Self-configuring long term evolution radio access network on unmanned autonomous vehicles

Patent metadata

Field	Value
Publication number	US-11054843-B2
Application number	US-201916289847-A
Country	US
Kind code	B2
Filing date	Mar 1, 2019
Priority date	Mar 12, 2018
Publication date	Jul 6, 2021
Grant date	Jul 6, 2021

Abstract

A computer-implemented method, system, and computer program product are provided for positioning an unmanned autonomous vehicle (UAV) in a long term evolution radio access network. The method includes acquiring, by a processor-device, a position of the UAV with a global position system. The method also includes determining, by the processor-device, physical distances from the UAV to each of a plurality of user equipment (UE) responsive to a time-of-flight from the UAV to each of the plurality of UE. The method additionally includes generating, by the processor-device, radio environment maps for each of the plurality of UE with signal-to-noise ratios (SNR) from each of the plurality of UEs to the UAV. The method further includes selecting, by the processor-device, a determined position for the UAV as a position with a minimum SNR in the REMs. The method also includes commanding the UAV to move to the determined position.

First claim

What is claimed is:

1. A computer-implemented method for positioning an unmanned autonomous vehicle (UAV) in a long term evolution (LTE) radio access network (RAN), the method comprising:
acquiring, by a processor-device, a position of the UAV with a global position system (GPS);
determining, by the processor-device, physical distances from the UAV to each of a plurality of user equipment (UE) responsive to a time-of-flight (ToF) from the UAV to each of the plurality of UE;
generating, by the processor-device, radio environment maps (REMs) for each of the plurality of UE with signal-to-noise ratios (SNR) from each of the plurality of UEs to the UAV;
selecting, by the processor-device, a determined position for the UAV as a position with a minimum SNR in the REMs;
computing a flight trajectory of the UAV in an operation area of the UAV by resolving a gradient map of differences between SNR in adjacent cells of an aggregate map; and
commanding the UAV to move to the determined position.

2. The computer-implemented method as recited in claim 1 , wherein determining includes generating the ToF from the UAV to each of the plurality of UE utilizing the position of the UAV and a synchronization reference signal (SRS) from each of the plurality of UE.

3. The computer-implemented method as recited in claim 2 , wherein utilizing includes assigning averages of a plurality of SRSs to a GPS report to generate a stream of GPS-ToF tuples.

4. The computer-implemented method as recited in claim 3 , wherein assigning includes resolving a UE position with a multilateration algorithm employing the stream of GPS-ToF tuples.

5. The computer-implemented method as recited in claim 1 , wherein generating includes assigning an optimal altitude for the UAV by selecting an altitude that has a lowest signal path loss between the UAV and the plurality of UE for a predefined altitude range.

6. The computer-implemented method as recited in claim 1 , wherein computing includes aggregating the REMs into the aggregate REM.

7. The computer-implemented method as recited in claim 1 , wherein computing includes clustering grid cells in a gradient map into high gradient clusters and low gradient clusters.

8. The computer-implemented method as recited in claim 1 , wherein computing includes calculating an information gain for each of the plurality of UE along a new trajectory.

9. The computer-implemented method as recited in claim 1 , wherein computing includes calculating cost-to-information ratios for each of the plurality of UE along a trajectory.

10. A computer program product for positioning an unmanned autonomous vehicle (UAV) in a long term evolution (LTE) radio access network (RAN), the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising:
acquiring, by a processor-device, a position of the UAV with a global position system (GPS);
determining, by the processor-device, physical distances from the UAV to each of a plurality of user equipment (UE) responsive to a time-of-flight from the UAV to each of the plurality of UE;
generating, by the processor-device, radio environment maps (REMs) for each of the plurality of UE with signal-to-noise ratios (SNR) from each of the plurality of UEs to the UAV;
selecting, by the processor-device, a determined position for the UAV as a position with a minimum SNR in the REMs;
aggregating, by the processor-device, the REMs into an aggregate REM and resolve a gradient map of differences between SNR in adjacent cells of the aggregate REM; and
commanding the UAV to move to the determined position.

11. An unmanned autonomous vehicle (UAV) in a long term evolution (LTE) radio access network (RAN), the UAV comprising:
a processing system including a processor and memory coupled to the processor, the processing system programmed to:
acquire a position of the UAV with a global position system (GPS);
determine physical distances from the UAV to each of a plurality of user equipment (UE) responsive to a time-of-flight (ToF) from the UAV to each of the plurality of UE;
generate radio environment maps (REMs) for each of the plurality of UE with signal-to-noise ratios (SNR) from each of the plurality of UEs to the UAV;
select a determined position for the UAV as a position with a minimum SNR in the REMs; and
aggregate the REMs into an aggregate REM and resolve a gradient map of differences between SNR in adjacent cells of the aggregate REM; and
move the UAV to the determined position.

12. The UAV as recited in claim 11 , wherein the processing system is further programmed to generate the ToF from the UAV to each of the plurality of UE utilizing the position of the UAV and a synchronization reference signal (SRS) from each of the plurality of UE.

13. The UAV as recited in claim 12 , wherein the processing system is further programmed to assign averages of a plurality of SRS s to a GPS report to generate a stream of GPS-ToF tuples.

14. The UAV as recited in claim 13 , wherein the processing system is further programmed to resolve a UE position with a multilateration algorithm employing the stream of GPS-ToF tuples.

15. The UAV as recited in claim 11 , wherein the processing system is further programmed to assign an optimal altitude for the UAV by selecting an altitude that has a lowest signal path loss between the UAV and the plurality of UE for a predefined altitude range.

16. The UAV as recited in claim 11 , wherein the processing system is further programmed to compute a flight trajectory of the UAV in an operation area of the UAV.

17. The UAV as recited in claim 11 , wherein the processing system is further programmed to calculate an information gain and cost-to-information ratios for each of the plurality of UE along a new trajectory.

Assignees

• Nec Lab America Inc
• Nec Corp

Inventors

• Sundaresan Karthikeyan
• Chai Eugene
• Rangarajan Sampath
• Khojastepour Mohammad
• Chakraborty Ayon

Classifications

• B64U2201/102

  adapted for flying in formations · CPC title

• B64U2201/104

  using satellite radio beacon positioning systems, e.g. GPS · CPC title

• G01S19/10

  providing dedicated supplementary positioning signals · CPC title

• H04B7/18504

  Aircraft used as relay or high altitude atmospheric platform · CPC title

• G01S19/46

  the supplementary measurement being of a radio-wave signal type · CPC title