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 .
The claims 1-20 are pending.
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.
Claim(s) 1-7 and 12-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Gemelli et al (US Patent No. 12,526,684 B2).
With respect to claim 1, Gemelli teaches a method performed by a server in a wireless communication system (network management system 140, Fig. 1), the method comprising:
acquiring first configuration management (CM) information and first performance management (PM) information of a first period for a sector managed by the server (col. 27, lines 5-67 disclose optimizer 504 in Network management system collecting training data related to training sector over an observation period; different collected training data include raw KPI values for KPIs are collected from performance management sub-system 142 for a training sector, sector configuration information for a training sector, such as the number of cells or frequency layers overlapping the training sector, actual load distribution parameters applied or set for the training sector, etc. The training data may include information specific to the cells that overlap the training sector, and architectural cell information indicating configuration management (CM) characteristics of a cell that contribute to the relationship between user throughput and the number of active users in the cell; see also Fig. 19 disclose knowledge DB for a training sector),
wherein the first CM information includes a first load balance parameter used for distribution of communication traffic in the sector (col. 27, lines 5-67 disclose sector configuration information for a training sector, such as the number of cells or frequency layers overlapping the training sector, actual load distribution parameters applied or set for the training sector, etc. The training data may include information specific to the cells that overlap the training sector, and architectural cell information indicating configuration management (CM) characteristics of a cell that contribute to the relationship between user throughput and the number of active users in the cell; see also Fig. 19), and wherein the first PM information includes at least one PM value indicating communication performance of the sector (col. 27, lines 5-67 disclose collected training data include raw KPI values for KPIs are collected from performance management sub-system 142 for a training sector; also Fig. 19); training a load balance model based on the first CM information and the first PM information (col. 28, line 1-36 disclose using the training data to build one or more ML models 524 for ML system 522); and determining a second load balance parameter to be used for distribution of communication traffic in the sector, based on output information which is outputted as a plurality of candidate load balance parameters are inputted to the load balance model (col. 29, line 5-col. 31, line 49 disclose outputting for a sector recommended load distribution parameters for the training sector by iterative sector optimization or by another system that implements another optimization strategy that maximizes or augments the aggregated user throughput of a training sector).
With respect to claim 2, Gemelli teaches wherein the first PM information further includes information on a number of at least one user equipment (UE) in the sector and information on traffic of the at least one UE (col. 2, lines 21-36 disclose performing sector throughput optimization over multiple optimization iterations of determining a total number of active users in the sector, determining a target number of users per cell that maximizes an aggregated user throughput of the sector where a sum of the target number of users per cell is equal to the total number of active users in the sector; col. 29, line 5-col. 31, line 49 disclose outputting for a sector recommended load distribution parameters for the training sector by iterative sector optimization or by another system that implements another optimization strategy that maximizes or augments the aggregated user throughput of a training sector), and wherein the load balance model outputs the at least one PM value indicting the communication performance of the sector based on the first CM information, the information on the number of the at least one UE, and the information on the traffic of the at least one UE which are inputted to the load balance model (col. 29, line 5-col. 31, line 49 disclose outputting for a sector recommended load distribution parameters for the training sector by iterative sector optimization or by another system that implements another optimization strategy that maximizes or augments the aggregated user throughput of a training sector).
With respect to claim 3, Gemelli teaches determining a load balance parameter policy to be applied to a base station for a second period after the first period, based on the determined second load balance parameter (col. 29, line 5-col. 31, line 49 disclose outputting for a sector recommended load distribution parameters for the training sector by iterative sector optimization or by another system that implements another optimization strategy that maximizes or augments the aggregated user throughput of a training sector), wherein the base station performs communication with at least one UE in the sector, based on the determined load balance parameter policy (col. 33, lines 40-67 disclose optimizer 504 applying the recommended load distribution parameters 622 in sector 202 of RAN 120).
With respect to claim 4, Gemelli teaches wherein the load balance parameter policy includes information on an identification (ID) of the sector, information on the first period, information on a number of the at least one UE in the sector, information on traffic of the at least one UE, information on whether the base station applies the second load balance parameter to the base station for the second period, and/or information on a rate at which the second load balance parameter is applied for the second period (col. 29, line 5-col. 31, line 49 disclose outputting for a sector recommended load distribution parameters for the training sector by iterative sector optimization or by another system that implements another optimization strategy that maximizes or augments the aggregated user throughput of a training sector; col. 33, lines 40-67 disclose optimizer 504 applying the recommended load distribution parameters 622 in sector 202 of RAN 120; see col. 14, lines 30-64 disclose details about recommended load distribution parameters).
With respect to claim 5, Gemelli teaches transmitting information on a predetermined load balance parameter policy to a base station or an external server controlling configuration of the base station (col. 12, lines 5-18 disclose the recommended load distribution parameters may be provided to one or more load management features 148 utilized for RAN 120, such as part of the configuration parameters provided to RAN 120), wherein the base station acquires the first PM information for the first period by using the first CM information which is acquired based on the predetermined load balance parameter policy, and wherein the first CM information and the first PM information are stored in an external database (col. 14, lines 30-64 disclose Optimization manager 514 then determines, adapts, or modifies recommended load distribution parameters 622 for the sector 202 based on the target number of users per cell 401-402 (step 712). The recommended load distribution parameters 622 may include percentage values, percentage weights, or some other values or indicators used for load management. The recommended load distribution parameters 622 may also include a target number of users per cell, a traffic split, or other information. Load distribution parameters may be initially assigned for a sector 202, and may be adapted or adjusted with each optimization iteration. Thus, in determining the recommended load distribution parameters 622, optimization manager 514 may adjust or adapt load distribution parameters initially assigned to the sector 202 (such as for the first iteration), or adapt the load distribution parameters from a prior optimization iteration); acquiring the first CM information and the first PM information from the external database (col. 27, lines 5-67 disclose optimizer 504 in Network management system collecting training data related to training sector over an observation period; different collected training data include raw KPI values for KPIs are collected from performance management sub-system 142 for a training sector, sector configuration information for a training sector, such as the number of cells or frequency layers overlapping the training sector, actual load distribution parameters applied or set for the training); and training the load balance model based on the first CM information and the first PM information (col. 28, line 1-36 disclose using the training data to build one or more ML models 524 for ML system 522);
With respect to claim 6, Gemelli teaches wherein the acquired first PM information includes throughput information on a throughput measured in cells in the sector for the first period and/or downlink load information on a downlink load measured in the cells in the sector for the first period (col. 27, lines 4-56 disclose collected training data including user throughput of the cell), and wherein the predetermined load balance parameter policy is predetermined based on at least one of the throughput information or the downlink load information (col. 12, lines 5-18 disclose the recommended load distribution parameters may be provided to one or more load management features 148 utilized for RAN 120, such as part of the configuration parameters provided to RAN 120))
With respect to claim 7, Gemelli teaches wherein the first PM information includes a plurality of PM values, and the plurality of PM values indicate communication performance of cells in the sector, and wherein the method further comprises: comparing one of a minimum value, a maximum value, or a standard deviation of the plurality of PM values with a target PM value, and determining whether to transmit the second load balance parameter to a base station or an external server controlling configuration of the base station, based on a result of comparing (col. 28, lines 37-col. 30, line 8 disclose KPIs include sector aggregated user throughput, sector aggregated capacity, sector busy hour aggregated capacity, handover performance band, DL channel quality band, UL link quality band, DL signal quality band, etc.; determining a mean, median, or mode of the raw KPI values over the observation period to determine the representative KPI value. Data handler 529 then stores the representative KPI value for the KPI as training data in knowledge database 528; After the data collection and training phase, ML system 522 may be used to output a prediction or recommendation based on input data for a new sector).
With respect to claim 12, Gemelli teaches wherein the first CM information includes a hand over parameter of a base station and a selection parameter on cells in the sector (col. 27, lines 5-col. 28, line 36 disclose training data collected from different source), and
wherein the first PM information includes information on a number of at least one user equipment (UE) in the sector, information on traffic of the at least one UE, information on a throughput of the cells in the sector, information on a downlink load of the cells, information on reference signal received power (RSRP) of the cells, information on reference signal received quality (RSRQ) of the cells, and information on a rank index (RI) of the cells (col. 27, lines 5-col. 28, line 36 disclose training data collected from different source including dynamic cell information).
With respect to claim 13, Gemelli teaches acquiring second CM information and second PM information of a second period for the sector, wherein the second CM information includes the second load balance parameter, and wherein the second PM information includes at least one PM value indicating communication performance of the sector for the second period when the base station is set based on the second load balance parameter (col. 27, lines 5-67 disclose optimizer 504 in Network management system collecting training data related to training sector over an observation period; different collected training data include raw KPI values for KPIs are collected from performance management sub-system 142 for a training sector, sector configuration information for a training sector, such as the number of cells or frequency layers overlapping the training sector, actual load distribution parameters applied or set for the training sector, etc. The training data may include information specific to the cells that overlap the training sector, and architectural cell information indicating configuration management (CM) characteristics of a cell that contribute to the relationship between user throughput and the number of active users in the cell; see also Fig. 19 disclose knowledge DB for a training sector);
training the load balance model based on the second CM information and the second PM information (col. 28, line 1-36 disclose using the training data to build one or more ML models 524 for ML system 522); and determining a third load balance parameter to be used for distribution of the communication traffic in the sector for a third period, based on the trained load balance model, wherein the third period is after the second period (col. 14, lines 30-64 disclose Optimization manager 514 then determines, adapts, or modifies recommended load distribution parameters 622 for the sector 202 based on the target number of users per cell 401-402 (step 712). The recommended load distribution parameters 622 may include percentage values, percentage weights, or some other values or indicators used for load management. The recommended load distribution parameters 622 may also include a target number of users per cell, a traffic split, or other information. Load distribution parameters may be initially assigned for a sector 202, and may be adapted or adjusted with each optimization iteration. Thus, in determining the recommended load distribution parameters 622, optimization manager 514 may adjust or adapt load distribution parameters initially assigned to the sector 202 (such as for the first iteration), or adapt the load distribution parameters from a prior optimization iteration).
With respect to claim 14, Gemelli teaches wherein the second period arrives after a designated time from the first period (col. 27, lines 5-col. 28, line 36 disclose training data collected from different source over observation period).
With respect to claim 15, Gemelli teaches wherein the first PM information includes PM data corresponding to designated time slots in the first period (col. 27, lines 5-col. 28, line 36 disclose training data collected from different source over observation period), wherein the method comprises: comparing a PM value of each time slot which is acquired based on the PM data with a target PM value, and determining a time slot of a second period in which the second load balance parameter is applied to configuration of a base station, based on a result of comparison (col. 14, lines 30-64 disclose Optimization manager 514 then determines, adapts, or modifies recommended load distribution parameters 622 for the sector 202 based on the target number of users per cell 401-402 (step 712). The recommended load distribution parameters 622 may include percentage values, percentage weights, or some other values or indicators used for load management. The recommended load distribution parameters 622 may also include a target number of users per cell, a traffic split, or other information. Load distribution parameters may be initially assigned for a sector 202, and may be adapted or adjusted with each optimization iteration. Thus, in determining the recommended load distribution parameters 622, optimization manager 514 may adjust or adapt load distribution parameters initially assigned to the sector 202 (such as for the first iteration), or adapt the load distribution parameters from a prior optimization iteration).
The limitations of claim 16 are rejected in the analysis of claim 1 above, and the claim
is rejected on that basis.
The limitations of claim 17 are rejected in the analysis of claim 2 above, and the claim
is rejected on that basis.
The limitations of claim 18 are rejected in the analysis of claim 3 above, and the claim
is rejected on that basis.
The limitations of claim 19 are rejected in the analysis of claim 1 above, and the claim
is rejected on that basis.
The limitations of claim 20 are rejected in the analysis of claim 2 above, and the claim
is rejected on that basis.
Allowable Subject Matter
Claims 8-11 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHEIKH T NDIAYE whose telephone number is (571)270-3914. The examiner can normally be reached Monday-Friday 8:00am-5:30pm.
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/CHEIKH T NDIAYE/Primary Examiner, Art Unit 2447
3/21/2026
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