Prosecution Insights
Last updated: April 19, 2026
Application No. 18/057,739

MITIGATING LOSS OF CONNECTIVITY DUE TO LINE-OF-SIGHT BLOCKAGES

Non-Final OA §103
Filed
Nov 21, 2022
Examiner
THOMPSON, JR, OTIS L
Art Unit
2477
Tech Center
2400 — Computer Networks
Assignee
International Business Machines Corporation
OA Round
1 (Non-Final)
89%
Grant Probability
Favorable
1-2
OA Rounds
2y 6m
To Grant
99%
With Interview

Examiner Intelligence

Grants 89% — above average
89%
Career Allow Rate
890 granted / 1002 resolved
+30.8% vs TC avg
Moderate +10% lift
Without
With
+9.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
32 currently pending
Career history
1034
Total Applications
across all art units

Statute-Specific Performance

§101
5.8%
-34.2% vs TC avg
§103
50.2%
+10.2% vs TC avg
§102
26.2%
-13.8% vs TC avg
§112
9.0%
-31.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1002 resolved cases

Office Action

§103
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 § 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. 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) 1-3, 6 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee (WO 2021/246546, Machine Translation) in view of Laufer et al. (US 2017/0012698). Regarding claim 1, Lee discloses a computer-based method of mitigating loss of connectivity in autonomous vehicles due to line-of-sight blockage, the method comprising: automatically identifying one or more impact zones and one or more non-impact zones located within a selected region (Paragraph 366, a variety of NLOS routes [non-impact zone] or LOS routes [impact zone] can be provided for the first vehicle (1601) to communicate with specific vehicles, and the first vehicle (1601) can select a number of NLOS routes or at least some of the LOS paths; LOS path is an impact zone when it there is an obstacle/occlusion/blockage on the LOS path and the vehicle has to use a different path communicate (See paragraphs 334-341)); automatically identifying line-of-sight blockage for a target vehicle entering the one or more impact zones (Paragraph 335, The first vehicle can see the occurrence of a blockage event in which an obstacle obscures the second vehicle in the line of sight (LOS) path [impact zone]; Figure 17 and paragraph 376, the first vehicle (1701) is communicating with the second vehicle (1702) as the target vehicle, but the third vehicle (1703) interferes with the communication. In this way, the third vehicle (1703) that interferes with the communication of the first vehicle (1701) is defined as a blocker); automatically identifying a secondary vehicle positioned to provide backup connectivity to the target vehicle (Figure 17 and paragraph 377, In this case, the first vehicle (1701) can communicate with the second vehicle (1702) using objects (1704a, 1704b, 1704c, 1704d) located in the adjacent environment. Objects located in adjacent environments (1704a, 1704b, 1704c, 1704d) can include other stationary vehicles (1704a), other moving vehicles (1704b), buildings (1704c), trees (1704d), and so on); and automatically establishing connectivity between the target vehicle and the secondary vehicle (Figure 17 and paragraph 378, the first vehicle (1701) can communicate using the NLOS path (1712) formed by another stationary vehicle (1704a); Paragraph 379, the first vehicle (1701) cannot communicate with the second vehicle (1702) that was communicating before the third vehicle (1703) was located, but it can communicate through the NLOS route (1712) formed in relation to the other stationary vehicle (1704a) in relation to the second vehicle (1702); Paragraph 380, The first vehicle (1701) can communicate with the second vehicle (1702) through other objects such as other moving vehicles (1704b), buildings (1704c), and trees (1704d) in addition to other stationary vehicles (1704a)). Lee does not disclose the following limitations that are disclosed by Laufer et al.: identifying a predicted line-of-sight blockage for the target vehicle entering the impact zone (Laufer et al., Paragraph 21, the change of orientation of vehicle 10 may be predicted over time based on its speed, direction and planned route so that a future LOS blockage may be predicted; Paragraph 22, the change of the location of vehicle 200 may be predicted over time based on its speed, direction and planned route so that a future blockage due to LOS blockage may be predicted); and automatically establishing connectivity with secondary vehicle before the target vehicle reaches a position corresponding to the predicted line-of-sight blockage (Laufer et al., Paragraph 21, ..a future LOS blockage may be predicted and the rerouting may be carried out before an actual blockage takes place; Paragraph 22, …a future blockage due to LOS blockage may be predicted and the rerouting may be carried out before an actual blockage takes place; Paragraph 9, Rerouting in the network level may include any change of the flow of data from one node to another via different nodes). