IP Library › Granted Patent US 11,689,264

Granted Patent B2

US 11,689,264 · App. 16/947,531 · Granted Jun 27, 2023

Determining a narrow beam for wireless communication

Inventors: Ravi Shankar Mehta (Ranchi, IN); Girish Kakalwar (Kalaburgi, IN); Dheeraj Sai V L Naga Dhulipalla (Nellore, IN)

Assignee: QUALCOMM INCORPORATED

H04B7/0617 G06N3/02 H04B17/391 H04W40/20 H04W52/04

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Quick Facts

Patent No.: US 11,689,264
App. No.: 16/947,531
Granted: Jun 27, 2023
Kind: B2

External Links

USPTO Patent Center↗ Full Patent PDF↗

Abstract

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first wireless communication device may determine, based at least in part on a first model, an estimated position of the first wireless communication device. The first wireless communication device may determine, based at least in part on a second model, an estimated direction for transmission of a packet to a second wireless communication device. The first wireless communication device may determine, based at least in part on a third model, an estimated transmit power for transmission of the packet. The first wireless communication device may determine, using a neural network, a narrow beam based at least in part on the estimated position, the estimated direction, and the estimated transmit power. The first wireless communication device may transmit the packet on the narrow beam to the second wireless communication device. Numerous other aspects are provided.

Claims (166)

1. A method of wireless communication performed by a first wireless communication device, comprising:

determining, based at least in part on a first model, an estimated position of the first wireless communication device, the estimated position including a first set of coordinate fields for a first coordinate plane and a second set of coordinate fields for a second coordinate plane;

determining, for a first coordinate field of the first set of coordinate fields:

that a first confidence value for an estimated error for the first coordinate field is 0 if the estimated error for the first coordinate field satisfies a first threshold, or

that the first confidence value is 1 if the estimated error for the first coordinate field does not satisfy the first threshold;

determining, for a second coordinate field of the first set of coordinate fields:

that a second confidence value for an estimated error for the second coordinate field is 0 if the estimated error for the second coordinate field satisfies a second threshold, or

that the second confidence value is 1 if the estimated error for the second coordinate field does not satisfy the second threshold;

determining, based at least in part on a second model, an estimated direction for transmission of a packet to a second wireless communication device;

determining, based at least in part on a third model, an estimated transmit power for transmission of the packet to the second wireless communication device;

determining, using a neural network, a narrow beam based at least in part on the estimated position, the estimated direction, and the estimated transmit power; and

transmitting the packet on the narrow beam to the second wireless communication device.

2. The method of claim 1 , wherein determining the estimated position comprises:

determining the estimated position based at least in part on:

one or more first parameters associated with the packet, and

one or more second parameters associated with another packet received from the second wireless communication device.

3. The method of claim 2 , wherein the one or more first parameters comprise at least one of:

beam position coordinates associated with the first wireless communication device, and

global navigation satellite system (GNSS) coordinates associated with the first wireless communication device; and

wherein the one or more second parameters comprise at least one of:

beam position coordinates associated with the second wireless communication device, and

GNSS coordinates associated with the second wireless communication device.

4. The method of claim 1 , wherein the first model comprises a regression model; and

wherein determining the estimated position comprises:

determining, using the regression model, the first set of coordinate fields for the first coordinate plane; and

determining, using the regression model, the second set of coordinate fields for the second coordinate plane.

5. The method of claim 4 , wherein the first set of coordinate fields and the second set of coordinate fields are based at least in part on:

beam position coordinates associated with the first wireless communication device,

global navigation satellite system (GNSS) coordinates associated with the first wireless communication device;

beam position coordinates associated with the second wireless communication device; and

GNSS coordinates associated with the second wireless communication device.

6. The method of claim 5 , wherein determining the first set of coordinate fields comprises:

determining a first beam coordinate field of the first set of coordinate fields based at least in part on a difference between a first beam position coordinate of the beam position coordinates associated with the first wireless communication device and an accumulated change for the first beam position coordinate;

determining a second beam coordinate field of the first set of coordinate fields based at least in part on a difference between a second beam position coordinate of the beam position coordinates associated with the first wireless communication device and an accumulated change for the second beam position coordinate;

determining a first GNSS coordinate field of the first set of coordinate fields based at least in part on a difference between a first GNSS coordinate of the GNSS coordinates associated with the first wireless communication device and an accumulated change for the first GNSS coordinate; and

determining a second GNSS coordinate field of the first set of coordinate fields based at least in part on a difference between a second GNSS coordinate of the GNSS coordinates associated with the first wireless communication device and an accumulated change for the second GNSS coordinate.

7. The method of claim 4 , further comprising:

determining an estimated error for each coordinate field of the first set of coordinate fields, and

determining a confidence value for each estimated error.

8. The method of claim 4 , wherein determining the estimated position comprises:

determining, as the estimated position:

a first beam number based at least in part on the first set of coordinate fields; and

a second beam number based at least in part on the second set of coordinate fields.

9. The method of claim 1 , wherein determining the estimated direction for transmission of the packet to the second wireless communication device comprises:

determining the estimated direction as a three-dimensional vector that is based at least in part on:

the first set of coordinate fields in the first coordinate plane, and

the second set of coordinate fields in the second coordinate plane.

10. The method of claim 1 , wherein the third model comprises a linear regression model; and

wherein determining the estimated transmit power for transmission of the packet to the second wireless communication device comprises:

determining a first transmit power component in the first coordinate plane;

determining a second transmit power component in the second coordinate plane; and

determining, using the linear regression model, the estimated transmit power based at least in part on the first transmit power component and the second transmit power component.

