 to steer the traffic between the STA 102 and the AP 101. In response to the STA 102 receiving the traffic steering request, the STA 102 performs the traffic steering on another AP based on the request. EXAMINER’S NOTE: The examiner notes that the claims are written in an alternative limitation format requiring and contingent on the selection of only one of various alternative options presented and as such the non-selected alternative options are crossed out (i.e. the limitations reciting “(iii) reducing an airtime allocation for the STA traffic, or (iv) any combination of (i)-(iii)”) and are not given patentable weight as being directed towards limitations that are not required to be performed as is indicated in MPEP 2143.03 that recites “Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art” and in MPEP 2111.04, Section ll that recites “The broadest reasonable interpretation of a claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition precedent are not met”).
Regarding claim 3, Naka discloses:
The method of claim 1, (see claim 1).
wherein the traffic information comprises any one of (i) information identifying associated STAs, (Naka, [0044] & Table 1 discloses For example, information about quality of a wireless channel between the AP 101 and STA 102, information about an AP in the vicinity of the STA 102, load information indicating a condition of load placed on the AP 101, information about quality of service QOS of the end-to-end traffic, and priority levels of respective pieces of information are used as the input data input to the learning model. Examples of input data and output data input to/output from the learning model are illustrated in Table 1 and Table 1 shows STA ID; Naka, [0019] discloses A wireless communication system in FIG. 1 includes access points AP 101, 101b, and 101c, stations STA 102, 107, and 110. EXAMINER’S NOTE: The examiner notes that the claims are written in an alternative limitation format requiring and contingent on the selection of only one of various alternative options presented and as such the non-selected alternative options are crossed out (i.e. the limitations reciting “(ii) information identifying a sender and a receiver of traffic, (iii) frame duration information, (iv) Modulation and Coding Scheme (MCS) information, (v) information identifying movement of STAs, (vi) information identifying Multi-Link Device (MLD) capable STAs, (vii) information identifying traffic type, or (viii) any combination of (i)-(vii)”) and are not given patentable weight as being directed towards limitations that are not required to be performed as is indicated in MPEP 2143.03 that recites “Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art” and in MPEP 2111.04, Section ll that recites “The broadest reasonable interpretation of a claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition precedent are not met”).
Regarding claim 5 and claim 12 and claim 18, Naka discloses:
The method of claim 1, (see claim 1) and The system of claim 9, (see claim 9) and The non-transitory computer-readable medium of claim 15, (see claim 15).
wherein modeling the traffic associated with the plurality of APs comprises any one of (Naka, [0071] discloses In the present exemplary embodiment, the STA such as the STA 102 that is in connection to the AP 101 performs steering on another AP operating as a follower. The present exemplary embodiment is not limited thereto. For example, in a case where an inference result indicates that the traffic of an STA belonging to a follower AP e.g., AP 101b is to be steered to another AP e.g., AP 101c, the AP 101 requests the traffic steering with respect to the STA. In this case, the AP 101 transmits the traffic steering request to a certain STA via the AP 101b serving as the follower. EXAMINER’S NOTE: The examiner notes that the claims are written in an alternative limitation format requiring and contingent on the selection of only one of various alternative options presented and as such the non-selected alternative options are crossed out (i.e. the limitations reciting “(i) identifying one or more STAs associated to two or more APs of the plurality of APs,” and “(iii) identifying one or more STAs not capable of associating to one or more neighboring APs, or (iv) any combination of (i)-(iii)”) and are not given patentable weight as being directed towards limitations that are not required to be performed as is indicated in MPEP 2143.03 that recites “Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art” and in MPEP 2111.04, Section ll that recites “The broadest reasonable interpretation of a claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition precedent are not met”).
