DETAILED ACTION
This first non-final action is in response to applicants’ original filing on 02/19/2025. Claims 1-20 are currently pending and have been considered as follows.
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.
Drawings
The drawings filed on 02/19/2025 are 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.
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 8 and 17 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.
Claim 8 recites the limitation "the determination” in line 1. There is insufficient antecedent basis for this limitation in the claim.
Claim 17 recites the limitation "the determination” in line 2. There is insufficient antecedent basis for this limitation in the claim.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, 4, 7, 9, 10, 12-14, 16, and 18-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by GACANIN et al. (US 20190124525 A1, hereinafter Gacanin).
As to Claim 1:
Gacanin discloses a method (e.g. Gacanin “a device and the related method that overcome the above identified shortcomings of existing solutions. More particularly, it is an objective to disclose an apparatus for managing performance of a Wi-Fi network” [0006]; a method for managing performance of a Wi-Fi network [0039]) comprising:
identifying information related to a first device connected to a Wi-Fi network, the information comprising network data related to operational parameters of the first device (e.g. Gacanin “a Wi-Fi network comprising one or more access points” [0007]; “collect network parameters of a configuration of the Wi-Fi network from the access points” [0008]; “Network parameters of the PHY can for example be a channel frequency response or CFR, a signal-to-noise ratio or SNR, noise, etc. Network parameters of the MAC layer can for example be a cyclic redundancy check or CRC, a throughput, a bit error rate or BER, etc. Network parameters of the NET layer can for example be an IP, an ID, a network, etc. Alternatively, network parameters may be derived from collected network parameters. For example, a signal-to-noise ratio may be calculated from a channel frequency response and from noise” [0034]; [0040]; “network parameters 30 of a configuration of a Wi-Fi network 2 are collected from access points 200 of the Wi-Fi network 2” [0055]);
analyzing the identified information for the first device based on stored operational parameters (e.g. Gacanin “compare the network parameters to predefined performance thresholds” [0009]; “the apparatus 1 also comprises a database 10 comprising the predefined performance thresholds 300 and/or the network parameters 30... The performance monitor 101 is then further adapted to store the network parameters 30 in the database 10” [0054]; “the network parameters 30 are compared to predefined performance thresholds 300” [0055]);
correlating, based on the analysis, the identified information for the first device to at least one of the stored operational parameters (e.g. Gacanin “identifying exceeding a predefined performance threshold as a performance symptom of the Wi-Fi network” [0042]; “a combination of two or more network parameters 30 is compared to a predefined performance threshold... predefined performance thresholds 300 may be retrieved from a database 115 of the performance monitor 101” [0054]; “the result of the comparison is analysed and exceeding a predefined performance threshold 300 is identified” [0055]); and
configuring operation of the first device on the Wi-Fi network based on the correlation, the configuration comprising modifying an initial operation of the first device to another configured operation on the Wi-Fi network (e.g. Gacanin “execute in function of the processed recommendations signals a plurality of algorithms to determine a network configuration for which the performance symptom is solved” [0013]; “the network configuration is initiated and executed in the Wi-Fi network, thereby solving the performance symptom identified from the network parameters. This way, the performance of the Wi-Fi network is improved” [0016]; “The network parameters are set to the corresponding Bayesian or belief network nodes having their numerical values discretized into different ranges” [0018]; [0039]; “The performance manager 102 is further configured to initiate the network configuration 21 in the Wi-Fi network 2” [0054]).