11. The method of claim 1 , wherein the neural network is a generative adversarial network; and

wherein determining the narrow beam comprises:

clubbing the estimated position, the estimated direction, and the estimated transmit power to generate an input to the generative adversarial network; and

processing the input using the generative adversarial network to determine narrow beam.

12. A first wireless communication device for wireless communication, comprising:

a memory; and

one or more processors coupled to the memory, the one or more processors configured to:

determine, based at least in part on a first model, an estimated position of the first wireless communication device, the estimated position including a first set of coordinate fields for a first coordinate plane and a second set of coordinate fields for a second coordinate plane;

determine, for a first coordinate field of the first set of coordinate fields:

that a first confidence value for an estimated error for the first coordinate field is 0 if the estimated error for the first coordinate field satisfies a first threshold, or

that the first confidence value is 1 if the estimated error for the first coordinate field does not satisfy the first threshold;

determine, for a second coordinate field of the first set of coordinate fields:

that a second confidence value for an estimated error for the second coordinate field is 0 if the estimated error for the second coordinate field satisfies a second threshold, or

that the second confidence value is 1 if the estimated error for the second coordinate field does not satisfy the second threshold;

determine, based at least in part on a second model, an estimated direction for transmission of a packet to a second wireless communication device;

determine, based at least in part on a third model, an estimated transmit power for transmission of the packet to the second wireless communication device;

determine, using a neural network, a narrow beam based at least in part on the estimated position, the estimated direction, and the estimated transmit power; and

transmit the packet on the narrow beam to the second wireless communication device.

13. The first wireless communication device of claim 12 , wherein the one or more processors, when determining the estimated position, are configured to:

determine the estimated position based at least in part on:

one or more first parameters associated with the packet, and

one or more second parameters associated with another packet received from the second wireless communication device.

14. The first wireless communication device of claim 13 , wherein the one or more first parameters comprise at least one of:

beam position coordinates associated with the first wireless communication device, and

global navigation satellite system (GNSS) coordinates associated with the first wireless communication device; and

wherein the one or more second parameters comprise at least one of:

beam position coordinates associated with the second wireless communication device, and

GNSS coordinates associated with the second wireless communication device.

15. The first wireless communication device of claim 12 , wherein the first model comprises a regression model; and

wherein the one or more processors, when determining the estimated position, are configured to:

determine, using the regression model, the first set of coordinate fields for the first coordinate plane; and

determine, using the regression model, the second set of coordinate fields for the second coordinate plane.

16. The first wireless communication device of claim 15 , wherein the first set of coordinate fields and the second set of coordinate fields are based at least in part on:

beam position coordinates associated with the first wireless communication device,

global navigation satellite system (GNSS) coordinates associated with the first wireless communication device;

beam position coordinates associated with the second wireless communication device; and

GNSS coordinates associated with the second wireless communication device.

17. The first wireless communication device of claim 16 , wherein the one or more processors, when determining the first set of coordinate fields, are configured to:

determine a first beam coordinate field of the first set of coordinate fields based at least in part on a difference between a first beam position coordinate of the beam position coordinates associated with the first wireless communication device and an accumulated change for the first beam position coordinate;

determine a second beam coordinate field of the first set of coordinate fields based at least in part on a difference between a second beam position coordinate of the beam position coordinates associated with the first wireless communication device and an accumulated change for the second beam position coordinate;

determine a first GNSS coordinate field of the first set of coordinate fields based at least in part on a difference between a first GNSS coordinate of the GNSS coordinates associated with the first wireless communication device and an accumulated change for the first GNSS coordinate; and

determine a second GNSS coordinate field of the first set of coordinate fields based at least in part on a difference between a second GNSS coordinate of the GNSS coordinates associated with the first wireless communication device and an accumulated change for the second GNSS coordinate.

18. The first wireless communication device of claim 15 , wherein the one or more processors are further configured to:

determine an estimated error for each coordinate field of the first set of coordinate fields, and

determine a confidence value for each estimated error.

19. The first wireless communication device of claim 15 , wherein the one or more processors, when determining the estimated position, are configured to:

determine, as the estimated position:

a first beam number based at least in part on the first set of coordinate fields; and

a second beam number based at least in part on the second set of coordinate fields.

20. The first wireless communication device of claim 12 , wherein the one or more processors, when determining the estimated direction for transmission of the packet to the second wireless communication device, are configured to:

determine the estimated direction as a three-dimensional vector that is based at least in part on:

the first set of coordinate fields in the first coordinate plane, and

the second set of coordinate fields in the second coordinate plane.

21. The first wireless communication device of claim 12 , wherein the third model comprises a linear regression model; and

wherein the one or more processors, when determining the estimated transmit power for transmission of the packet to the second wireless communication device, are configured to:

determine a first transmit power component in the first coordinate plane;

determine a second transmit power component in the second coordinate plane; and

determine, using the linear regression model, the estimated transmit power based at least in part on the first transmit power component and the second transmit power component.

22. The first wireless communication device of claim 12 , wherein the neural network is a generative adversarial network; and

wherein the one or more processors, when determining the narrow beam, are configured to:

club the estimated position, the estimated direction, and the estimated transmit power to generate an input to the generative adversarial network; and

process the input using the generative adversarial network to determine narrow beam.

23. A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising:

one or more instructions that, when executed by one or more processors of a first wireless communication device, cause the first wireless communication device to: