Prosecution Insights
Last updated: April 19, 2026
Application No. 18/685,709

METHODS AND APPARATUS FOR DETERMINING ABOVE GROUND COVERAGE OF A MOBILE TELECOMMUNICATIONS NETWORK

Non-Final OA §101
Filed
Feb 22, 2024
Examiner
MITCHELL, NATHAN A
Art Unit
3627
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Vodafone Group Services Limited
OA Round
1 (Non-Final)
73%
Grant Probability
Favorable
1-2
OA Rounds
2y 9m
To Grant
83%
With Interview

Examiner Intelligence

Grants 73% — above average
73%
Career Allow Rate
689 granted / 940 resolved
+21.3% vs TC avg
Moderate +10% lift
Without
With
+10.1%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
36 currently pending
Career history
976
Total Applications
across all art units

Statute-Specific Performance

§101
16.4%
-23.6% vs TC avg
§103
44.3%
+4.3% vs TC avg
§102
19.9%
-20.1% vs TC avg
§112
11.2%
-28.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 940 resolved cases

Office Action

§101
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 Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-22 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. All claims recite subject matter falling within one of the four categories of invention (step 1). Exemplary claims 1-10 recite: 1. (Original) A computer implemented method of determining above ground coverage of a mobile telecommunications network, the method comprising:receiving data representative of coverage of the mobile telecommunications network at a plurality of ground based locations; identifying a location above ground for which coverage of the mobile telecommunications network is to be determined; selecting a subset of the data representative of coverage at the plurality of ground based locations, wherein the subset comprises data representative of coverage of the mobile telecommunications network at a subset of the ground based locations and wherein selecting the subset comprises selecting the subset of the ground based locations in dependence on their location relative to the identified location above ground; providing a property of the identified location above ground and the selected subset of data representative of coverage at ground based locations as inputs to a prediction model, configured through training, to determine coverage of a mobile telecommunications network at locations above ground in dependence on data representative of coverage of the mobile telecommunications network at one or more ground based locations; and implementing the prediction model to generate an output in dependence on the provided inputs, wherein the output of the model is representative of the coverage of the mobile telecommunications network at the identified location above ground. 2. (Original) The method of claim 1, wherein selecting the subset of the ground based locations in dependence on their location relative to the identified location above ground comprises: selecting a subset of N ground based locations which are the N closest of the plurality of ground based locations to the identified location above ground, wherein N is an integer equal to or greater than 1. 3. (Currently Amended) The method of claim 1, wherein selecting the subset of the ground based locations in dependence on their location relative to the identified location above ground comprises: selecting all of the ground based locations which are positioned within a distance threshold of the identified location above ground. 4. (Currently Amended) The method of claim 1, wherein the data representative of coverage of the mobile telecommunications network at a plurality of ground based locations is based on measurements indicative of coverage of the mobile telecommunications made at a plurality of ground based locations. 5. (Currently Amended) The method of claim 1, wherein the prediction model is configured through supervised training using a plurality of training data records, the plurality of training data records being derived from measurements indicative of the coverage of a mobile telecommunications made at both ground based and above ground locations. 6. (Currently Amended) The method of claim 1, wherein the selected subset of data representative of coverage at the subset of ground based locations comprises at least one of a received signal power, a received signal quality and a timing advance at each of the subset of the ground based locations. 7. (Currently Amended) The method of claim 1, wherein the selected subset of data representative of coverage at the plurality of ground based locations comprises data representative of network coverage provided by a serving cell at each of the subset of the ground based locations. 8. (Currently Amended) The method of claim 1, wherein the selected subset of data representative of coverage at the subset of ground based locations comprises data representative of network coverage provided by a plurality of cells at each of the subset of the ground based locations. 9. (Currently Amended) The method of claim 1,further comprising providing at least one further input to the prediction model, wherein the at least one further input is based on the geographical position of the identified location above ground and/or the geographical positions of the selected subset of the ground based locations. 10. (Currently Amended) The method of claim 1,further comprising performing feature engineering based on the selected subset of data representative of coverage at ground based locations to determine at least one further input to the prediction model. But for the recitation of the underlined and bolded elements, claims 1-10 recites a judicial exception. The identifying and selecting steps of claim 1 (further refined by dependent claims) under the broadest reasonable interpretation encompass mental observations and/or evaluations that are practically performed in the human mind. The providing step and subsequent dependent claims illustrate subject matter that under the broadest reasonable interpretation encompass mathematical calculations. Training a machine learning model is known to be done by making mathematical calculations (see spec paragraph 168). Based on the above, claims 1-10 recite an abstract idea (step 2A_1). The additional elements comprise 1) computer implementation 2) data gathering/output (bolded) 3) model application The computer implementation and model application provide nothing more than mere instructions to implement an abstract idea, which per MPEP 2106.05(f) means they do not provide a practical application or significantly more. Regarding the data gathering/output, all uses of the recited judicial exceptions require such data gathering and output, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and outputting and per MPEP 2106.05(g) are insignificant extra-solution activity that does not provide a practical application or significantly more. Data gathering/output is also regarded as conventional per MPEP 2106.05(d) (see OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93 regarding data output and Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) regarding receiving data)and therefore additional not significantly more per step 2B. Thus claims 1-10 are directed to an abstract idea without a practical application or significantly more (Step 2A_2 and Step 2B) and are ineligible. Claims 11-22 contain similar limitations to claims 1-10 and are considered ineligible for substantially the same reasons. Also the examiner brings attention to subject matter eligibility materials at https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf Instant claims are considered to be similar to claim Example 47 claim 2. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Swift (US 20040110518 A1) discloses a 3D interference model being generated based on ground and above ground measurements. Murphy (US 20180293897 A1) discloses generating a coverage model based on base station and environmental data. Neubauer (US 11763683 B2) discloses generating a 3D model based on measurements. Ma (US 12356209 B2) discloses coverage prediction using machine learning. None of the cited art discloses claims 1-22. Any inquiry concerning this communication or earlier communications from the examiner should be directed to NATHAN A MITCHELL whose telephone number is (571)270-3117. The examiner can normally be reached M-F 9-5. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan Zeender can be reached at 571-272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /NATHAN A MITCHELL/Primary Examiner, Art Unit 3627
Read full office action

Prosecution Timeline

Feb 22, 2024
Application Filed
Feb 06, 2026
Non-Final Rejection — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
73%
Grant Probability
83%
With Interview (+10.1%)
2y 9m
Median Time to Grant
Low
PTA Risk
Based on 940 resolved cases by this examiner. Grant probability derived from career allow rate.

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