As to Claim 2:
Gacanin discloses the method of claim 1, further comprising the correlation of the first device comprising causing operation of an application on the first device to enable connectivity on the network via other configured operation (e.g. Gacanin “access points should be deployed in home networks on the “plug-and-play” basis and configure themselves, and they should also dynamically optimize their parameters when the home network is running in order to ensure the management of the home network stays simple and to guarantee the QoS” [0003]; “With a Self-Optimizing Network, or SON, the planning, the configuration, the management, the optimization and the healing of access networks is made simple and fast. With the SON functionality, newly added access points are self-configured in line with a “plug-and-play” paradigm while all operational access points will regularly self-optimize parameters and algorithmic behaviour in response to observed network performance and radio conditions. Furthermore, with the SON functionality, self-healing mechanisms can be triggered to temporarily compensate for a detected equipment outage, while awaiting a more permanent solution. The Wi-Fi SON functionality monitors network parameters in the form of read parameters from the Wi-Fi network and optimizes the performance of the Wi-Fi network by modifying the network parameters per use case basis. For example the Wi-Fi SON functionality modifies the coverage, the interference and the multi-band selection in order to optimize the traffic load balancing. The Wi-Fi SON functionality further gives out write parameters as outputs into the Wi-Fi network” [0004]; “the monitoring and the collection of network parameters of the Wi-Fi network are combined with self-optimizing functions” [0020]).
As to Claim 4:
Gacanin discloses the method of claim 1, further comprising the configured operation causing modified functionality for the first device on the Wi-Fi network (e.g. Gacanin “access points should be deployed in home networks on the “plug-and-play” basis and configure themselves, and they should also dynamically optimize their parameters when the home network is running in order to ensure the management of the home network stays simple and to guarantee the QoS” [0003]; “With a Self-Optimizing Network, or SON, the planning, the configuration, the management, the optimization and the healing of access networks is made simple and fast. With the SON functionality, newly added access points are self-configured in line with a “plug-and-play” paradigm while all operational access points will regularly self-optimize parameters and algorithmic behaviour in response to observed network performance and radio conditions. Furthermore, with the SON functionality, self-healing mechanisms can be triggered to temporarily compensate for a detected equipment outage, while awaiting a more permanent solution. The Wi-Fi SON functionality monitors network parameters in the form of read parameters from the Wi-Fi network and optimizes the performance of the Wi-Fi network by modifying the network parameters per use case basis. For example the Wi-Fi SON functionality modifies the coverage, the interference and the multi-band selection in order to optimize the traffic load balancing. The Wi-Fi SON functionality further gives out write parameters as outputs into the Wi-Fi network” [0004]; “the monitoring and the collection of network parameters of the Wi-Fi network are combined with self-optimizing functions” [0019]; “the network configuration is initiated and executed in the Wi-Fi network, thereby solving the performance symptom identified from the network parameters. This way, the performance of the Wi-Fi network is improved” [0016]; “The network parameters are set to the corresponding Bayesian or belief network nodes having their numerical values discretized into different ranges” [0018]; [0039]; “The performance manager 102 is further configured to initiate the network configuration 21 in the Wi-Fi network 2” [0054]).
As to Claim 7:
Gacanin discloses the method of claim 1, further comprising the operational parameters for the first device comprising information related to at least one of a time of device usage, software or firmware installation, a type of device, a transmission pattern, packet information, network connection information, location data, service provider information, or networking metadata (e.g. Gacanin “Network parameters of the PHY can for example be a channel frequency response or CFR, a signal-to-noise ratio or SNR, noise, etc. Network parameters of the MAC layer can for example be a cyclic redundancy check or CRC, a throughput, a bit error rate or BER, etc. Network parameters of the NET layer can for example be an IP, an ID, a network, etc” [0034]; [0054]).
As to Claim 9:
Gacanin discloses the method of claim 1, further comprising the stored operational parameters corresponding to a second device (e.g. Gacanin FIG. 2 apparatus 1, performance monitor comparator; “The predefined performance thresholds 300 may be retrieved from a database 115 of the performance monitor 101. For example, the network parameters 30 are set at said comparator 112 of said performance monitor 101 having their values discretized into different ranges” [0054]).
