Detailed Action
The office action is in response to the communications filed on 05/04/2023.
Notice of 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 .
Claims Status
Claims 1-20 are pending in this application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/04/2023, 10/20/2023, 09/20/2024, and 05/09/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Ramalingam et al. (Patent No. US 11,375,255), the prior art discloses that for a given event, situation, and/or condition (e.g., a given amount of network traffic, a given latency, etc.) based on the event data, the treatment experimentation module 613 may select various treatment parameters (e.g., settings) to adjust from the parameter library; see column 14 lines 22-26. The event data and the treatment selected from the parameter library 614 may be sent to the simulation module 615 to determine the predicted network performance based on the assigned treatment for the given event ; see column 14 lines 26-30.
Allowable Subject Matter
Claims 3-5 and 13-14 are 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.
Claim Rejections - 35 USC § 103
The following is a quotation of AIA 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under AIA 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 7, 11, 16, and 20 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Velusamy et al. (Patent No. US 10,716,019; hereinafter referred as Velusamy) in view of Black et al. (Patent No. US 11,190,266; hereinafter referred as Black).
Regarding claims 1, 11, and 20, Velusamy discloses a memory configured to store one or more instructions and a simulator of the digital twin (It is inherent that the electronic device includes a memory in order to store instructions. NOTE: The simulator of a digital twin has been equated to the instructions that enable simulating the key performance indicator (KPI).);
a transceiver (It is inherent that the electronic device includes a transceiver in order to receive the instructions.); and
at least one processor configured to execute the one or more instructions to (It is inherent that the electronic device includes at least one processor in order to execute the instructions.):
obtain at least one simulated key performance indicator (KPI) by providing, to the simulator, information (Determine a second set of KPIs for the simulation of the network communication activity, wherein initiates a simulation of the same or similar network communication activity see column 2 lines 53-55; see figure 4a numeral 408.);
calculate a degree of similarity between the at least one simulated KPI and at least one network KPI received through the transceiver (Determine a first set of KPIs for the network communication activity on a default wireless network; see figure 4 numeral 404. Compare [similarity] the first set of KPIs and the second set of KPIs to determine whether one or more features of the alternative wireless network are superior to that of the default network; see figure 4a numeral 410.); and
update the at least one input parameter, based on the calculated degree of similarity (Present at least one recommendation [input parameter] based on the one or more superior network performance features; see figure 4a numeral 414).
Velusamy discloses determining a set of KPI based on the simulation of the network communication activity, but fails to explicitly disclose providing, to the simulator, information indicating whether or not a function of the network base station is activated, an operation parameter related to an operation of the network base station, and at least one input parameter to replicate the network base station, which are received through the transceiver. However, in analogous art, Black discloses that the digital element twin may be employed to model mirrored characteristics, parameters, firmware versions, and key performance indicator (KPI) values of the actual RF signal repeater device; see column 6 lines 37-42. The KPI values may include one or more of system up time [activation], RF power level [input parameter], device temperature, polarization downlink over time, polarization uplink over time, quality of service [operation parameter] or the like; see column 6 lines 54-57. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Velusamy simulation system by incorporating the data (e.g. up time, RF power level, or QoS) of Black in order to avoid any disruption of service by first simulating the data changes.
Regarding claims 7 and 16, Velusamy discloses wherein an item of the at least one network KPI and an item of the at least one simulated KPI comprise at least one of throughput of a cell, a number of activated terminals, or a use amount of a physical resource block (PRB), collected at a predetermined time of the network base station (The first and second sets of KPIs are then compared by the comparison application to determine one or more network performance features of the alternative wireless carrier network that are superior to the one or more corresponding network performance features of the default wireless carrier network, wherein the one or more superior network performance features may include a higher network data throughput rate; see column 2 lines 63-67.).
Claims 2 and 12 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Velusamy et al. (Patent No. US 10,716,019; hereinafter referred as Velusamy) in view of Black et al. (Patent No. US 11,190,266; hereinafter referred as Black) and further in view of Yousefi'zadeh et al. (Patent No. US 10,841,853; hereinafter referred as Yousefi'zadeh).
Regarding claims 2 and 12, Velusamy, as modified teaches parent claims 1 and 11. In addition, Velusamy discloses presenting at least one recommendation [input parameter] based on the one or more superior network performance features (see figure 4a numeral 414), but fails to explicitly disclose updating the at least one input parameter based on one or more optimized input parameters which are generated by using a repetition-based optimization algorithm on the at least one input parameter, wherein the repetition-based optimization algorithm comprises at least one from among at least one of a genetic algorithm (GA) and a particle swarm optimization (PSO) algorithm. However, in analogous art, Yousefi'zadeh discloses choosing genetic algorithm (GA) optimization algorithm to redistribute traffic as the result of changing power, antenna tilt, and handover thresholds of the plurality of cells; see figure 11 numeral 114 & column 4 lines 37-44. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Velusamy simulation system by incorporating the optimization algorithm of Yousefi'zadeh in order to effectively redistribute traffic from congested cells to non-congested cells thereby optimally reducing the congestion and balancing the load of the cellular network.
