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 instant office action is in response to communication filed on 04/18/2024.
Claims 1-20 are pending of which claims 1, 9, and 17 are independent.
Examiner approached on 05/26/26 Applicant’s representative, David Sumy, to consider compact prosecution by amending the independent claims 1, 9, and 17 with objected claims 2, 10, and 18 and consequently make the application attain allowance. On 05/29/2026 communicated to the examiner that the Applicant preferred to receive an office action and hence the instant office action is prepared for Applicant’s consideration.
Internet Communications
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Claim Rejections - 35 USC § 102
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 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)(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.
Claim(s) 1, 6-9, and 14-17 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rushton et al (US 20220007209 A1).
Regarding claim 1, Rushton discloses a method (See Figs. 1-6 and in particular to Fig. 6) comprising:
generating, by a device (i.e. Fig. 1 Network Device 110) , geo-bins associated (Fig. 2E shows the geo-bins for RAN devices in access network 130 shown in Figs 1&2A and paragraphs 25 and 41 detailing access network 130 has RAN devices) with a radio coverage area of a radio access network (RAN) (Per Fig. 6 step 605 wherein the network device 110 receives network information and map information with a radio coverage area of a radio access network (RAN) of access network 130 and then generates associated geo-bins shown in Fig. 2E in step 610 of Fig. 6 – see paragraphs 41 and 68-69) ;
selecting, by the device, one or more performance metrics of at least one of a RAN device or end devices associated with the geo-bins; (See paragraph 38 declaring the network device calculate performance metrics for each geo-bin by selecting from performance metrics comprising packet drop rates, latency, error rate, throughput etc… See also Fig. 2B in relation to paragraph 37)
calculating, by the device, a weighting value for each of the geo-bins based on the one or more performance metrics; (See paragraph 39 and Fig. 2C for each geo-bin a weighting value T time value is calculated using equation 1 based performance value 230 being throughput and data volume value DV. The weighing time value T indicates the length of time the resources of the RAN device associated with the geo-bin are engaged. And in paragraph 40 first sentence states “Referring to FIG. 2D, network device 110 may generate time value information for each geo-bin 235. Network device 110 may calculate a summation of the time values attributable to end devices 140 of relevance for each geo-bin.” Rate of Investment (ROI) based on data volume DV is determined for each geo-bin per table 1 and Fig. 3C and paragraph 45. See also Fig. 6 step 615 )
calculating, by the device based on the weighting values of the geo-bins, an apportionment value of a RAN device metric of the RAN device (i.e. per paragraph 47 an apportionment value for each geo-bin is based on time value info and ROI value having different weights and is the apportionment value of the RAN device to be placed in the geo-bin) , for each of the geo-bins (See paragraphs 47-48 and 52-54 where the selected geo-bins with low T values and high ROI end up receiving the selection of RAN devices, the number of RAN devices, a budget, the size of the geographic area subject to the new RF design, a coverage target of a geographic area as detailed in paragraph 48); and
generating, by the device, a RAN plan (i.e. Fig. 4C the RF design information output 420 is the RAN plan ) of a new RAN device based on the geo-bins that include the apportionment values. (i.e. Fig. 4C the output RF design being the new RAN plan, the design output indicates a new RAN for the geo-bins with apportionment value of weighted time T and weighted ROI for each geo-bin results in a new RAN per paragraph 53 stating “…As an example, different carrier nodes (e.g., low coverage/power nodes, small cell nodes (e.g., picocell, femtocell, relay nodes, etc.), iDAS, oDAS, 5G UWB nodes, CBRS nodes, LAA nodes, C-band nodes, etc.), may be optimally placed to off-load usage associated with the selected geo-bins and existing RAN device (e.g., eNB, etc.) and perhaps reduce usage for neighboring geo-bins and associated RAN device(s). The optimization may be based on the time value information associated with geo-bins and the RF design. For example, the optimization may include generating estimated time values and/or ROI values for selected geo-bins.” See paragraphs 47-48 and 52-54)
Regarding claim 9, Rushton discloses a device (i.e. Fig. 1 Network Device 110) comprising: a processor (Fig. 5 Processor 510) configured to:
generate geo-bins associated (Fig. 2E shows the geo-bins for RAN devices in access network 130 shown in Figs 1&2A and paragraphs 25 and 41 detailing access network 130 has RAN devices) with a radio coverage area of a radio access network (RAN) (Per Fig. 6 step 605 wherein the network device 110 receives network information and map information with a radio coverage area of a radio access network (RAN) of access network 130 and then generates associated geo-bins shown in Fig. 2E in step 610 of Fig. 6 – see paragraphs 41 and 68-69) ;
