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 .
Claim Objections
Claims 5, 12, and 15-20 are objected to because of the following informalities:
Regarding claim 5, on line 2, it appears that the word “by” is missing after the word “collected”.
Regarding claim 12, on line 2, it appears that the word “by” is missing after the word “collected”.
Regarding claim 15, on line 1, it appears that the word “has” should instead be “having”.
Regarding claim 19, on line 2, it appears that the word “by” is missing after the word “collected”.
Claims 16-20 are also objected to as being dependent on claim 15 and containing the same deficiency.
Appropriate correction is required.
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, 4-8, 11-15, and 18-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Halabian et al. (U.S. 2019/0320332) (hereinafter “Halabian”). Halabian teaches all of the limitations of the specified claims with the reasoning that follows.
Regarding claim 1, “a system comprising: a processor; and a memory comprising computer program code, the memory and the computer program code configured to cause the processor to: obtain configuration data and location data from a plurality of wireless access points (WAPs)” as well as “determine a first WAP of the plurality of WAPs and a second WAP of the plurality of WAPs are neighbor WAPs using the configuration data and the location data, wherein the neighbor WAPs have overlapping signal coverage areas” as well as “receive network data from the first WAP and from the second WAP” is anticipated by the Self-Organizing Network (SON) manager 2 (system) of Figure 1 that collects (receives, obtains) network data from network access points (APs) which are required to run radio resource management (RRM) optimization algorithms, where the network data includes RF scan reports from the APs (WAPs), traffic load statistics, channel utilization statistics, AP static configuration parameters (configuration data), etc. as spoken of on page 4, paragraph [0067]; where the RF scan reports are used by the APs to identify (determine) the neighboring APs (location data) on all the channels as spoken of on page 3, paragraph [0037]; and where the SON manager node 2 of Figure 4 includes a processor 36 coupled to a memory 34 storing the RF scan data 38.
Lastly, “generate network resource allocation instructions for the first WAP and for the second WAP using a network optimization model, the received network data, and the obtained configuration data; and distribute the generated network resource allocation instructions to the first WAP and to the second WAP, whereby the first WAP and the second WAP are instructed to operate in ways that do not interfere with each other” is anticipated by the SON manager node 2 that, in response to receiving the RF scan data from the APs, creates network segments of limited sizes based on the RF scan data, and executes a RRM optimization algorithm (network optimization model) in an RRM time slot in each of successive RRM periods as shown in steps 5100, 5102, 5104 of Figure 6 and spoken of on page 5, paragraph [0078]; where after running optimization algorithms the optimal RRM configuration parameters (generated network resource allocation instructions) are sent (distributed) from the SON manager to the APs (first, second WAP) as spoken of on page 4, paragraph [0068]; and where the network segments are formed such that they have minimum RF impact (do not interfere with) on each other as spoken of on page 3, paragraph [0037].
Regarding claim 4, “wherein the generated network resource allocation instructions include instructions for the first WAP to use a first frequency range and instructions for the second WAP to use a second frequency range, wherein the first frequency range and the second frequency range do not interfere with each other” is anticipated by the SON manager 2 that includes a slicer algorithm that uses received RF scan reports to create network segments of limited sizes (frequency ranges), where the segments are formed such that they have minimum RF impact (frequency ranges do not interfere with) on each other as spoken of on page 3, paragraph [0037]; and where optimal RRM configuration parameters are sent to the APs such that the APs can update their parameters as spoken of on page 4, paragraph [0068].
Regarding claim 5, “wherein the received network data includes at least one of throughput data, interference data, or noise data collected a first user equipment (UE) device communicating with the first WAP and a second UE device communicating with the second WAP” is anticipated by the collected network data that includes RF scan reports from the APs (WAPs), traffic load statistics (throughput data), channel utilization statistics, AP static configuration parameters, etc. as spoken of on page 4, paragraph [0067].
