IP Library › Granted Patent US 12,744,580
Granted Patent B2
US 12,744,580 · App. 18/341,324 · Granted Sep 22, 2026

Sensor-aided beam management at user equipment

Inventors: Hoda Shahmohammadian (San Diego, CA); Jung Hyun Bae (San Diego, CA); Jungwon Lee (San Diego, CA); Dongwoon Bai (San Diego, CA)
Assignee: Samsung Electronics Co., Ltd.
H04B7/086H04B7/0617H04B7/0854H04B7/0857H04W64/006
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Quick Facts
Patent No.
US 12,744,580
App. No.
18/341,324
Granted
Sep 22, 2026
Kind
B2
Abstract

Methods and apparatuses are provided in which position information is determined corresponding to movement of a user equipment (UE) from first local coordinates to second local coordinates. Receive angles of the UE are derived from the position information of the UE. A beamforming weight of the UE is determined based on the derived receive angles of the UE. The beamforming weight is configured such that a beam direction of the second local coordinates matches a beam direction of the first local coordinates.

Claims (40)

1 . A method comprising:

determining position information corresponding to movement of a user equipment (UE) from first local coordinates to second local coordinates;

deriving receive angles of the UE from the position information of the UE; and

determining a beamforming weight of the UE based on the derived receive angles of the UE, wherein the beamforming weight is configured to compensate for a change in a local coordinate system of the UE such that a beam direction associated with the first local coordinates is preserved.

2 . The method of claim 1 , further comprising updating a steering angle of the UE based on the beamforming weight, the steering angle corresponding to a direction of highest reference signal resource power (RSRP).

3 . The method of claim 1 , wherein the position information comprises at least one of a displacement and a rotation of the UE, and the position information is measured by at least one of a gyroscope, accelerometer, and geo-magnetic sensor of the UE.

4 . The method of claim 1 , further comprising averaging a uniform distribution for one or more of the receive angles in case that the one or more of the receive angles are subject to UE blindness.

5 . The method of claim 1 , wherein the receive angles of the UE comprise a zenith angle of arrival of the UE and an azimuth angle of arrival of the UE.

6 . The method of claim 1 , wherein determining the beamforming weight comprises selecting quantized versions of beam indications based on a preset decision metric to minimize misalignment of the beam direction, wherein the beam indications are based on the receive angles of the UE.

7 . The method of claim 1 , further comprising:

determining an angle-beam relationship for the UE based on a known beamforming weight and corresponding receive beams,

wherein determining the beamforming weight comprises:

deriving quantized versions of beam indications in the updated local coordinates based on the angle-beam relationship; and

determining the beamforming weight based on the quantized versions of the beam indications.

8 . A method comprising:

estimating a first beamforming channel of a user equipment (UE) associated with first local coordinates;

determining position information corresponding to movement of the UE from the first local coordinates to second local coordinates;

estimating a second beamforming channel of the UE corresponding to the second local coordinates based on the first beamforming channel and the position information; and

determining a beamforming weight for the second local coordinates based on the second beamforming channel and a decision metric, wherein the beamforming weight corresponds to a change in a beam direction associated with the second local coordinates,

wherein the first beamforming channel is estimated based on a sensing channel recovery algorithm, and the second beamforming channel is estimated based on a technique including at least one of maximum likelihood, minimum mean square error (MMSE), autoregressive (AR) modeling, Kalman filtering, and Wiener filtering.

9 . The method of claim 8 , further comprising updating a steering angle of the UE based on the beamforming weight, the steering angle corresponding to a direction of highest reference signal resource power (RSRP).

10 . The method of claim 8 , wherein the position information comprises at least one of a displacement and a rotation of the UE, and the position information is measured by at least one of a gyroscope, accelerometer, and a geo-magnetic sensor of the UE.

11 . The method of claim 8 , wherein determining the beamforming weight comprises selecting the beamforming weight from a codebook based on the decision metric maximizing at least one of RSRP, signal-to-interference and noise ratio (SINR), and capacity in a beamforming scheme.

12 . The method of claim 8 , further comprising averaging a uniform distribution for one or more angles of arrival at different stages of beamforming weight determination in case that the one or more angles of arrival are subject to UE blindness.

13 . A user equipment (UE) comprising:

a processor; and

a non-transitory computer readable storage medium storing instructions that, when executed, cause the processor to:

determine position information corresponding to movement of the UE from first local coordinates to second local coordinates;

derive receive angles of the UE from the position information of the UE; and

determine a beamforming weight of the UE based on the derived receive angles of the UE, wherein the beamforming weight is configured to compensate for a change in a local coordinate system of the UE such that a beam direction associated with the first local coordinates is preserved.

