IP Library › Granted Patent US 11,888,236
Granted Patent B2
US 11,888,236 · App. 17/295,623 · Granted Jan 30, 2024

Method and device for selecting reception beam on basis of artificial neural network

Inventors: Yongsang Cho (Suwon-si, KR); Taeyoon Kim (Suwon-si, KR); Chaeman Lim (Suwon-si, KR); Hyoungjoo Lee (Suwon-si, KR)
Assignee: Samsung Electronics Co., Ltd.
H01Q3/2605G06N3/02H01Q3/24H04B10/695
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Quick Facts
Patent No.
US 11,888,236
App. No.
17/295,623
Granted
Jan 30, 2024
Kind
B2
Abstract

Disclosed in various embodiments of the present invention are a method and a device, the device comprising: an antenna module configured to form a plurality of beams having different directions; and a processor operatively connected to the antenna module, wherein the processor is configured to select a partial reception beam from among a plurality of reception beams, measure the reception power of the selected reception beam, determine a transmission condition through an artificial neural network on the basis of the measured reception power, and determine a reception beam for a communication connection by using the artificial neural network corresponding to the transmission condition. Various embodiments are possible.

Claims (48)

1. An electronic device comprising:

an antenna module configured to form a plurality of reception beams in different directions; and

a processor operatively connected to the antenna module,

wherein the processor is configured to

select some reception beams from among the plurality of reception beams,

measure reception power of the selected reception beams,

determine a transmission condition through an artificial neural network, based on the measured reception power, and

determine a reception beam for a communication connection using an artificial neural network corresponding to the transmission condition.

2. The electronic device of claim 1 , wherein the processor is configured to select at least two reception beams, which are not adjacent to each other, from among the plurality of reception beams.

3. The electronic device of claim 1 , wherein the processor is configured to determine the transmission condition by inputting the measured reception power to the artificial neural network for determining the transmission condition.

4. The electronic device of claim 1 , wherein the transmission condition comprises at least one of no transmission beam, NLOS (non-line of sight), or LOS (line of sight), and

wherein the processor is configured to predict a reception beam using an artificial neural network corresponding to the transmission condition.

5. The electronic device of claim 4 , wherein the processor is configured

if the transmission condition is “NLOS”, to predict a reception beam using an artificial neural network corresponding to “NLOS”, and

if the transmission condition is “LOS”, to predict a reception beam using an artificial neural network corresponding to “LOS”.

6. The electronic device of claim 4 , wherein the processor is configured, if the transmission condition is “no transmission beam”, to perform a reception beam prediction process for a reception beam that is not selected from among the plurality of reception beams.

7. The method of claim 1 , wherein the processor is configured

if reception power of the selected reception beam is less than or equal to a minimum power, to determine the transmission condition to be “no transmission beam”, and,

if the reception power of the selected reception beam exceeds the minimum power, to determine the transmission condition to be “NLOS” or “LOS”.

8. The electronic device of claim 7 , wherein the processor is configured

if a difference in reception power between the selected reception beams is less than or equal to a reference value, to determine the transmission condition to be “NLOS”, and

if a difference in reception power between the selected reception beams exceeds the reference value, to determine the transmission condition to be “LOS”.

9. The electronic device of claim 1 , wherein the processor is configured to

predict a reception beam using the artificial neural network corresponding to the transmission condition,

determine success or failure of communication through the predicted reception beam, and

determine a reception beam for a communication connection, based on the determination result.

10. The electronic device of claim 9 , wherein the processor is configured

to predict an error rate of the predicted reception beam, and

if the predicted error rate is less than a threshold, to determine the predicted reception beam to be a reception beam for a communication connection.

11. The electronic device of claim 9 , wherein the processor is configured

to predict an error rate of the predicted reception beam,

if the predicted error rate is greater than or equal to a threshold, to determine that communication fails, and

to perform a reception beam prediction process for a reception beam that is not selected from among the plurality of reception beams.

12. The electronic device of claim 1 , wherein the processor is configured to

predict a reception beam using an artificial neural network corresponding to the transmission condition,

measure reception power of the predicted reception beam, and

determine a reception beam for a communication connection, based on the measured reception power.

13. The electronic device of claim 12 , wherein the processor is configured

if the reception power of the predicted reception beam is greater than or equal to a reference value, to predict an error rate of the predicted reception beam, and

if the predicted error rate is less than a threshold, to determine the predicted reception beam to be a reception beam for a communication connection.

14. The electronic device of claim 12 , wherein the processor is configured

if the reception power of the predicted reception beam is less than a reference value, to predict an error rate of a reception beam having the highest reception power among the reception beams whose reception power was measured, and

if the predicted error rate is less than a threshold, to determine the reception beam having the highest reception power to be a reception beam for a communication connection.

15. An operation method of an electronic device, the method comprising:

selecting some reception beams from among a plurality of reception beams in different directions from each other;

measuring reception power of the selected reception beams;

determining a transmission condition through an artificial neural network, based on the measured reception power; and

determining a reception beam for a communication connection using an artificial neural network corresponding to the transmission condition.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 20, 2021
From: CHO, YONGSANG; KIM, TAEYOON; LIM, CHAEMAN; LEE, HYOUNGJOO
To: SAMSUNG ELECTRONICS CO., LTD.
Reel/Frame 056301/0786 →
Priority Claims (1)
KR 10-2018-0147525 · Nov 26, 2018 · national
Continuity (1)
Related Publication 20220029286A1 · Jan 27, 2022