Prosecution Insights
Last updated: April 18, 2026
Application No. 18/558,663

LANDSCAPE SENSING USING RADIO SIGNALS

Non-Final OA §103
Filed
Nov 02, 2023
Examiner
TROST IV, WILLIAM GEORGE
Art Unit
2641
Tech Center
2600 — Communications
Assignee
Telefonaktiebolaget Lm Ericsson (Publ)
OA Round
1 (Non-Final)
63%
Grant Probability
Moderate
1-2
OA Rounds
2y 9m
To Grant
28%
With Interview

Examiner Intelligence

Grants 63% of resolved cases
63%
Career Allow Rate
17 granted / 27 resolved
+1.0% vs TC avg
Minimal -35% lift
Without
With
+-35.4%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
27 currently pending
Career history
54
Total Applications
across all art units

Statute-Specific Performance

§101
3.5%
-36.5% vs TC avg
§103
60.4%
+20.4% vs TC avg
§102
26.4%
-13.6% vs TC avg
§112
7.6%
-32.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 27 resolved cases

Office Action

§103
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. Priority Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Claim Rejections - 35 USC § 103 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. Claim s FILLIN "Insert the claim numbers which are under rejection." \d "[ 1 ]" 1- 9, and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over FILLIN "Insert the prior art relied upon." \d "[ 2 ]" Peroulas (2019/0268779) in view of Chakraborty (WO 2020/234902) . Regarding claim s 1 and 14 , Peroulas discloses a method performed by a bases station for determining landscape type surrounding a user equipment UE being served by the base station (Figure 1) comprising: obtaining measurements related to a path-gain between the UE and a plurality of base stations including the service base station (Step 502) and determining a map based on the obtained measurements and a classification model (steps 506, 508 using a neural network model and the observations to generate an observation /coverage map). Peroulas fails to explicitly disclose that the measurements are related to determining a landscape type but does disclose the use of terrain maps (para 49) Chakraborty teaches in an analogous art, the use of machine learning and wireless measurements between a base station and UE (Figure 4) where the measurements are used to determine a landscape type (para 112-114, use of machine learning to define optimal predictions for terrain). Therefore, it would have been obvious to one of ordinary skill in the art before the effective date of the invention to include landscape derivation in order to provide a complete topology map to the end user. Regarding claims 2- 4 , and 15-17, Peroulas further discloses that the measurements related to the path-gain are both downlink and uplink measurements (para 36 , para 51-52, observations 130, 132, 134). Peroulas also discloses that the path-gain measurement is RSRP, para 36. Regarding claims 5-6 , and 18-19 , Peroulas disclose determining the landscape type using only the N strongest measurements related to the path-gain, where N is greater than 4, (paragraphs 36 and 47 disclose that the system collects observations from multiple base stations and that the model will use as many data points as necessary – note para 48 using as many and larger observations to create a confidence interval). Chakraborty teaches the reception of data from at least 4 base stations (Figure 2). Neither explicitly discloses greater than 4 measurements, but one of ordinary skill in the art would ensure to utilize the highest number of observations to have the highest accuracy and most complete measurement data set. Regarding claims 7-8, 20, Chakraborty further teaches that the classification model is a machine learning model (machine learning module 404, para 77-81). And that the classification model is trained with a training set (Figure 10, step 1008 – training the ML model). Therefore, it would have been obvious to one of ordinary skill in the art before the effective date of the invention to include training in order to provide increase accuracy of the ML model upon receiving further data. Regarding claim 9, Peroulas discloses that the classification model comprises at least one from the group consisting of a neural network (para 56). Claim s FILLIN "Pluralize claim, if necessary, and then insert the claim number(s) which is/are under rejection." \d "[ 1 ]" 10 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over FILLIN "Insert the prior art reference(s) relied upon for the obviousness rejection." \d "[ 2 ]" Peroulas and Chakraborty as applied to claim FILLIN "Pluralize claim, if necessary, and then insert the claim number(s) which is/are under rejection." \d "[ 3 ]" 1 above, and further in view of FILLIN "Insert the additional prior art reference(s) relied upon for the obviousness rejection." \d "[ 4 ]" Sahin (9930558) . Regarding claims 10 and 13, the combination discloses that the UE does downlink measurements with respect to the path-gain between the UE and the base station ( Peroulas 36, 51-52) and taking at least one action regarding the UE based on the determined landscape type (Figure 10, 1016 – triggers to the UE to update one or more radio parameters). The combination fails to explicitly disclose that the UE is configured for periodic reporting (note the UE reports based on the received and transmitted signals which are inherently periodic in nature). However, Sahin teaches in an analogous art, a wireless measurement system in which the UE (WTRU) is configured for periodic reporting (Col 9; 35-55 and Col; 15;10-25) as well as taking actions on the UE (WTRU) based on the landscape (Col; 23;1-58 and Col 27;54-Col28;25). Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include periodic reporting in order to dynamically update the model. Claims FILLIN "Pluralize claim, if necessary, and then insert the claim number(s) which is/are under rejection." \d "[ 1 ]" 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over FILLIN "Insert the prior art reference(s) relied upon for the obviousness rejection." \d "[ 2 ]" Peroulas and Chakraborty as applied to claim FILLIN "Pluralize claim, if necessary, and then insert the claim number(s) which is/are under rejection." \d "[ 3 ]" 1 above, and further in view of FILLIN "Insert the additional prior art reference(s) relied upon for the obviousness rejection." \d "[ 4 ]" El- Sallabi (8532676) . Regarding claims 11-12, the combination discloses all the limitations except the determination if an environment is rural or urban based on the measurements. However, El- Sallabi teaches that radio measurements reported for a modeling system indicate a rural or urban environment based on measurements (Col. 14;40-Col. 15;10, outdoor coverage would show stronger measurements than indoor measurements, as well as indicative of cell size). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include analysis in order to properly categorize the landscape type based on the received measurements. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. FILLIN "Enter the appropriate information" \* MERGEFORMAT Rappaport (6499006) disclose the use of modeling wireless communications based on terrain and obstacles . Sadhu (20210068170) disclose machine learning to update directional communications based on environmental measures Abir (WO 2020/245834) disclose machine learning in a vehicular environment with training and wireless parameter inputs. Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT WILLIAM GEORGE TROST IV whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)272-7872 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT Monday-Thursday 7a-4p, Fridays 7a-2p . 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, FILLIN "SPE Name?" \* MERGEFORMAT Charles Appiah can be reached at FILLIN "SPE Phone?" \* MERGEFORMAT 571-272-7904 . 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. FILLIN "Examiner Stamp" \* MERGEFORMAT WILLIAM GEORGE TROST IV Primary Patent Examiner Art Unit 2641 /WILLIAM G TROST IV/ Primary Patent Examiner, Art Unit 2641
Read full office action

Prosecution Timeline

Nov 02, 2023
Application Filed
Dec 16, 2025
Non-Final Rejection — §103
Mar 20, 2026
Response Filed

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12574720
METHOD AND SYSTEM FOR END DEVICE CONFIGURATION BASED ON SUBSCRIBER ATTRIBUTES AND AVAILABILITY
2y 5m to grant Granted Mar 10, 2026
Patent 12477509
WIRELESS COMMUNICATION SYSTEM, REPEATER, AND WIRELESS COMMUNICATIONMETHOD
2y 5m to grant Granted Nov 18, 2025
Patent 12452818
Handling PLMN Prioritization
2y 5m to grant Granted Oct 21, 2025
Patent 12446080
METHODS AND SYSTEMS FOR DATA COMMUNICATION AT A PRIMARY WIRELESS COMMUNICATION APPARATUS IN CONJUNCTION WITH AN AUXILIARY WIRELESS COMMUNICATION APPARATUS
2y 5m to grant Granted Oct 14, 2025
Patent 7791481
LIGHT ACTIVATED RFID TAG
2y 5m to grant Granted Sep 07, 2010
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
63%
Grant Probability
28%
With Interview (-35.4%)
2y 9m
Median Time to Grant
Low
PTA Risk
Based on 27 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month