As to Claim 10:
Gacanin discloses the method of claim 1, further comprising stored operational parameters corresponding to the first device at a time prior to a time the identification of the information is performed (e.g. Gacanin “The predefined performance thresholds 300 are manually inputted in the apparatus 1. According to an alternative embodiment, the predefined performance thresholds 300 are programmed in the apparatus 1. The predefined performance thresholds 300 may be retrieved from a database 115 of the performance monitor 101… a network parameter 30 may be a received signal strength indicator and its value can be found within several regions denoted by 0-10 dB, 10-20 dB, etc. The predefined performance thresholds 300 in this case are 0 dB, 10 dB, 20 dB, etc. The comparator 112 evaluates the value of the network parameter 30 can for example be in one of three states for example a first state “good”, a second state “medium” and a third state “low” depending on the comparison of the network parameter 30 with the predefined performance thresholds 300. The comparator 112 identifies if the network parameter 30 exceeds a predefined performance threshold 300” [0054]).
As to Claim 12:
Gacanin discloses a non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions (e.g. Gacanin “Local memory 504 may include a random access memory (RAM) or another type of dynamic storage device that stores information and instructions for execution by processor 502 and/or a read only memory (ROM) or another type of static storage device that stores static information and instructions for use by processor 504” [0056]), that when executed by a processor, perform a method comprising:
identifying information related to a first device connected to a Wi-Fi network, the information comprising network data related to operational parameters of the first device (e.g. Gacanin “a Wi-Fi network comprising one or more access points” [0007]; “collect network parameters of a configuration of the Wi-Fi network from the access points” [0008]; “Network parameters of the PHY can for example be a channel frequency response or CFR, a signal-to-noise ratio or SNR, noise, etc. Network parameters of the MAC layer can for example be a cyclic redundancy check or CRC, a throughput, a bit error rate or BER, etc. Network parameters of the NET layer can for example be an IP, an ID, a network, etc. Alternatively, network parameters may be derived from collected network parameters. For example, a signal-to-noise ratio may be calculated from a channel frequency response and from noise” [0034]; [0040]; “network parameters 30 of a configuration of a Wi-Fi network 2 are collected from access points 200 of the Wi-Fi network 2” [0055]);
analyzing the identified information for the first device based on stored operational parameters (e.g. Gacanin “compare the network parameters to predefined performance thresholds” [0009]; “the apparatus 1 also comprises a database 10 comprising the predefined performance thresholds 300 and/or the network parameters 30... The performance monitor 101 is then further adapted to store the network parameters 30 in the database 10” [0054]; “the network parameters 30 are compared to predefined performance thresholds 300” [0055]);
correlating, based on the analysis, the identified information for the first device to at least one of the stored operational parameters (e.g. Gacanin “identifying exceeding a predefined performance threshold as a performance symptom of the Wi-Fi network” [0042]; “a combination of two or more network parameters 30 is compared to a predefined performance threshold... predefined performance thresholds 300 may be retrieved from a database 115 of the performance monitor 101” [0054]; “the result of the comparison is analysed and exceeding a predefined performance threshold 300 is identified” [0055]); and
configuring operation of the first device on the Wi-Fi network based on the correlation, the configuration comprising modifying an initial operation of the first device to another configured operation on the Wi-Fi network (e.g. Gacanin “execute in function of the processed recommendations signals a plurality of algorithms to determine a network configuration for which the performance symptom is solved” [0013]; “the network configuration is initiated and executed in the Wi-Fi network, thereby solving the performance symptom identified from the network parameters. This way, the performance of the Wi-Fi network is improved” [0016]; “The network parameters are set to the corresponding Bayesian or belief network nodes having their numerical values discretized into different ranges” [0018]; [0039]; “The performance manager 102 is further configured to initiate the network configuration 21 in the Wi-Fi network 2” [0054]).