Claims 6 and 15 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Velusamy et al. (Patent No. US 10,716,019; hereinafter referred as Velusamy) in view of Black et al. (Patent No. US 11,190,266; hereinafter referred as Black) and further in view of Lukens et al. (Publication No. US 2023/0206060; hereinafter referred as Lukens).
Regarding claims 6 and 15, Velusamy, as modified teaches parent claims 1 and 11. In addition, Velusamy discloses comparing [similarity] the first set of KPIs and the second set of KPIs (see figure 4a numeral 410), but fails to explicitly disclose calculating the degree of similarity between the at least one simulated KPI and the at least one network KPI by using a mean absolute percentage error (MAPE). However, in analogous art, Lukens discloses determining a mean absolute percentage error (MAPE) between the network traffic metrics and the predicted network traffic metrics [simulated], wherein the metrics [KPI] such as throughput, bandwidth, latency, and peak gateway performance, among others; see ¶ 38. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Velusamy simulation system by incorporating the mean error of Lukens in order to more accurate determine the performance of devices communicating across the network.
Claims 8-9 and 17-18 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Velusamy et al. (Patent No. US 10,716,019; hereinafter referred as Velusamy) in view of Black et al. (Patent No. US 11,190,266; hereinafter referred as Black) and further in view of Flanagan et al. (Publication No. US 2016/0212633; hereinafter referred as Flanagan).
Regarding claims 8 and 17, Velusamy, as modified teaches parent claims 1 and 11. In addition, Velusamy discloses simulating KPI based on information, but fail to explicitly disclose that the information [operation parameter] comprises at least one of a handover parameter, a selection or re-selection parameter, a cell on/off parameter, or a load balancing parameter. However, in analogous art, Flanagan discloses all network simulations performed within the SON optimizers may be based upon the network configuration at the time the relevant measurements were taken, wherein the configuration includes various thresholds defined for controlling handover decisions; see ¶ 35. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Velusamy simulation system by incorporating the network configuration of Flanagan in order to provide a higher possible degree of accuracy and improve the likelihood that simulated network changes will achieve their predicted KPI improvements, when implemented within the network.
Regarding claims 9 and 18, Velusamy, as modified teaches parent claims 1 and 11. In addition, Velusamy discloses simulating KPI based on information, but fail to explicitly disclose that the information indicating whether or not the function is activated comprises information about whether or not at least one of a scheduling algorithm, a handover algorithm, or a discontinuous reception (DRX) algorithm is activated. However, in analogous art, Flanagan discloses all network simulations performed within the SON optimizers may be based upon the network configuration at the time the relevant measurements were taken, wherein the configuration includes frequencies/channels/time-slots/spreading codes; see ¶ 35. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Velusamy simulation system by incorporating the network configuration of Flanagan in order to provide a higher possible degree of accuracy and improve the likelihood that simulated network changes will achieve their predicted KPI improvements, when implemented within the network.
Claims 10 and 19 are rejected under AIA 35 U.S.C. 103 as being unpatentable over Velusamy et al. (Patent No. US 10,716,019; hereinafter referred as Velusamy) in view of Black et al. (Patent No. US 11,190,266; hereinafter referred as Black) and further in view of Larish et al. (Publication No. US 2019/0149425; hereinafter referred as Larish).
Regarding claims 10 and 19, Velusamy, as modified teaches parent claims 1 and 11. In addition, Velusamy discloses simulating KPI based on information, but fail to explicitly disclose that the information [input parameter] indicates at least one of an average packet size, an average request interval, or a number of terminals. However, in analogous art, Larish discloses a simulated VNF MO represent a virtualized eNodeB, wherein the simulated VNF MO receive the workload vector may specify a total number of UE devices connected to the eNodeB; see ¶ figure 5A & ¶ 83. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Velusamy simulation system by incorporating the workload vector of Larish in order to take into account various conditions that vary across networks and/or devices.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HECTOR REYES whose telephone number is (571)270-0239. The examiner can normally be reached M-F 6-5.
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/H.R/Examiner, Art Unit 2472
/KEVIN T BATES/Supervisory Patent Examiner, Art Unit 2472