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lee with the cited disclosure from Laufer et al. in order to predict/forecast LOS blockage to reroute communications before the actual blockage (Laufer et al., Abstract, Paragraphs 21-22). Regarding claim 2, Lee in view of Laufer et al. discloses wherein automatically identifying one or more impact zones and one or more non-impact zones located within a selected region further comprises: automatically compiling 3-dimensional (3D) city data comprising one or more of global position system data, global navigation satellite system data, forecast assured navigation data, and ray-trace data (Lee, Paragraph 204, The location data generator 280 can generate the location data of the vehicle 10. The location data generation device 280 may include at least one of the Global Positioning System (GPS) and the Differential Global Positioning System (DGPS). The location data generator 280 can generate the location data of the vehicle 10 based on the signal generated by at least one of the GPS and DGPS. Depending on the embodiment, the position data generator 280 may calibrate the position data based on at least one of the cameras of the IMU (Inertial Measurement Unit) of the sensing unit 270 and the object detection unit 210. The location data generator 280 can be named GNSS (Global Navigation Satellite System); Laufer et al., Paragraph 44, forecast input parameters may include at least one of: 2D or 3D weather conditions, satellite parameters, communication links properties, communication network performance, platform performance, platform orientation, overall communication system/platform resources; topography, terrain, geographic location, potential relays, vehicle morphology, and system failures). Regarding claim 3, Laufer et al. disclose automatically identifying the impact zones using the compiled 3D city data including positions of one or more of detected buildings, objects, or foliage in relation to one or more satellites (Paragraph 44, forecast input parameters may include at least one of: 2D or 3D weather conditions, satellite parameters, communication links properties, communication network performance, platform performance, platform orientation, overall communication system/platform resources; topography, terrain, geographic location, potential relays, vehicle morphology, and system failures). Regarding claim 6, Laufer et al. disclose wherein establishing the backup connectivity for the target vehicle before the target vehicle reaches the position corresponding to the predicted line-of-sight blockage further comprises: automatically connecting to pre-installed connectivity infrastructure using a vehicle-to-infrastructure (V2I) connection (Lee, Paragraph 377, the first vehicle (1701) can communicate with the second vehicle (1702) using objects (1704a, 1704b, 1704c, 1704d) located in the adjacent environment. Objects located in adjacent environments (1704a, 1704b, 1704c, 1704d) can include other stationary vehicles (1704a), other moving vehicles (1704b), buildings (1704c), trees (1704d), and so on; Laufer et al., Paragraph 9, Rerouting in the network level may include any change of the flow of data from one node to another via different nodes; Paragraphs 21 and 22, communication rerouted between vehicle and satellite based on predicted LOS blockage before actual blockage takes place). Regarding claim 7, Lee in view Laufer et al. discloses wherein the identified secondary vehicle is expected to be positioned within the identified non-impact zones during a time corresponding to the predicted line-of-sight blockage for the target vehicle (Figure 17 and paragraph 377, In this case, the first vehicle (1701) can communicate with the second vehicle (1702) using objects (1704a, 1704b, 1704c, 1704d) located in the adjacent environment. Objects located in adjacent environments [non-impact zones] (1704a, 1704b, 1704c, 1704d) can include other stationary vehicles (1704a) [secondary vehicle], other moving vehicles (1704b) [secondary vehicle], buildings (1704c), trees (1704d), and so on). Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Laufer et al. as applied to claim 1 above, and further in view of Geissler et al. (US 2021/0112417). Regarding claim 4, Lee in view of Laufer et al. discloses the claimed invention above as well asl wherein automatically identifying the predicted line-of-sight blockage for the target vehicle entering the one or more impact zones further comprises: automatically utilizing sensor data and external data from the target vehicle to determine an expected location of the target vehicle (Lee, Paragraph 174, The object detection device 210 may include at least one sensor that can detect objects outside the vehicle 10. The object detection device 210 may include at least one of the following sensors: a camera, radar, lidar, ultrasonic sensor, and an infrared sensor; Laufer et al., Paragraph 21, the change of orientation of vehicle 10 may be predicted over time based on its speed, direction and planned route so that a future LOS blockage may be predicted; Paragraph 22, the change of the location of vehicle 200 may be predicted over time based on its speed, direction and planned route so that a future blockage due to LOS blockage may be predicted; Paragraph 44, forecast input parameters including 2D/3D weather conditions, topography, terrain, geographic location as external data). Lee in view of Laufer et al. does not disclose the following limitations that are disclosed by Geissler et al.: to utilizing sensor data and external data to determine an expected duration corresponding to the identified predicted line-of-sight-blockage (Geissler et al., Paragraphs 32-34, detecting pathloss dips…V2X occlusion mechanism 200 to detect a pathloss dip…pathloss dip detection of first V2X occlusion mechanism…expected occlusion duration, where both the sending and the receiving channels of the trusted devices are open and transmitting and may detect the pathloss dip. The occluding interval may depend on multiple factors, most importantly the speed and the dimension of an object…duration of the direction LoS occlusion). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Lee and Laufer et al. with the cited disclosure from Geissler et al. in order to improve pathloss detection due to LoS occlusion (Geissler et al., Paragraphs 34). Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Laufer et al. as applied to claim 1 above, and further in view of Mun (US 11,218,212). Regarding claim 5, Lee in view of Laufer et al. discloses the claimed invention above but does not disclose the following limitations that are disclosed by Mun: wherein automatically identifying the secondary vehicle positioned to provide the backup connectivity to the target vehicle further comprises: automatically determining, based on received secondary vehicle external data and secondary vehicle sensor data, a future position of the secondary vehicle that corresponds to the predicted line-of-sight blockage of the target vehicle (Mun, Column 2 lines 47-53, determining locations and movement trajectories of the base station node and the mobile node using the probe node data, predicting blocking of a line-of-sight (LOS) path between the base station node and the mobile node on the basis of the locations and the movement trajectories [future position], and updating the LDM information on the basis of the predicted blocking of the LOS path; Figure 2, trajectories of mobile nodes 110). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Lee and Laufer et al. with the cited disclosure from Mun in order to further account for node movement when predicting blockage of a LOS path (Mun, Column 2 lines 47-53). Regarding claims 8-14, the functional limitations are rejected for similar reasons set forth in rejecting claims 1-7 above. Lee additionally discloses a computer system (Figure 1 and paragraphs 63-65, the first communication device or the second communication device may be a base station, a network node, a transmitting terminal, a receiving terminal, a wireless device, a wireless communication device, an autonomous driving device, etc.), the computer system comprising: one or more processors (Figure 1 and paragraph 64, processor 911/912), one or more computer-readable memories (Figure 1 and paragraph 64, memory 914/924), one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more computer-readable tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, wherein the computer system is capable of performing the functional limitations (Figure 1 and paragraph 64, The processor 921 may be associated with memory 924, which stores program code and data. Memory can be referred to as a computer-readable medium; Claim 15, one or more memories connected to one or more processors and storing instructions; and the instructions, when executed by one or more processors, enable one or more processors to support actions for intelligent beam prediction). Regarding claims 15-20, the functional limitations are rejected for similar reasons set forth in rejecting claims 1-6 above. Lee additionally discloses a computer program product comprising: the computer system comprising: one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more computer-readable tangible storage medium, the program instructions executable a processor capable of performing the functional limitations (Figure 1 and paragraph 64, The processor 921 may be associated with memory 924, which stores program code and data. Memory can be referred to as a computer-readable medium; Claim 15, one or more memories connected to one or more processors and storing instructions; and the instructions, when executed by one or more processors, enable one or more processors to support actions for intelligent beam prediction). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to OTIS L THOMPSON, JR whose telephone number is (571)270-1953. The examiner can normally be reached Monday - Friday, 6:30am - 7:00pm. 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, Chirag G. Shah can be reached at (571)272-3144. 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. /OTIS L THOMPSON, JR/Primary Examiner, Art Unit 2477 March 5, 2026
Read full office action

Prosecution Timeline

Nov 21, 2022
Application Filed
Dec 27, 2023
Response after Non-Final Action
Mar 05, 2026
Non-Final Rejection — §103 (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
89%
Grant Probability
99%
With Interview (+9.9%)
2y 6m
Median Time to Grant
Low
PTA Risk
Based on 1002 resolved cases by this examiner. Grant probability derived from career allow rate.

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