DETAILED ACTION
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 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.
Claims 1-5, 11-14 and 16-18 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pantelidou (US Pub. 2024/0323835).
Regarding claim 1, Pantelidou discloses a method comprising:
receiving, by a network management system from a plurality of access points (APs) deployed in a network, telemetry data comprising information about client associations and network activity of the plurality of Aps (par.006; par. 024 “OAM”, par. 043, fig.1 element 16);
identifying, by the network management system (par.024 “OAM”, fig.1 element 16), a candidate AP for power saving from the plurality of APs based on the telemetry data (par.006 “mobile communication”, par.042 “one or more of the gNBs”, par.043 “KPI, “UE measurements”, “load measurement”, “radio load”, par.059 “emergency calls”) and using a machine learning model (par.009, 014);
inferring, by the network management system, a power-saving transition for the candidate AP based on the telemetry data using the machine learning model (par.046 “which cells should be switched off”, “proactively switch off or on the cell”); and
operating, by the network management system, the candidate AP in a power-saving mode as per the power-saving transition (par.046 “which cells should be switched off”).
Regarding claim 2, Pantelidou discloses training the machine learning model, by the network management system during a learning phase (par.009 “learning”), to learn one or more reduced utilization patterns for the plurality of APs, based on the network activity reported in the telemetry data (par.010 “energy saving decision…..a reward for implementing the respective energy saving pattern”, par.080 “Different switch-on switch-off patterns of cells”).
Regarding claims 3 and 17, Pantelidou discloses using the machine learning model to identify the candidate AP and infer the power-saving transition for the candidate AP based on the learned one or more reduced utilization patterns (par.046 “which cells should be switched off”).
Regarding claims 4 and 13, Pantelidou discloses learn roaming characteristics of a client device based on the client associations reported in the telemetry data, wherein the roaming characteristics define a temporal sequence of APs that the client device has associated within a predefined interval (par.054 “a coverage layer….saving report including an estimate of additional traffic in the event”, par.079 “the coverage layer during this time window…….the time window(s)”).
Regarding claims 5 and 18, Pantelidou discloses inferring, by the network management system, a power-on transition for the candidate AP based on the learned roaming characteristics of a client device (par.043 “UE measurements”); and resuming, by the network management system, operations of the candidate AP as per the power-on transition in advance of the client device associating with the candidate AP (par.043 “switched-on”).
Regarding claim 11, Pantelidou discloses everything as claim 1 above. More specifically, Patelidou discloses a network management system comprising: a machine-readable storage medium storing executable instructions (par.020) to:
receiving, from a plurality of access points (APs) deployed in a network, telemetry data comprising information about client associations and network activity of the plurality of Aps (par.006; par. 024 “OAM”, par. 043, fig.1 element 16);
identifying, candidate AP for power saving from the plurality of APs based on the telemetry data (par.006 “mobile communication”, par.042 “one or more of the gNBs”, par.043 “KPI, “UE measurements”, “load measurement”, “radio load”, par.059 “emergency calls”) and using a machine learning model (par.009, 014);
inferring a power-saving transition for the candidate AP based on the telemetry data using the machine learning model (par.046 “which cells should be switched off”, “proactively switch off or on the cell”); and
operating the candidate AP in a power-saving mode as per the power-saving transition (par.046 “which cells should be switched off”).
Regarding claim 12, Pantelidou discloses training the machine learning model, by the network management system during a learning phase (par.009 “learning”), to learn one or more reduced utilization patterns for the plurality of APs, based on the network activity reported in the telemetry data (par.010 “energy saving decision…..a reward for implementing the respective energy saving pattern”, par.080 “Different switch-on switch-off patterns of cells”); and
and identify the candidate AP and infer the power-saving transition for the candidate AP based on the learned one or more reduced utilization patterns (par.023 “determining which cell…..should be turned …off”).
Regarding claim 14, Pantelidou discloses infer a power-on transition for the candidate AP based on the learned roaming characteristics of a client device; and resume operations of the candidate AP as per the power-on transition in advance of the client device associating with the candidate AP (par.021-023 “load and timing information……..determining which cell….should be turned on”).
Regarding claim 16, Pantelidou discloses everything as claim 1 above. More specifically, Patelidou discloses an access point (AP) configured to provide wireless network connectivity to a client device; and a network management system coupled to the AP (fig. 1, par.078 “users in its cells”)
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.
Claims 10 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Pantelidou (US Pub. 2024/0323835) in view of LV (CN 112804739 A).
Regarding claims 10 and 20, Patelidou fails to discloses operating the candidate AP in the power-saving mode comprises: operating the candidate AP in a sleep mode; operating the candidate AP in a deep-sleep mode.
LV discloses operating the candidate AP in the power-saving mode comprises: operating the candidate AP in a sleep mode; operating the candidate AP in a deep-sleep mode (page 5 “In order to……..the deep sleep”); or first operating the candidate AP in the sleep mode followed by operating the candidate AP in the deep-sleep mode responsive to determining no-data traffic for the candidate AP for a predefined duration after the candidate AP entered the sleep mode (consideration is optional). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to modify the system of Patelidou with the above teaching of LV in order to achieve the effect of saving energy.
Allowable Subject Matter
Claims 6-9, 15 and 19 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Examiner Tu Nguyen whose telephone number is (571)272-7883. The examiner can normally be reached on 8AM-5PM Eastern Time.
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/TU X NGUYEN/ Primary Examiner, Art Unit 2642
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