Wireless communication method and device

Patent metadata

Field	Value
Publication number	US-2026012917-A1
Application number	US-202519324856-A
Country	US
Kind code	A1
Filing date	Sep 10, 2025
Priority date	Mar 29, 2023
Publication date	Jan 8, 2026
Grant date	—

Abstract

A wireless communication method and device are provided. The method includes that: the distribution of positional features between a user node and at least three signal source nodes is acquired; and the position of the user node is determined according to the distribution of the positional features between the user node and the at least three signal source nodes.

First claim

1 . A method for wireless communication, comprising:
obtaining distributions of positional features between a user node and at least three signal source nodes; and determining a position of the user node according to the distributions of the positional features between the user node and the at least three signal source nodes.

2 . The method according to claim 1 , wherein obtaining the distributions of positional features between the user node and the at least three signal source nodes comprises:
determining first distributions according to signals sent by the at least three signal source nodes and received by the user node, wherein the first distributions are distributions of environmental information included in the signals; determining second distributions according to the signals sent by the at least three signal source nodes and received by the user node, wherein the second distributions are distributions of the positional features of the signals under the environmental information of the first distributions; and determining a target distribution according to the first distributions and second distributions, wherein the target distribution is a distribution of the positional features included in the signals.

3 . The method according to claim 2 , wherein determining the target distribution according to the first distributions and second distributions comprises:
determining the target distribution p(x|r) according to the following formula:

p
⁡
(

x
|
r

)

=

∑
z

p
⁡
(

z
|
r

)

⁢

p
⁡
(

x
|
r

,
z

)

where r represents a received signal, z represents the environmental information, x represents the positional feature, p(z|r) represents the distribution of the environmental information z included in the signal r, and p(x|r, z) represents the distribution of the positional feature included in the signal r under the environmental information z.

4 . The method according to claim 2 , further comprising:
determining, according to the first distributions, an environmental tag corresponding to an environment in which the user node is located.

5 . The method according to claim 2 , wherein the target distribution is obtained based on a target model, the target model comprises a first network module and a second network module, the first network module is used to infer a first distribution, and the second network module is used to infer a second distribution;
wherein an input of the first network module is a received signal, and an output of the first network module is a distribution parameter corresponding to the first distribution; wherein the first distribution is a variational distribution.

6 . The method according to claim 5 , wherein inputs of the second network module are a received signal and environmental information outputted by the first network module, and an output of the second network module is a distribution parameter corresponding to the second distribution;
wherein the second distribution is a Gaussian distribution.

7 . The method according to claim 5 , wherein the target model further comprises:
a third network module, used to infer a distribution of an environmental tag corresponding to an environment where the user node is located; and a fourth network module, used to derive a distribution of a received signal; wherein an input of the third network module is an output of the first network module, and an input of the fourth network module is the output of the first network module.

8 . The method according to claim 7 , wherein a global loss function L of the target model is:

L
=

α
AE

⁢

L
AE

+

α
dist

⁢

L
dist

+

α
env

⁢

L
env

where α AE , α dist , α env are training hyperparameters, L AE is a loss function of the first network module and the fourth network module, L dist is a loss function of the second network module, and L env is a loss function of the third network module.

9 . The method according to claim 8 , wherein the loss function L AE of the first network module and the fourth network module is:

L
AE

(

r
;
θ

,
ϕ

)

=



r
-

r
ˆ

(

r
;
θ

,
ϕ

)

)



2

Assignees

• Guangdong Oppo Mobile Telecommunications Corp Ltd
• Univ Tsinghua

Inventors

• Shen Yuan
• Li Yuxiao
• Liu Yang
• Yu Xinlei
• Lu Qianxi
• Shi Cong

Classifications

• H04W64/00 Primary

  Locating users or terminals {or network equipment} for network management purposes, e.g. mobility management · CPC title