As to Claim 13:
Gacanin discloses the non-transitory computer-readable storage medium of claim 12, further comprising the correlation of the first device comprising causing operation of an application on the first device to enable connectivity on the network via other configured operation (e.g. Gacanin “access points should be deployed in home networks on the “plug-and-play” basis and configure themselves, and they should also dynamically optimize their parameters when the home network is running in order to ensure the management of the home network stays simple and to guarantee the QoS” [0003]; “With a Self-Optimizing Network, or SON, the planning, the configuration, the management, the optimization and the healing of access networks is made simple and fast. With the SON functionality, newly added access points are self-configured in line with a “plug-and-play” paradigm while all operational access points will regularly self-optimize parameters and algorithmic behaviour in response to observed network performance and radio conditions. Furthermore, with the SON functionality, self-healing mechanisms can be triggered to temporarily compensate for a detected equipment outage, while awaiting a more permanent solution. The Wi-Fi SON functionality monitors network parameters in the form of read parameters from the Wi-Fi network and optimizes the performance of the Wi-Fi network by modifying the network parameters per use case basis. For example the Wi-Fi SON functionality modifies the coverage, the interference and the multi-band selection in order to optimize the traffic load balancing. The Wi-Fi SON functionality further gives out write parameters as outputs into the Wi-Fi network” [0004]; “the monitoring and the collection of network parameters of the Wi-Fi network are combined with self-optimizing functions” [0020]).
As to Claim 14:
Gacanin discloses the non-transitory computer-readable storage medium of claim 12, further comprising the configured operation causing modified functionality for the first device on the Wi-Fi network (e.g. Gacanin “access points should be deployed in home networks on the “plug-and-play” basis and configure themselves, and they should also dynamically optimize their parameters when the home network is running in order to ensure the management of the home network stays simple and to guarantee the QoS” [0003]; “With a Self-Optimizing Network, or SON, the planning, the configuration, the management, the optimization and the healing of access networks is made simple and fast. With the SON functionality, newly added access points are self-configured in line with a “plug-and-play” paradigm while all operational access points will regularly self-optimize parameters and algorithmic behaviour in response to observed network performance and radio conditions. Furthermore, with the SON functionality, self-healing mechanisms can be triggered to temporarily compensate for a detected equipment outage, while awaiting a more permanent solution. The Wi-Fi SON functionality monitors network parameters in the form of read parameters from the Wi-Fi network and optimizes the performance of the Wi-Fi network by modifying the network parameters per use case basis. For example the Wi-Fi SON functionality modifies the coverage, the interference and the multi-band selection in order to optimize the traffic load balancing. The Wi-Fi SON functionality further gives out write parameters as outputs into the Wi-Fi network” [0004]; “the monitoring and the collection of network parameters of the Wi-Fi network are combined with self-optimizing functions” [0019]; “the network configuration is initiated and executed in the Wi-Fi network, thereby solving the performance symptom identified from the network parameters. This way, the performance of the Wi-Fi network is improved” [0016]; “The network parameters are set to the corresponding Bayesian or belief network nodes having their numerical values discretized into different ranges” [0018]; [0039]; “The performance manager 102 is further configured to initiate the network configuration 21 in the Wi-Fi network 2” [0054]).
As to Claim 16:
Gacanin discloses the non-transitory computer-readable storage medium of claim 12, further comprising the operational parameters for the first device comprising information related to at least one of a device identifier, a time of device usage, software or firmware installation, a type of device, a transmission pattern, packet information, network connection information, location data, service provider information, or networking metadata (e.g. Gacanin “Network parameters of the PHY can for example be a channel frequency response or CFR, a signal-to-noise ratio or SNR, noise, etc. Network parameters of the MAC layer can for example be a cyclic redundancy check or CRC, a throughput, a bit error rate or BER, etc. Network parameters of the NET layer can for example be an IP, an ID, a network, etc” [0034]; [0054]).
As to Claim 18:
Gacanin discloses the non-transitory computer-readable storage medium of claim 12, further comprising the stored operational parameters corresponding to a second device (e.g. Gacanin FIG. 2 apparatus 1, performance monitor comparator; “The predefined performance thresholds 300 may be retrieved from a database 115 of the performance monitor 101. For example, the network parameters 30 are set at said comparator 112 of said performance monitor 101 having their values discretized into different ranges” [0054]).