Regarding claim 6, “route data to a plurality of UE devices via the first WAP and the second WAP as a combined wireless network” is anticipated by the APs that are responsible for distribution of Internet access (route data) to wireless user devices (UE devices) as spoken of on page 1, paragraph [0002].
Regarding claim 7, “train the network optimization model using machine learning techniques to improve throughput of the plurality of WAPs operating as a combined wireless network” is anticipated by the SON manager that utilizes an RRM solution that operates based on network learning principles (machine learning techniques) and optimizes the network by using the latest RF survey data as well as network performance statistics collected from the network as spoken of on page 3, paragraphs [0040]-[0042].
Regarding claim 8, “a computerized method comprising: obtaining configuration data and location data from a plurality of wireless access points (WAPs); determining a first WAP of the plurality of WAPs and a second WAP of the plurality of WAPs are neighbor WAPs using the configuration data and the location data, wherein the neighbor WAPs have overlapping signal coverage areas; receiving network data from the first WAP and from the second WAP” is anticipated by the Self-Organizing Network (SON) manager 2 of Figure 1 that collects (receives, obtains) network data from network access points (APs) which are required to run radio resource management (RRM) optimization algorithms, where the network data includes RF scan reports from the APs (WAPs), traffic load statistics, channel utilization statistics, AP static configuration parameters (configuration data), etc. as spoken of on page 4, paragraph [0067]; and where the RF scan reports are used by the APs to identify (determine) the neighboring APs (location data) on all the channels as spoken of on page 3, paragraph [0037].
Lastly, “generating network resource allocation instructions for the first WAP and for the second WAP using a network optimization model, the received network data, and the obtained configuration data; and distributing the generated network resource allocation instructions to the first WAP and to the second WAP, whereby the first WAP and the second WAP are instructed to operate in ways that do not interfere with each other” is anticipated by the SON manager node 2 that, in response to receiving the RF scan data from the APs, creates network segments of limited sizes based on the RF scan data, and executes a RRM optimization algorithm (network optimization model) in an RRM time slot in each of successive RRM periods as shown in steps 5100, 5102, 5104 of Figure 6 and spoken of on page 5, paragraph [0078]; where after running optimization algorithms the optimal RRM configuration parameters (generated network resource allocation instructions) are sent (distributed) from the SON manager to the APs (first, second WAP) as spoken of on page 4, paragraph [0068]; and where the network segments are formed such that they have minimum RF impact (do not interfere with) on each other as spoken of on page 3, paragraph [0037].
Regarding claim 11, “wherein the generated network resource allocation instructions include instructions for the first WAP to use a first frequency range and instructions for the second WAP to use a second frequency range, wherein the first frequency range and the second frequency range do not interfere with each other” is anticipated by the SON manager 2 that includes a slicer algorithm that uses received RF scan reports to create network segments of limited sizes (frequency ranges), where the segments are formed such that they have minimum RF impact (frequency ranges do not interfere with) on each other as spoken of on page 3, paragraph [0037]; and where optimal RRM configuration parameters are sent to the APs such that the APs can update their parameters as spoken of on page 4, paragraph [0068].
Regarding claim 12, “wherein the received network data includes at least one of throughput data, interference data, or noise data collected a first user equipment (UE) device communicating with the first WAP and a second UE device communicating with the second WAP” is anticipated by the collected network data that includes RF scan reports from the APs (WAPs), traffic load statistics (throughput data), channel utilization statistics, AP static configuration parameters, etc. as spoken of on page 4, paragraph [0067].
Regarding claim 13, “routing data to a plurality of UE devices via the first WAP and the second WAP as a combined wireless network” is anticipated by the APs that are responsible for distribution of Internet access (route data) to wireless user devices (UE devices) as spoken of on page 1, paragraph [0002].
Regarding claim 14, “training the network optimization model using machine learning techniques to improve throughput of the plurality of WAPs operating as a combined wireless network” is anticipated by the SON manager that utilizes an RRM solution that operates based on network learning principles (machine learning techniques) and optimizes the network by using the latest RF survey data as well as network performance statistics collected from the network as spoken of on page 3, paragraphs [0040]-[0042].