Regarding claim 7 and claim 14 and claim 20, Naka discloses:
The method of claim 1, (see claim 1) and The system of claim 9, (see claim 9) and The non-transitory computer-readable medium of claim 15, (see claim 15).
wherein modeling the gain in AP efficiency comprises any one of: (i) using naive Bayes to evaluate an effect of modifying the STA traffic by moving the STA traffic to a new AP of the plurality of APs; (Naka, [0061] discloses Examples of learning algorithms include algorithms such as nearest neighbors, Naive Bayes classifiers, decision trees, and support vector machines. Examples of learning algorithms further include deep learning which generates by itself a feature amount for learning and a connection weight coefficient by using a neural network. Any algorithm available from among the above-described algorithms can be used and applied to the present exemplary embodiment as appropriate; Naka, [0069]-[0071] discloses The inference server 106 infers, based on the input data included in the traffic steering inference request transmitted from the AP 101, information about BSS of a transition destination of a link when traffic steering is executed e.g. a list of BSS transition candidates, and returns the information as an inference result. In step S504, the inference server 106 also infers a recommendation score of the link and information about addition and/or deletion of a link between the STA 102 and AP 101, and returns results as an inference result to the AP 101 and discloses The AP 101 determines whether to steer the traffic between the STA 102 and the AP 101 based on the traffic steering inference result received from the inference server 106. In a case where the AP 101 determines that traffic steering is to be performed, in step S505, the AP 101 transmits a traffic steering request to the STA 102 to steer the traffic between the STA 102 and the AP 101. In response to the STA 102 receiving the traffic steering request, the STA 102 performs the traffic steering on another AP based on the request and discloses In the present exemplary embodiment, the STA such as the STA 102 that is in connection to the AP 101 performs steering on another AP operating as a follower. The present exemplary embodiment is not limited thereto. For example, in a case where an inference result indicates that the traffic of an STA belonging to a follower AP e.g., AP 101b is to be steered to another AP e.g., AP 101c, the AP 101 requests the traffic steering with respect to the STA. In this case, the AP 101 transmits the traffic steering request to a certain STA via the AP 101b serving as the follower. EXAMINER’S NOTE: The examiner notes that the claims are written in an alternative limitation format requiring and contingent on the selection of only one of various alternative options presented and as such the non-selected alternative options are crossed out (i.e. the limitations reciting “or (ii) using a regressor coupled with a booster that minimizes uncertainty resulting from modifying the STA traffic by moving the STA traffic to the new AP of the plurality of APs”) and are not given patentable weight as being directed towards limitations that are not required to be performed as is indicated in MPEP 2143.03 that recites “Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art” and in MPEP 2111.04, Section ll that recites “The broadest reasonable interpretation of a claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition precedent are not met”).
Regarding claim 8, Naka discloses:
The method of claim 1, (see claim 1).
wherein an AP of the one or more recipient APs sends at least a portion of the recommendation to the STA (Naka, [0069]-[0071] discloses The inference server 106 infers, based on the input data included in the traffic steering inference request transmitted from the AP 101, information about BSS of a transition destination of a link when traffic steering is executed e.g. a list of BSS transition candidates, and returns the information as an inference result. In step S504, the inference server 106 also infers a recommendation score of the link and information about addition and/or deletion of a link between the STA 102 and AP 101, and returns results as an inference result to the AP 101 and discloses The AP 101 determines whether to steer the traffic between the STA 102 and the AP 101 based on the traffic steering inference result received from the inference server 106. In a case where the AP 101 determines that traffic steering is to be performed, in step S505, the AP 101 transmits a traffic steering request to the STA 102 to steer the traffic between the STA 102 and the AP 101. In response to the STA 102 receiving the traffic steering request, the STA 102 performs the traffic steering on another AP based on the request and discloses In the present exemplary embodiment, the STA such as the STA 102 that is in connection to the AP 101 performs steering on another AP operating as a follower. The present exemplary embodiment is not limited thereto. For example, in a case where an inference result indicates that the traffic of an STA belonging to a follower AP e.g., AP 101b is to be steered to another AP e.g., AP 101c, the AP 101 requests the traffic steering with respect to the STA. In this case, the AP 101 transmits the traffic steering request to a certain STA via the AP 101b serving as the follower).