As to Claim 19:
Gacanin discloses the non-transitory computer-readable storage medium of claim 12, further comprising the stored operational parameters corresponding to the first device at a time prior to a time the identification of the information is performed (e.g. Gacanin “The predefined performance thresholds 300 are manually inputted in the apparatus 1. According to an alternative embodiment, the predefined performance thresholds 300 are programmed in the apparatus 1. The predefined performance thresholds 300 may be retrieved from a database 115 of the performance monitor 101… a network parameter 30 may be a received signal strength indicator and its value can be found within several regions denoted by 0-10 dB, 10-20 dB, etc. The predefined performance thresholds 300 in this case are 0 dB, 10 dB, 20 dB, etc. The comparator 112 evaluates the value of the network parameter 30 can for example be in one of three states for example a first state “good”, a second state “medium” and a third state “low” depending on the comparison of the network parameter 30 with the predefined performance thresholds 300. The comparator 112 identifies if the network parameter 30 exceeds a predefined performance threshold 300” [0054]).
As to Claim 20:
Gacanin discloses a system (e.g. Gacanin FIG. 4 “a device and the related method that overcome the above identified shortcomings of existing solutions. More particularly, it is an objective to disclose an apparatus for managing performance of a Wi-Fi network” [0006]; computing system [0056]) comprising:
a processor (e.g. Gacanin FIG. 4 processor 502 [0056]) configured to:
identify information related to a first device connected to a Wi-Fi network, the information comprising network data related to operational parameters of the first device (e.g. Gacanin “a Wi-Fi network comprising one or more access points” [0007]; “collect network parameters of a configuration of the Wi-Fi network from the access points” [0008]; “Network parameters of the PHY can for example be a channel frequency response or CFR, a signal-to-noise ratio or SNR, noise, etc. Network parameters of the MAC layer can for example be a cyclic redundancy check or CRC, a throughput, a bit error rate or BER, etc. Network parameters of the NET layer can for example be an IP, an ID, a network, etc. Alternatively, network parameters may be derived from collected network parameters. For example, a signal-to-noise ratio may be calculated from a channel frequency response and from noise” [0034]; [0040]; “network parameters 30 of a configuration of a Wi-Fi network 2 are collected from access points 200 of the Wi-Fi network 2” [0055]);
analyze the identified information for the first device based on stored operational parameters (e.g. Gacanin “compare the network parameters to predefined performance thresholds” [0009]; “the apparatus 1 also comprises a database 10 comprising the predefined performance thresholds 300 and/or the network parameters 30... The performance monitor 101 is then further adapted to store the network parameters 30 in the database 10” [0054]; “the network parameters 30 are compared to predefined performance thresholds 300” [0055]);
correlate, based on the analysis, the identified information for the first device to at least one of the stored operational parameters (e.g. Gacanin “identifying exceeding a predefined performance threshold as a performance symptom of the Wi-Fi network” [0042]; “a combination of two or more network parameters 30 is compared to a predefined performance threshold... predefined performance thresholds 300 may be retrieved from a database 115 of the performance monitor 101” [0054]; “the result of the comparison is analysed and exceeding a predefined performance threshold 300 is identified” [0055]); and
configure operation of the first device on the Wi-Fi network based on the correlation, the configuration comprising modifying an initial operation of the first device to another configured operation on the Wi-Fi network (e.g. Gacanin “execute in function of the processed recommendations signals a plurality of algorithms to determine a network configuration for which the performance symptom is solved” [0013]; “the network configuration is initiated and executed in the Wi-Fi network, thereby solving the performance symptom identified from the network parameters. This way, the performance of the Wi-Fi network is improved” [0016]; “The network parameters are set to the corresponding Bayesian or belief network nodes having their numerical values discretized into different ranges” [0018]; [0039]; “The performance manager 102 is further configured to initiate the network configuration 21 in the Wi-Fi network 2” [0054]).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Gacanin in view of ELSINS et al. (US 20190097976 A1, hereinafter Elsins).