select one or more performance metrics of at least one of a RAN device or end devices associated with the geo-bins; (See paragraph 38 declaring the network device calculate performance metrics for each geo-bin by selecting from performance metrics comprising packet drop rates, latency, error rate, throughput etc… See also Fig. 2B in relation to paragraph 37)
calculate, a weighting value for each of the geo-bins based on the one or more performance metrics; (See paragraph 39 and Fig. 2C for each geo-bin a weighting value T time value is calculated using equation 1 based performance value 230 being throughput and data volume value DV. The weighing time value T indicates the length of time the resources of the RAN device associated with the geo-bin are engaged. And in paragraph 40 first sentence states “Referring to FIG. 2D, network device 110 may generate time value information for each geo-bin 235. Network device 110 may calculate a summation of the time values attributable to end devices 140 of relevance for each geo-bin.” Rate of Investment (ROI) based on data volume DV is determined for each geo-bin per table 1 and Fig. 3C and paragraph 45. See also Fig. 6 step 615 )
calculate, based on the weighting values of the geo-bins, an apportionment value of a RAN device metric of the RAN device (i.e. per paragraph 47 an apportionment value for each geo-bin is based on time value info and ROI value having different weights and is the apportionment value of the RAN device to be placed in the geo-bin) , for each of the geo-bins (See paragraphs 47-48 and 52-54 where the selected geo-bins with low T values and high ROI end up receiving the selection of RAN devices, the number of RAN devices, a budget, the size of the geographic area subject to the new RF design, a coverage target of a geographic area as detailed in paragraph 48); and
generate, by the device, a RAN plan (i.e. Fig. 4C the RF design information output 420 is the RAN plan ) of a new RAN device based on the geo-bins that include the apportionment values. (i.e. Fig. 4C the output RF design being the new RAN plan, the design output indicates a new RAN for the geo-bins with apportionment value of weighted time T and weighted ROI for each geo-bin results in a new RAN per paragraph 53 stating “…As an example, different carrier nodes (e.g., low coverage/power nodes, small cell nodes (e.g., picocell, femtocell, relay nodes, etc.), iDAS, oDAS, 5G UWB nodes, CBRS nodes, LAA nodes, C-band nodes, etc.), may be optimally placed to off-load usage associated with the selected geo-bins and existing RAN device (e.g., eNB, etc.) and perhaps reduce usage for neighboring geo-bins and associated RAN device(s). The optimization may be based on the time value information associated with geo-bins and the RF design. For example, the optimization may include generating estimated time values and/or ROI values for selected geo-bins.” See paragraphs 47-48 and 52-54)
Regarding claim 17, Rushton discloses a non-transitory computer-readable storage medium storing instructions executable by a processor of a device (Network Device 110 with components shown in Fig. 5 as processor 510 and non-transitory computer readable storage 515 and in instruction 520), wherein the instructions are configured to:
generate geo-bins associated (Fig. 2E shows the geo-bins for RAN devices in access network 130 shown in Figs 1&2A and paragraphs 25 and 41 detailing access network 130 has RAN devices) with a radio coverage area of a radio access network (RAN) (Per Fig. 6 step 605 wherein the network device 110 receives network information and map information with a radio coverage area of a radio access network (RAN) of access network 130 and then generates associated geo-bins shown in Fig. 2E in step 610 of Fig. 6 – see paragraphs 41 and 68-69) ;
select one or more performance metrics of at least one of a RAN device or end devices associated with the geo-bins; (See paragraph 38 declaring the network device calculate performance metrics for each geo-bin by selecting from performance metrics comprising packet drop rates, latency, error rate, throughput etc… See also Fig. 2B in relation to paragraph 37)
calculate, a weighting value for each of the geo-bins based on the one or more performance metrics; (See paragraph 39 and Fig. 2C for each geo-bin a weighting value T time value is calculated using equation 1 based performance value 230 being throughput and data volume value DV. The weighing time value T indicates the length of time the resources of the RAN device associated with the geo-bin are engaged. And in paragraph 40 first sentence states “Referring to FIG. 2D, network device 110 may generate time value information for each geo-bin 235. Network device 110 may calculate a summation of the time values attributable to end devices 140 of relevance for each geo-bin.” Rate of Investment (ROI) based on data volume DV is determined for each geo-bin per table 1 and Fig. 3C and paragraph 45. See also Fig. 6 step 615 )