Claim(s) 4, 11 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over NAKAGAWA (US Patent Publication 2025/0150920 herein after referenced as Naka) in view of Foreign Document "Performance optimizations for wireless access points" (EP 2 947 910 A2 herein after referenced as Saha).
Regarding claim 4 and claim 11 and claim 17, Naka discloses:
The method of claim 1, (see claim 1) and The system of claim 9, (see claim 9) and The non-transitory computer-readable medium of claim 15, (see claim 15).
wherein modeling the traffic associated with the plurality of APs comprises using (Naka, [0087] discloses In a case where the traffic steering inference request is received YES in step S901, the processing proceeds to step S902. In step S902, the inference server 106 performs input to the trained model based on the metadata for input; Naka, [0081] discloses When the inference server 106 receives a metadata list from the data collection server 105 in step S802, in step S803, the inference server 106 generates a data set to be used for learning, from time-series data. The input data may be entire data of a certain continuous period. For example, the input data may be data of one day in a past, sampled and collected minute by minute).
Naka discloses performing a process of modeling traffic information to reconfigure access points but fails to explicitly recite the use of a regressor and therefore fails to disclose “using a regressor to model”.
In a related field of endeavor, Saha discloses:
using a regressor to model (Saha, [0019] discloses The predictive modeler 166, for example, may generate a model to forecast the performance of the access point based on the calculated variables outputted from the device analyzer 164. The model may be generated using a stepwise regression analysis to test all combinations of the independent variables during multiple iterations of the model; Saha, [0079] discloses In block 1220, the predictive modeler 166 may create a linear regression model to predict the performance of the access points based on the network analytic record and to identify and resolve the causes or reasons for the underperforming access points. In this regard, the predictive modeler 166 may analyze variables to determine their impact upon the performance of the underperforming access points as calculated by the device analyzer 164. That is, the predictive modeler 166 may generate a variable contribution summary that sequentially ranks the independent variables in order of their impact upon the dependent variable. The predictive modeler 166 may then output the model and the variable contribution summary to the configuration circuit 168 to deploy the model for the selected access points on the configuration portal 1000; Saha, [0070] discloses According to an example, the configuration circuit 168 may adjust the controllable input parameters 1050 to optimize the performance of the selected access points. That is, by adjusting the controllable input parameters 1050 of the configuration portal 1000, the respective independent variables are modified to facilitate improved access point performance).
Therefore, at the time before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to modify the invention of Naka to incorporate the teachings of Saha for the purpose of providing the system with a means to generate a model that tests all combinations of variables during multiple iterations to forecast the performance of the access point (Saha, [0019]) to optimize and facilitate improved access point performance (Saha, [0070]) and for the purpose of making the system more dynamic and adaptable by providing the system with added functionalities and various different alternatives in design, thereby allowing the system to handle a number of various different combination of specific design structure and scenarios and thereby, preventing the system from being limited to a single specific design structure and scenario (Naka, [0100] & [0104]) and furthermore, one of ordinary skill in the art would recognize based on the guidelines to rationales supporting a conclusion of obviousness seen on MPEP 2143, that the modification would involve use of a simple substitution of one known element and base device (i.e. performing a process of modeling information to reconfigure access points as taught by Naka) with another known element and comparable device utilizing a known technique (i.e. performing a process of modeling information to reconfigure access points, wherein the modeling process utilizes regression techniques as taught by Saha) to improve the similar devices in the same way and to obtain the predictable result of the system performing a process of modeling information to reconfigure access points (i.e. as taught by both Naka & Saha) and is dependent upon the specific intended use, design incentives, needs and requirements (i.e. such as due to teachings of a known standard, current technology, conservation of resources, personal preferences, economic considerations, etc.) of the user and the system as has been established in MPEP 2144.04.