As to Claim 3:
Gacanin discloses the method of claim 1, but does not specifically disclose:
causing connectivity of the first device with the Wi-Fi network to occur via a portal.
However, the analogous art Elsins does disclose causing connectivity of the first device with the Wi-Fi network to occur via a portal (e.g. Elsins “the secure portal device may provide a Wi-Fi AP (Access Point) with a captive portal, so that when the user connects to that AP with his mobile phone, computer, or other device, a browser may open automatically and shows a Web page which guides the user through further actions, such as: (1) Connect the secure portal device to Internet using either Wi-Fi network” [0044]). Gacanin and Elsins are analogous art because they are from the same field of endeavor in accessing Wi-Fi networks.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art, having the teachings of Gacanin and Elsins before him or her, to modify the disclosure of Gacanin with the teachings of Elsins to include causing connectivity of the first device with the Wi-Fi network to occur via a portal as claimed. The suggestion/motivation for doing so would have been to provide a secure and convenient way to establish a remote branch of a home area network, and therefore any resource connected to the home area network (Elsins [0008]; [0040]). Therefore, it would have been obvious to combine Gacanin and Elsins to obtain the invention as specified in the instant claim(s).
Claims 5, 6, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Gacanin in view of Gunasekara et al. (US 20180352473 A1, hereinafter Gunasekara).
As to Claim 5:
Gacanin discloses the method of claim 1, but does not specifically disclose:
updating the stored operational parameters based on the correlation.
However, the analogous art Gunasekara does disclose updating the stored operational parameters based on the correlation (e.g. Gunasekara “a plurality of parameters associated with a wireless interface of the wireless AP utilizing the first radio protocol; modify the data representative of the configuration, the modification comprising an update of at least one of the plurality of parameters; and transmit the modified data representative of the configuration to the wireless AP, the modified data enabling the wireless AP to modify at least one operational characteristic associated with the wireless interface based on the updated at least one parameter” [0015]; [0064]; [0148]; “determines that the configuration of one or more Wi-Fi APs (e.g., AP 204 in FIG. 4) should be updated so as to meet a prescribed performance level; e.g., to match the LTE in connectivity parameters (such as back-off waiting period, LBT procedures, signal strength, RF parameters, etc.), thereby affording Wi-Fi a more competitive opportunity to connect with the client devices 211” [0153]; “retrieve a configuration file from the mass storage 705, AP DB 205, or provisioning server 201, and then modify connectivity parameters stored in the configuration file based at least in part on reports received from the background scanner and other identified network conditions” [0230]). Gacanin and Gunasekara are analogous art because they are from the same field of endeavor in configuring Wi-Fi networks.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art, having the teachings of Gacanin and Gunasekara before him or her, to modify the disclosure of Gacanin with the teachings of Gunasekara to include updating the stored operational parameters based on the correlation as claimed. The suggestion/motivation for doing so would have been to thereby afford Wi-Fi a more competitive opportunity to connect with the client devices (Gunasekara [0153]). Therefore, it would have been obvious to combine Gacanin and Gunasekara to obtain the invention as specified in the instant claim(s).
As to Claim 6:
Gacanin discloses the method of claim 1, but does not specifically disclose:
the operational parameters for the first device comprising a device identifier.
However, the analogous art Gunasekara does disclose the operational parameters for the first device comprising a device identifier (e.g. Gunasekara “device specific IDs (e.g., MAC address or the like) can be cross-correlated to MSO subscriber data maintained” [0074]; “AP DB 205 in the illustrated embodiment retains data relating to, among other things: (i) AP identification (e.g., MAC)” [0097]). Gacanin and Gunasekara are analogous art because they are from the same field of endeavor in configuring Wi-Fi networks.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art, having the teachings of Gacanin and Gunasekara before him or her, to modify the disclosure of Gacanin with the teachings of Gunasekara to include the operational parameters for the first device comprising a device identifier as claimed. The suggestion/motivation for doing so would have been so as to enable selective client (and/or AP) configuration changes to enhance WLAN prioritization over competing RATs (Gunasekara [0096]). Therefore, it would have been obvious to combine Gacanin and Gunasekara to obtain the invention as specified in the instant claim(s).
As to Claim 15:
Gacanin discloses the non-transitory computer-readable storage medium of claim 12, but does not specifically disclose:
updating the stored operational parameters based on the correlation.
However, the analogous art Gunasekara does disclose updating the stored operational parameters based on the correlation (e.g. Gunasekara “a plurality of parameters associated with a wireless interface of the wireless AP utilizing the first radio protocol; modify the data representative of the configuration, the modification comprising an update of at least one of the plurality of parameters; and transmit the modified data representative of the configuration to the wireless AP, the modified data enabling the wireless AP to modify at least one operational characteristic associated with the wireless interface based on the updated at least one parameter” [0015]; [0064]; [0148]; “determines that the configuration of one or more Wi-Fi APs (e.g., AP 204 in FIG. 4) should be updated so as to meet a prescribed performance level; e.g., to match the LTE in connectivity parameters (such as back-off waiting period, LBT procedures, signal strength, RF parameters, etc.), thereby affording Wi-Fi a more competitive opportunity to connect with the client devices 211” [0153]; “retrieve a configuration file from the mass storage 705, AP DB 205, or provisioning server 201, and then modify connectivity parameters stored in the configuration file based at least in part on reports received from the background scanner and other identified network conditions” [0230]). Gacanin and Gunasekara are analogous art because they are from the same field of endeavor in configuring Wi-Fi networks.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art, having the teachings of Gacanin and Gunasekara before him or her, to modify the disclosure of Gacanin with the teachings of Gunasekara to include updating the stored operational parameters based on the correlation as claimed. The suggestion/motivation for doing so would have been to thereby afford Wi-Fi a more competitive opportunity to connect with the client devices (Gunasekara [0153]). Therefore, it would have been obvious to combine Gacanin and Gunasekara to obtain the invention as specified in the instant claim(s).
Claims 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Gacanin in view of McKay (US 20170041744 A).
As to Claim 8:
Gacanin discloses the method of claim 1, but does not specifically disclose:
determining the operational parameters of the first device correspond to a randomized version of at least one of the stored operational parameters.
However, the analogous art McKay does disclose determining the operational parameters of the first device correspond to a randomized version of at least one of the stored operational parameters (e.g. McKay “Identifying information of mobile devices (e.g., MAC address) can be parsed from WiFi connections, Bluetooth connections, and so on, with the mobile devices, and correlated with measured signal strengths, such that mobile devices can be (1 uniquely identified and (2) triangulated, while accounting for randomization associated with, for instance, MAC addresses of the mobile devices” [0009]; “Particular mobile phone operating systems (e.g., Apple iOS, such as iOS 8) may periodically transmit a “phantom” WiFi Media Access Control (MAC) address (e.g., randomized MAC address) that is not the actual WiFi MAC of the device (e.g., assigned to the device, for instance by a manufacturer)” [0024]). Gacanin and McKay are analogous art because they are from the same field of endeavor in monitoring Wi-Fi networks.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art, having the teachings of Gacanin and McKay before him or her, to modify the disclosure of Gacanin with the teachings of McKay to include determining the operational parameters of the first device correspond to a randomized version of at least one of the stored operational parameters as claimed. The suggestion/motivation for doing so would have been so as to minimize the impact of phantom mobile device identifiers on the quality of these measurements (McKay [0007]). Therefore, it would have been obvious to combine Gacanin and McKay to obtain the invention as specified in the instant claim(s).
