US-12621037-B2 - Beam tracking with statistical learning

Abstract

A method includes obtaining information representing a current state of communication with a user equipment (UE) performed using one or more beams. The method also includes comparing the information to statistical historical state information to determine one or more best next narrow beam candidates. The method further includes performing a beam search using the one or more best next narrow beam candidates in order to select a next narrow beam. The method also includes communicating with the UE using the selected next narrow beam.

Inventors

• Mustafa Furkan Ozkoc
• JIANHUA MO

Assignees

• SAMSUNG ELECTRONICS CO., LTD.

Dates

Publication Date

20260505

Application Date

20230803

Claims (20)

1. 1 . A method comprising: obtaining information representing a current state of communication with a user equipment (UE) performed using one or more beams; comparing the information to statistical historical state information to determine one or more best next narrow beam candidates; performing a beam search using the one or more best next narrow beam candidates in order to select a next narrow beam; and communicating with the UE using the selected next narrow beam, wherein the statistical historical state information comprises a current wide beam, a current narrow beam, and a previous narrow beam before the current narrow beam.
2. 2 . The method of claim 1 , wherein the statistical historical state information further comprises a reference signal received power (RSRP) change indicator.
3. 3 . The method of claim 2 , wherein the RSRP change indicator indicates whether or not a RSRP of the current narrow beam is increasing.
4. 4 . The method of claim 2 , wherein the statistical historical state information further comprises: multiple next narrow beam candidates; and an observation count corresponding to each of the multiple next narrow beam candidates.
5. 5 . The method of claim 1 , further comprising: obtaining a new observation of the current state of communication in response to communicating with the UE using the selected next narrow beam; and updating the statistical historical state information based on the new observation.
6. 6 . The method of claim 5 , wherein updating the statistical historical state information based on the new observation comprises at least one of: adding a new data record to the statistical historical state information; and updating an observation count of an existing record of the statistical historical state information.
7. 7 . The method of claim 1 , wherein the one or more best next narrow beam candidates comprise one of: a most frequent next narrow beam candidate; a predetermined quantity of next narrow beam candidates; and multiple next narrow beam candidates having an accumulated probability that is equal to or greater than a threshold probability value.
8. 8 . A device comprising: a transceiver; and a processor operably connected to the transceiver, the processor configured to: obtain information representing a current state of communication with a user equipment (UE) performed using one or more beams; compare the information to statistical historical state information to determine one or more best next narrow beam candidates; perform a beam search using the one or more best next narrow beam candidates in order to select a next narrow beam; and communicate with the UE using the selected next narrow beam, wherein the statistical historical state information comprises (i) multiple next narrow beam candidates, and (ii) an observation count corresponding to each of the multiple next narrow beam candidates.
9. 9 . The device of claim 8 , wherein the statistical historical state information further comprises a current wide beam, a current narrow beam, a previous narrow beam before the current narrow beam, and a reference signal received power (RSRP) change indicator.
10. 10 . The device of claim 9 , wherein the RSRP change indicator indicates whether or not a RSRP of the current narrow beam is increasing.
11. 11 . The device of claim 8 , wherein the processor is further configured to: obtain a new observation of the current state of communication in response to communicating with the UE using the selected next narrow beam; and update the statistical historical state information based on the new observation.
12. 12 . The device of claim 11 , wherein to update the statistical historical state information based on the new observation, the processor is configured to at least one of: add a new data record to the statistical historical state information; and update an observation count of an existing record of the statistical historical state information.
13. 13 . The device of claim 8 , wherein the one or more best next narrow beam candidates comprise one of: a most frequent next narrow beam candidate; a predetermined quantity of next narrow beam candidates; and multiple next narrow beam candidates having an accumulated probability that is equal to or greater than a threshold probability value.
14. 14 . A non-transitory computer readable medium comprising program code that, when executed by a processor of a device, causes the device to: obtain information representing a current state of communication with a user equipment (UE) performed using one or more beams; compare the information to statistical historical state information to determine one or more best next narrow beam candidates; perform a beam search using the one or more best next narrow beam candidates in order to select a next narrow beam; and communicate with the UE using the selected next narrow beam, wherein the statistical historical state information comprises a current wide beam, a current narrow beam, and a previous narrow beam before the current narrow beam.
15. 15 . The non-transitory computer readable medium of claim 14 , wherein the statistical historical state information further comprises a reference signal received power (RSRP) change indicator.