Claim(s) 6, 13 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over NAKAGAWA (US Patent Publication 2025/0150920 herein after referenced as Naka) in view of Donepudi et al. (US Patent Publication 2014/0133456 herein after referenced as Done).
Regarding claim 6 and claim 13 and claim 19, Naka discloses:
The method of claim 1, (see claim 1) and The system of claim 9, (see claim 9) and The non-transitory computer-readable medium of claim 15, (see claim 15).
wherein: modeling the gain in AP efficiency comprises identifying the STA (Naka, [0069]-[0071] discloses The inference server 106 infers, based on the input data included in the traffic steering inference request transmitted from the AP 101, information about BSS of a transition destination of a link when traffic steering is executed e.g. a list of BSS transition candidates, and returns the information as an inference result. In step S504, the inference server 106 also infers a recommendation score of the link and information about addition and/or deletion of a link between the STA 102 and AP 101, and returns results as an inference result to the AP 101 and discloses The AP 101 determines whether to steer the traffic between the STA 102 and the AP 101 based on the traffic steering inference result received from the inference server 106. In a case where the AP 101 determines that traffic steering is to be performed, in step S505, the AP 101 transmits a traffic steering request to the STA 102 to steer the traffic between the STA 102 and the AP 101. In response to the STA 102 receiving the traffic steering request, the STA 102 performs the traffic steering on another AP based on the request and discloses In the present exemplary embodiment, the STA such as the STA 102 that is in connection to the AP 101 performs steering on another AP operating as a follower. The present exemplary embodiment is not limited thereto. For example, in a case where an inference result indicates that the traffic of an STA belonging to a follower AP e.g., AP 101b is to be steered to another AP e.g., AP 101c, the AP 101 requests the traffic steering with respect to the STA. In this case, the AP 101 transmits the traffic steering request to a certain STA via the AP 101b serving as the follower).
Naka discloses performing traffic steering by identifying the mobile station but fails to explicitly recite that the identified mobile station is an edge mobile station and therefore fails to disclose “identifying the STA is an edge STA”.
In a related field of endeavor, Done discloses:
identifying the STA is an edge STA (Done, [0085] discloses The computing cloud 630 has a global view of the loading experienced by each multi-RAT node 612, 614, 616 to which it is communicatively coupled. This global view allows the computing cloud 630 to achieve an optimal network load by selectively offloading cell edge UEs to neighbor cells by intelligent redirection as well as cell radius planning).
Therefore, at the time before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to modify the invention of Naka to incorporate the teachings of Done for the purpose of providing the system with a means to select the type of mobile stations to offload or steer to another access point or cell to achieve optimal network load (Done, [0085]) and for the purpose of making the system more dynamic and adaptable by providing the system with added functionalities and various different alternatives in design, thereby allowing the system to handle a number of various different combination of specific design structure and scenarios and thereby, preventing the system from being limited to a single specific design structure and scenario (Naka, [0100] & [0104]) and furthermore, one of ordinary skill in the art would recognize based on the guidelines to rationales supporting a conclusion of obviousness seen on MPEP 2143, that the modification would involve use of a simple substitution of one known element and base device (i.e. performing traffic steering by identifying the mobile station as taught by Naka) with another known element and comparable device utilizing a known technique (i.e. performing traffic steering by identifying the mobile station, wherein the identified mobile stations are cell edge mobile stations as taught by Done) to improve the similar devices in the same way and to obtain the predictable result of the system performing traffic steering by identifying the mobile station (i.e. as taught by both Naka & Done) and is dependent upon the specific intended use, design incentives, needs and requirements (i.e. such as due to teachings of a known standard, current technology, conservation of resources, personal preferences, economic considerations, etc.) of the user and the system as has been established in MPEP 2144.04.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL Y MAPA whose telephone number is (571)270-5540. The examiner can normally be reached Monday thru Thursday: 10 AM - 8 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anthony Addy can be reached at (571) 272 - 7795. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL Y MAPA/Primary Examiner, Art Unit 2645
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