IP Library Granted Patent US 12677227
Granted Patent B2
US 12677227 · App. 18/294,877 · Granted Jul 7, 2026

Method for performing federated learning in wireless communication system, and apparatus therefor

Inventors: Kijun Jeon (Seoul, KR); Sangrim Lee (Seoul, KR); Ikjoo Jung (Seoul, KR); Hojae Lee (Seoul, KR); Yeongjun Kim (Seoul, KR); Taehyun Lee (Seoul, KR)
Assignee: LG Electronics Inc.
H04W52/325H04L1/0063H04L41/16
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Quick Facts
Patent No.
US 12677227
App. No.
18/294,877
Granted
Jul 7, 2026
Kind
B2
Abstract

Proposed are a method for performing federated learning in a wireless communication system, and an apparatus therefor. The method performed by a terminal may comprise the steps of: generating a Q-ary code including i) a restriction-based system part and ii) a parity part by coding restriction-based Q-ary information; determining, on the basis of a preset method, the number T of transmissions of the parity part of the Q-ary code; on the basis of specific channel information from among channel information between a plurality of terminals and a base station participating in the federated learning, allocating power to the system part and T parity parts; and transmitting, on the basis of the allocated power, the system part and the T parity parts to the base station.

Claims (33)

1 . A method for performing federated learning in a wireless communication system, the method performed by a user equipment (UE) comprising:

generating a Q-ary code including i) a restriction-based system part and ii) a parity part by coding restriction-based Q-ary information;

determining a number of transmissions (T) of the parity part among the Q-ary code based on a preconfigured way;

allocating power to the system part and T parity parts based on specific channel information among channel information between a plurality of UEs and a base station participating in the federated learning; and

transmitting the system part and the T parity parts to the base station based on the allocated power.

2 . The method of claim 1 , wherein the number of transmissions (T) is determined based on available resources.

3 . The method of claim 1 , wherein a maximum number of the transmissions of the parity part is determined based on a Q-ary related value and a restriction-based Q-ary related value.

4 . The method of claim 3 , wherein the restriction-based Q-ary related value is determined based on at least one of channel state and/or a number of the plurality of UEs.

5 . The method of claim 1 , wherein the system part is modulated based on a modulation order different from the parity part.

6 . The method of claim 1 , further comprising:

receiving the specific channel information from the base station,

wherein the specific channel information is information about a channel with highest noise among channels between the plurality of UEs and the base station.

7 . A user equipment (UE) configured to perform federated learning in a wireless communication system, the UE comprising:

at least one transceiver;

at least one processor functionally connected to the at least one transceiver; and

at least one memory functionally connected to the at least one processor, and storing instructions for causing the at least one processor to perform operations,

wherein the operations includes:

generating a Q-ary code including i) a restriction-based system part and ii) a parity part by coding restriction-based Q-ary information;

determining a number of transmissions (T) of the parity part among the Q-ary code based on a preconfigured way;

allocating power to the system part and T parity parts based on specific channel information among channel information between a plurality of UEs and a base station participating in the federated learning; and

transmitting the system part and the T parity parts to the base station based on the allocated power.

8 . A method for performing federated learning in a wireless communication system, the method performed by a base station comprising:

receiving a system part and T parity parts from a user equipment (UE) based on allocated power,

wherein the system part and parity parts are generated by coding restriction-based Q-ary information,

wherein a number of transmissions (T) of the parity part is determined based on a preconfigured way, and

wherein the allocated power of the system part and T parity parts is determined based on specific channel information among channel information between a plurality of UEs and a base station participating in the federated learning.

9 . The method of claim 8 , wherein the number of transmissions (T) is determined based on available resources.

10 . The method of claim 8 , wherein a maximum number of the transmissions of the parity part is determined based on a Q-ary related value and a restriction-based Q-ary related value.

11 . The method of claim 10 , wherein the restriction-based Q-ary related value is determined based on at least one of channel state and/or a number of the plurality of UEs.

12 . The method of claim 8 , wherein the system part is modulated based on a modulation order different from the parity part.

13 . The method of claim 8 , further comprising:

transmitting the specific channel information to the UE,

wherein the specific channel information is information about a channel with highest noise among channels between the plurality of UEs and the base station.