14 . The UE of claim 13 , wherein the instructions further cause the processor to update a steering angle of the UE based on the beamforming weight, the steering angle corresponding to a direction of highest reference signal resource power (RSRP).

15 . The UE of claim 13 , further comprising a sensor component including at least one of a gyroscope, accelerometer, and geo-magnetic sensor that measure the position information, wherein the position information comprises at least one of a displacement and a rotation of the UE as measured by the sensor component.

16 . The UE of claim 13 , wherein the instructions further cause the processor to average a uniform distribution for one or more of the receive angles in case that the one or more of the receive angles are subject to UE blindness.

17 . The UE of claim 13 , wherein the receive angles of the UE comprise a zenith angle of arrival of the UE and an azimuth angle of arrival of the UE.

18 . The UE of claim 13 , wherein, in determining the beamforming weight, the instructions further cause the processor to select quantized versions of beam indications based on a preset decision metric to minimize misalignment of the beam direction, wherein the beam indications are based on the receive angles of the UE.

19 . The UE of claim 13 , wherein:

the instructions further cause the processor to determine an angle-beam relationship for the UE based on a known beamforming weight and corresponding receive beams; and

in determining the beamforming weight, the instructions further cause the processor to:

derive quantized versions of beam indications in the updated local coordinates based on the angle-beam relationship; and

determine the beamforming weight based on the quantized versions of the beam indications.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 7, 2023
From: SHAHMOHAMMADIAN, HODA; BAE, JUNG HYUN; LEE, JUNGWON; BAI, DONGWOON
To: SAMSUNG ELECTRONICS CO., LTD.
Reel/Frame 064183/0847 →
Continuity (2)
Provisional Application 63432662 · Dec 14, 2022
Related Publication 20240204855A1 · Jun 20, 2024
References Cited (24)
US 9253592B1 · Moscovich · 2016 [cited by examiner]
US 10447374B2 · Rune et al. · 2019 [cited by applicant]
US 10841819B2 · Yu et al. · 2020 [cited by applicant]
US 11245456B2 · Marinier et al. · 2022 [cited by applicant]
US 20120230380A1 · Keusgen · 2012 [cited by examiner]
US 20170111852A1 · Selén · 2017 [cited by examiner]
US 20170195834A1 · Na · 2017 [cited by examiner]
US 20200204237A1 · Zhou · 2020 [cited by examiner]
US 20200374713A1 · Bogatin · 2020 [cited by examiner]
US 20210328653A1 · Tang · 2021 [cited by examiner]
US 20220352960A1 · Park et al. · 2022 [cited by applicant]
US 20230103220A1 · Pezeshki · 2023 [cited by examiner]
US 20230291444A1 · Nammi · 2023 [cited by examiner]
IN 201841012895 · 2019 [cited by applicant]
WO WO2022133933 · 2022 [cited by applicant]
Duk-Sun Shim et al., “Application of Motion Sensors for Beam-Tracking of Mobile Stations in mmWave Communication Systems”, Sensors 2014, 14, 19622-19638, pp. 17. [cited by applicant]
Zichen Qi et al., “Three-Dimensional Millimetre Wave Beam Tracking Based on Handset MEMS Sensors with Extended Kalman Filtering”. [cited by applicant]
Radio Propagation and Technologies for 5G. Mar. 6, 2016, pp. 7. [cited by applicant]
Zichen Qi, “Three-Dimensional Beam Tracking for Wireless Communications Systems”, Feb. 2019, University of Sheffield, pp. 77. [cited by applicant]
Sentiance Team, “Driving behavior modeling using smart phone sensor data”, https://sentiance.com/driving-behavior-modeling-using-smart-phone-sensor-data, May 25, 2023, pp. 17. [cited by applicant]
3GPP TR 36.897 V13.0.0 (Jun. 2015), Technical Report, pp. 58. [cited by applicant]
3GPP TR 38.901 V17.0.0 (Mar. 2022), Technical Report, pp. 98. [cited by applicant]
ZTE, ZTE Microelectronics, “Further clarification on assumptions for Phase 1”, 3GPP TSG RAN WG1 NR Ad-Hoc Meeting R1-1700144 Spokane, USA, Jan. 16-20, 2017, pp. 8. [cited by applicant]
Hyoungju Ji et al., “Overview of Full-Dimension MIMO in LTE-Advanced Pro”, arXiv:1601.00019v4 [cs.IT] Aug. 10, 2016, pp. 22. [cited by applicant]