Regarding claim 15, “a computer storage medium has computer-executable instructions that, upon execution by a processor, cause the processor to at least: obtain configuration data and location data from a plurality of wireless access points (WAPs); determine a first WAP of the plurality of WAPs and a second WAP of the plurality of WAPs are neighbor WAPs using the configuration data and the location data, wherein the neighbor WAPs have overlapping signal coverage areas; receive network data from the first WAP and from the second WAP” is anticipated by the Self-Organizing Network (SON) manager 2 (system) of Figure 1 that collects (receives, obtains) network data from network access points (APs) which are required to run radio resource management (RRM) optimization algorithms, where the network data includes RF scan reports from the APs (WAPs), traffic load statistics, channel utilization statistics, AP static configuration parameters (configuration data), etc. as spoken of on page 4, paragraph [0067]; where the RF scan reports are used by the APs to identify (determine) the neighboring APs (location data) on all the channels as spoken of on page 3, paragraph [0037]; where the SON manager node 2 of Figure 4 includes a processor 36 coupled to a memory 34 storing the RF scan data 38; and where a computer readable storage medium including computer program code may be utilized as spoken of on page 7, paragraph [0110].
Lastly, “generate network resource allocation instructions for the first WAP and for the second WAP using a network optimization model, the received network data, and the obtained configuration data; and distribute the generated network resource allocation instructions to the first WAP and to the second WAP, whereby the first WAP and the second WAP are instructed to operate in ways that do not interfere with each other” is anticipated by the SON manager node 2 that, in response to receiving the RF scan data from the APs, creates network segments of limited sizes based on the RF scan data, and executes a RRM optimization algorithm (network optimization model) in an RRM time slot in each of successive RRM periods as shown in steps 5100, 5102, 5104 of Figure 6 and spoken of on page 5, paragraph [0078]; where after running optimization algorithms the optimal RRM configuration parameters (generated network resource allocation instructions) are sent (distributed) from the SON manager to the APs (first, second WAP) as spoken of on page 4, paragraph [0068]; and where the network segments are formed such that they have minimum RF impact (do not interfere with) on each other as spoken of on page 3, paragraph [0037].
Regarding claim 18, “wherein the generated network resource allocation instructions include instructions for the first WAP to use a first frequency range and instructions for the second WAP to use a second frequency range, wherein the first frequency range and the second frequency range do not interfere with each other” is anticipated by the SON manager 2 that includes a slicer algorithm that uses received RF scan reports to create network segments of limited sizes (frequency ranges), where the segments are formed such that they have minimum RF impact (frequency ranges do not interfere with) on each other as spoken of on page 3, paragraph [0037]; and where optimal RRM configuration parameters are sent to the APs such that the APs can update their parameters as spoken of on page 4, paragraph [0068].
Regarding claim 19, “wherein the received network data includes at least one of throughput data, interference data, or noise data collected a first user equipment (UE) device communicating with the first WAP and a second UE device communicating with the second WAP” is anticipated by the collected network data that includes RF scan reports from the APs (WAPs), traffic load statistics (throughput data), channel utilization statistics, AP static configuration parameters, etc. as spoken of on page 4, paragraph [0067].
Regarding claim 20, “route data to a plurality of UE devices via the first WAP and the second WAP as a combined wireless network” is anticipated by the APs that are responsible for distribution of Internet access (route data) to wireless user devices (UE devices) as spoken of on page 1, paragraph [0002].
Allowable Subject Matter
Claims 2, 3, 9, 10, 16, and 17 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. References considered relevant to this application are listed in the attached “Notice of References Cited” (PTO-892).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J. MOORE, JR., whose telephone number is (571)272-3168. The examiner can normally be reached M-F (9am-4pm).
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/MICHAEL J MOORE JR/Primary Examiner, Art Unit 2467