16. 16 . The non-transitory computer readable medium of claim 15 , wherein the statistical historical state information further comprises: multiple next narrow beam candidates; and an observation count corresponding to each of the multiple next narrow beam candidates.
17. 17 . The non-transitory computer readable medium of claim 14 , wherein the RSRP change indicator indicates whether or not a RSRP of a current narrow beam is increasing.
18. 18 . The non-transitory computer readable medium of claim 14 , wherein the program code further causes the device to: obtain a new observation of the current state of communication in response to communicating with the UE using the selected next narrow beam; and update the statistical historical state information based on the new observation.
19. 19 . The non-transitory computer readable medium of claim 18 , wherein the program code to update the statistical historical state information based on the new observation, further comprises program code to at least one of: add a new data record to the statistical historical state information; and update an observation count of an existing record of the statistical historical state information.
20. 20 . The non-transitory computer readable medium of claim 14 , wherein the one or more best next narrow beam candidates comprise one of: a most frequent next narrow beam candidate; a predetermined quantity of next narrow beam candidates; and multiple next narrow beam candidates having an accumulated probability that is equal to or greater than a threshold probability value.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS AND CLAIM OF PRIORITY The present application claims priority to U.S. Provisional Patent Application Ser. No. 63/399,358 filed on Aug. 19, 2022. The content of the above-identified patent document is incorporated herein by reference. TECHNICAL FIELD The present disclosure relates generally to wireless communication systems and, more specifically, the present disclosure relates to a system and method for beam tracking with statistical learning. BACKGROUND Beam management is an important and required procedure in mmWave frequencies. The mmWave beam codebook design is very important and challenging for 5G mmWave base stations. Different from the low frequency bands, beamforming is needed to support the high data transmission at the mmWave band due to the large mmWave band path-loss. A significant number of beams (e.g., more than 100 beams) may be needed to cover a wide angular region, for example, horizontally from −60 degrees to +60 degrees. On the other hand, many reference signals are needed to find out the best beam between the base station (BS) and the user equipment (UE). SUMMARY The present disclosure relates to wireless communication systems and, more specifically, the present disclosure relates to a system and method for beam tracking with statistical learning. In one embodiment, a method includes obtaining information representing a current state of communication with a user equipment (UE) performed using one or more beams. The method also includes comparing the information to statistical historical state information to determine one or more best next narrow beam candidates. The method further includes performing a beam search using the one or more best next narrow beam candidates in order to select a next narrow beam. The method also includes communicating with the UE using the selected next narrow beam. In another embodiment, a device includes a transceiver and a processor operably connected to the transceiver. The processor is configured to: obtain information representing a current state of communication with a UE performed using one or more beams; compare the information to statistical historical state information to determine one or more best next narrow beam candidates; perform a beam search using the one or more best next narrow beam candidates in order to select a next narrow beam; and communicate with the UE using the selected next narrow beam. In yet another embodiment, a non-transitory computer readable medium includes program code that, when executed by a processor of a device, causes the device to: obtain information representing a current state of communication with a UE performed using one or more beams; compare the information to statistical historical state information to determine one or more best next narrow beam candidates; perform a beam search using the one or more best next narrow beam candidates in order to select a next narrow beam; and communicate with the UE using the selected next narrow beam. Other technical features may be readily apparent to one skilled in the art from the following figures, descriptions, and claims. Before undertaking the DETAILED DESCRIPTION below, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document. The term “couple” and its derivatives refer to any direct or indirect communication between two or more elements, whether or not those elements are in physical contact with one another. The terms “transmit,” “receive,” and “communicate,” as well as derivatives thereof, encompass both direct and indirect communication. The terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation. The term “or” is inclusive, meaning and/or. The phrase “associated with,” as well as derivatives thereof, means to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or the like. The term “controller” means any device, system, or part thereof that controls at least one operation. Such a controller may be implemented in hardware or a combination of hardware and software and/or firmware. The functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. The phrase “at least one of,” when used with a list of items, means that different combinations of one or more of the listed items may be used, and only one item in the list may be needed. For example, “at least one of: A, B, and C” includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C. Moreover, various functions described below can be implemented or supported by one or more computer programs, each of which is formed from computer readable program code and embodied in a com