As to Claim 17:
Gacanin discloses the non-transitory computer-readable storage medium of claim 12, but does not specifically disclose:
determining the operational parameters of the first device correspond to a randomized version of at least one of the stored operational parameters.
However, the analogous art McKay does disclose determining the operational parameters of the first device correspond to a randomized version of at least one of the stored operational parameters (e.g. McKay “Identifying information of mobile devices (e.g., MAC address) can be parsed from WiFi connections, Bluetooth connections, and so on, with the mobile devices, and correlated with measured signal strengths, such that mobile devices can be (1 uniquely identified and (2) triangulated, while accounting for randomization associated with, for instance, MAC addresses of the mobile devices” [0009]; “Particular mobile phone operating systems (e.g., Apple iOS, such as iOS 8) may periodically transmit a “phantom” WiFi Media Access Control (MAC) address (e.g., randomized MAC address) that is not the actual WiFi MAC of the device (e.g., assigned to the device, for instance by a manufacturer)” [0024]). Gacanin and McKay are analogous art because they are from the same field of endeavor in monitoring Wi-Fi networks.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art, having the teachings of Gacanin and McKay before him or her, to modify the disclosure of Gacanin with the teachings of McKay to include determining the operational parameters of the first device correspond to a randomized version of at least one of the stored operational parameters as claimed. The suggestion/motivation for doing so would have been so as to minimize the impact of phantom mobile device identifiers on the quality of these measurements (McKay [0007]). Therefore, it would have been obvious to combine Gacanin and McKay to obtain the invention as specified in the instant claim(s).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Gacanin in view of Ergen (US 20210297866 A1).
As to Claim 11:
Gacanin discloses the method of claim 1, but does not specifically disclose:
the analysis being performed via an artificial intelligence (AI) model.
However, the analogous art Ergen does disclose the analysis being performed via an artificial intelligence (AI) model (e.g. Ergen “The method and system collects radio frequency (RF) measurements pertaining to each client device, the connected Wi-Fi access point, and the plurality of nearby Wi-Fi access points, and an Artificial Intelligence (AI) model is utilized to derive interference measurements based on the RF measurements. The AI model then derives configurations related to Wi-Fi network parameters associated with the connected Wi-Fi access point based on the RF measurements and the interference measurements by solving a complex optimization problem. The Wi-Fi network parameters are then updated based on the derived configurations” [Abstract]; “the AI model derives configurations related to one or more Wi-Fi network parameters associated with the connected Wi-Fi access point based on the RF measurements and the interference measurements… The AI model then utilizes the RF measurements and the interference measurements to maximize overall performance of the Wi-Fi network by solving a complex optimization problem” [0029]; “Cloud platform 106 then utilizes AI model 210 to derive configurations related to one or more Wi-Fi network parameters associated with connected Wi-Fi access point 102A based on the RF measurements and the interference measurements” [0041]; [0078]-[0082]). Gacanin and Ergen are analogous art because they are from the same field of endeavor in monitoring Wi-Fi networks.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art, having the teachings of Gacanin and Ergen before him or her, to modify the disclosure of Gacanin with the teachings of Ergen to include the analysis being performed via an artificial intelligence (AI) model as claimed. The suggestion/motivation for doing so would have been to enhance signal qualities/performance within a Wi-Fi network based on user-centric and interference measurements from nearby Wi-Fi access points and Wi-Fi capable devices in the Wi-Fi network, to provide higher throughput despite different characteristics of network elements and changing network conditions (Ergen [0001]). Therefore, it would have been obvious to combine Gacanin and Ergen to obtain the invention as specified in the instant claim(s).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicants’ disclosure.
An et al. (US 20070076664 A1)
Yang (US 20170013667 A1)
Powell et al. (US 20200136904 A1)
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/KENNETH W CHANG/Primary Examiner, Art Unit 2438
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