calculate, based on the weighting values of the geo-bins, an apportionment value of a RAN device metric of the RAN device (i.e. per paragraph 47 an apportionment value for each geo-bin is based on time value info and ROI value having different weights and is the apportionment value of the RAN device to be placed in the geo-bin) , for each of the geo-bins (See paragraphs 47-48 and 52-54 where the selected geo-bins with low T values and high ROI end up receiving the selection of RAN devices, the number of RAN devices, a budget, the size of the geographic area subject to the new RF design, a coverage target of a geographic area as detailed in paragraph 48); and
generate, by the device, a RAN plan (i.e. Fig. 4C the RF design information output 420 is the RAN plan ) of a new RAN device based on the geo-bins that include the apportionment values. (i.e. Fig. 4C the output RF design being the new RAN plan, the design output indicates a new RAN for the geo-bins with apportionment value of weighted time T and weighted ROI for each geo-bin results in a new RAN per paragraph 53 stating “…As an example, different carrier nodes (e.g., low coverage/power nodes, small cell nodes (e.g., picocell, femtocell, relay nodes, etc.), iDAS, oDAS, 5G UWB nodes, CBRS nodes, LAA nodes, C-band nodes, etc.), may be optimally placed to off-load usage associated with the selected geo-bins and existing RAN device (e.g., eNB, etc.) and perhaps reduce usage for neighboring geo-bins and associated RAN device(s). The optimization may be based on the time value information associated with geo-bins and the RF design. For example, the optimization may include generating estimated time values and/or ROI values for selected geo-bins.” See paragraphs 47-48 and 52-54)
Regarding claim 6, Rushton discloses the method of claim 1, wherein the selecting comprises: selecting, by the device, the one or more performance metrics based on a causal or a correlative relationship with the RAN device metric. (See paragraphs 24 and 38-39 wherein the performance metric has a casual or a correlative relationship with the RAN metric device. In paragraph the throughput and data volume performance metric is related to the length of time the resources of the RAN device associated with the geo-bins are engaged per paragraph 39)
Regarding claim 7, Rushton discloses the method of claim 1, wherein the RAN device metric relates to dropped calls, wait time, network resource utilization of the RAN device. (In paragraph the throughput and data volume performance metric is related to the length of time the resources of the RAN device associated with the geo-bins are engaged per paragraph 39)
Regarding claim 8, Rushton discloses the method of claim 1, wherein the one or more performance metrics relate to at least one of throughput, latency or packet error rate. ( See paragraph 38 on being one of throughput, latency, error rate or even another QoS parameter. See also paragraph 39.).
Regarding claim 14, claim 14 is rejected in the same scope as claim 6.
Regarding claim 15, claim 15 is rejected in the same scope as claim 7.
Regarding claim 16, claim 16 is rejected in the same scope as claim 8.
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.
The factual inquiries for establishing a background for determining obviousness under 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.
Claim(s) 3, 4, 5, 11,12, 13, 19 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rushton in view of Kanza et al (US 2022/0377570 A1)
Regarding claim 3, Rushton discloses the method of claim 1, but fails to disclose further comprising generating, by the device based on an antenna design of an existing RAN device that matches a density value associated with the new RAN device, an antenna design of the new RAN device.
Kanza, in the same endeavor, discloses generating, by the device based on an antenna design of an existing RAN device that matches a density value associated with the new RAN device, an antenna design of the new RAN device. (See Fig. 2D step 222d indicates as planning a new RAN device by still keeping the same density of antennas of existing RAN device and adding an additional antenna. See Paragraphs 25 and 54-56.)
In view of the above, having Rushton’s node placement service and then given the well- established teaching of Kanza’s techniques for RAN planning based on antenna density, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made to modify Rushton’s node placement service as taught by Kanza’s techniques for RAN planning based on antenna density, since Kanza states in paragraph 60 that the modification makes RAN planning much more efficient.
Regarding claim 11, claim 11 is rejected in the same scope as claim 3.
Regarding claim 19, claim 19 is rejected in the same scope as claim 3.
Regarding claim 4, Rushton discloses the method of claim 1, but fails to disclose
calculating, by the device, a first radio frequency (RF) propagation modeling of the RAN device; and calculating, by the device based on the first RF propagation modeling, a second RF propagation modeling for the new RAN device.
Kanza, in the same endeavor, discloses calculating, by the device, a first radio frequency (RF) propagation modeling of the RAN device; and calculating, by the device based on the first RF propagation modeling, a second RF propagation modeling for the new RAN device.(In paragraphs 31, 34, 40, and 46 it is disclosed using more than one propagation models for the new RAN device. In paragraph 31 it is explicitly stated “…Different propagation models can be used, e.g., signal strength that decays as the distance from the antenna grows (SINR), radio waves that can go through obstacles, with some decay, reflection of transmissions from obstacles, diffraction, etc.”. And in paragraph 15 it is explicitly stated “…For example, system 100 can facilitate in whole or in part selecting equipment locations such as of cellular antennas, based on a combination of a grid geospatial representation of a planning area and optimization algorithms (which can be combined with propagation models and a 3D model of the world) where the optimization algorithm can select a deployment from a large space of options and would make RAN planning much more efficient.”)
In view of the above, having Rushton’s node placement service and then given the well- established teaching of Kanza’s techniques for RAN planning based on propagation models, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made to modify Rushton’s node placement service as taught by Kanza’s techniques for RAN planning based on propagation model, since Kanza states in paragraph 60 that the modification makes RAN planning much more efficient.
Regarding claim 12, claim 12 is rejected in the same scope as claim 4.
Regarding claim 20, claim 20 is rejected in the same scope as claim 4.
Regarding claim 5, Rushton discloses the method of claim 1, but fails to disclose
by the device, one or more objective criteria; iteratively calculating, by the device, first geo-bins of the geo-bins, wherein the first geo- bins satisfy the one or more objective criteria and are candidate locations for new RAN devices; and ranking, by the device, the first geo-bins based on an optimization of the one or more objective criteria.
Kanza, in the same endeavor, receiving, by the device (Fig. 1 Network Elements (NE)), one or more objective criteria (Fig. 2D steps 202d and 214d Network Element receives objective criteria to meet objective function …paragraph 52); iteratively calculating (See Method in Fig. 2d steps 210d, 214d, and 222d can be repeated iteratively – see paragraph 56), by the device, first geo-bins of the geo-bins, wherein the first geo- bins satisfy the one or more objective criteria and are candidate locations for new RAN devices(Step 210d and step 222d of Fig. 2D identifies Grids/cells/geo-bins satisfies new location where new RAN devices in the form of additional antennas (see paragraphs 50-56) ); and ranking, by the device, the first geo-bins based on an optimization of the one or more objective criteria. (See paragraphs 38 and 107 on ranking)
In view of the above, having Rushton’s node placement service and then given the well- established teaching of Kanza’s techniques for RAN planning based on iterative calculations, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made to modify Rushton’s node placement service as taught by Kanza’s techniques for RAN planning based on iterative calculation, since Kanza states in paragraph 60 that the modification makes RAN planning much more efficient.
Allowable Subject Matter
Claims 2, 10, and 18 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.
The following is a statement of reasons for the indication of allowable subject matter: The prior art of record fails to teach individually or in combination the limitation reciting “..calculating, by the device, a ratio value between a first apportionment value associated with a first geo-bin of the geo-bins and a second apportionment value associated with a summation of the apportionment values of the geo-bins.” In combination with the limitations of the independent claims 1, 9, and 17 respectively.
The closest prior art is WO 2015/120696 to Sheng et al and teaches the following while failing the above recited limitation:
Sheng discloses data apportion method.. The method comprises the steps of determining the apportion dimensionality of each record in apportion cardinal numbers and the apportion dimensionality of each record in apportion objects according to names of the apportion dimensionality input by a user, which comprises names of target dimensionality and numerical dimensionality; obtaining the apportion proportion dimensionality of each record in the apportion cardinal numbers, and distributing each record in the apportion objects into a plurality of records according to all the records in the apportion cardinal numbers, wherein the data in the apportion proportion dimensionality of each record in the apportion cardinal numbers is an apportion proportion value of the sum of data in the numerical dimensionality in all the records to each record in the apportion cardinal numbers, and the data in the target dimensionality in each record in the apportion objects is distributed to data of the target dimensionality in each record in the apportion cardinal numbers. Accordingly, the apportion flexibility ratio is increased, the apportion complexity is reduced, and the apportion method code maintenance cost is reduced.
Conclusion
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/HABTE MERED/Primary Examiner, Art Unit 2474
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