Communication method, network node, storage medium, and program product

Patent metadata

Field	Value
Publication number	US-2025132868-A1
Application number	US-202418899775-A
Country	US
Kind code	A1
Filing date	Sep 27, 2024
Priority date	Oct 20, 2023
Publication date	Apr 24, 2025
Grant date	—

Abstract

Embodiments of the present disclosure provide a communication method, a network node, a storage medium and a program product, and relate to fields such as communication and artificial intelligence. In an example method, a first network node determines a first retransmission UE, determines an MU pairing recommendation result using a first AI network based on the first retransmission UE, and transmits the MU pairing recommendation result to a second network node, so that the computation of MU scheduling of the second network node can be assisted, and the computation complexity of MU scheduling of the second network node can be reduced. Optionally, the method performed by a network node can be performed by an artificial intelligence mode

First claim

What is claimed is:

1 . A method performed by a first network node in a communication system, comprising:
identifying a first retransmission user equipment (UE); identifying information on a multi-user (MU) pairing recommendation result using a first artificial intelligence (AI) network based on the first retransmission UE; and transmitting the information on the MU pairing recommendation result to a second network node.

2 . The method according to claim 1 , wherein the identifying a first retransmission UE comprises:
determining a retransmission probability of at least one UE; and identifying a first retransmission UE based on the retransmission probability of the at least one UE.

3 . The method according to claim 2 , wherein the determining the retransmission probability of at least one UE comprises:
determining the retransmission probability of the at least one UE according to historical MU pairing recommendation results and a target block error rate.

4 . The method according to claim 3 , wherein the determining the retransmission probability of the at least one UE according to historical MU pairing recommendation results and a target block error rate comprises:
determining the number of times of using the at least one UE as initial transmission in the historical MU pairing recommendation results; determining the retransmission probability of initial transmission based on the target block error rate; and determining the retransmission probability of the at least one UE based on the number of times of the initial transmission and the retransmission probability of the initial transmission.

5 . The method according to claim 2 , wherein the determining a first retransmission UE based on the retransmission probability of the at least one UE comprises:
determining a retransmission validity threshold corresponding to the at least one UE; and determining a first retransmission UE based on the retransmission probability of the at least one UE and the retransmission validity threshold corresponding to the at least one UE.

6 . The method according to claim 5 , wherein the determining a retransmission validity threshold corresponding to the at least one UE comprises:
determining the retransmission validity threshold corresponding to the at least one UE according to historical scheduling information.

7 . The method according to claim 6 , wherein the determining a retransmission validity threshold corresponding to the at least one UE according to historical scheduling information comprises:
determining a historical MU pairing recommendation result validity metric according to the historical scheduling information, the MU pairing recommendation result validity metric being used to measure a validity of retransmission UEs in the historical MU pairing recommendation results; and determining, according to the historical MU pairing recommendation result validity metric and using a second AI network, a retransmission validity threshold corresponding to at least one UE in each first time unit set in a current period.

8 . The method according to claim 7 , wherein the each first time unit set comprises at least one first time unit in which hybrid automatic repeat request (HARQ) feedback is performed on a same continuous uplink second time unit.

9 . The method according to claim 6 , wherein the historical scheduling information comprises at least one of the following:
an MU-scheduled first time unit; a first time unit in which the second network node determines the MU pairing recommendation result; a first time unit in which the second network node uses the MU pairing recommendation result provided by the first network node; an actual usage condition of the MU pairing recommendation result provided by the first network node by the second network node in each first time unit set of the historical period; and the number of first time units MU-scheduled by the second network node in each first time unit set of the historical period.

10 . The method according to claim 6 , wherein the identifying a first retransmission UE based on the retransmission probability of the at least one UE and the retransmission validity threshold corresponding to the at least one UE comprises:
identifying a first retransmission UE based on a comparison result of the retransmission probability of the at least one UE and the retransmission validity threshold corresponding to the at least one UE.

11 . The method according to claim 10 , wherein the identifying a first retransmission UE based on a comparison result of the retransmission probability of the at least one UE and the retransmission validity threshold corresponding to the at least one UE comprises:
sorting the at least one UE in an order from smallest to largest retransmission probabilities; performing on the sorted at least one UE until a target UE is determined: determining a cumulative retransmission probability of a UE and UEs before this UE, determining the corresponding retransmission validity probability based on the cumulative retransmission probability, and determining this UE as a target UE based on the retransmission validity probability being less than the retransmission validity threshold; and identifying the target UE and UEs after the target UE as first retransmission UEs.

12 . The method according to claim 1 , wherein the identifying the information on the MU pairing recommendation result using the first AI network based on the first retransmission UE comprises:
determining at least one candidate UE according to the amount of data to be transmitted of UEs and measurement configuration information; and identifying information on the MU pairing recommendation result using the first AI network based on the first retransmission UE and the at least one candidate UE.

13 . The method according to claim 12 , wherein the determining at least one candidate UE according to the amount of data to be transmitted of UEs and measurement configuration information comprises:
determining at least one candidate UE according to the amount of data to be transmitted of UEs, the measurement configuration information and a UE scheduling parameter; wherein the UE scheduling parameter is determined according to the number of first time units in which UEs satisfy a specified condition in a specified period of time including a plurality of first time units.

14 . The method according to claim 12 , wherein the determining at least one candidate UE according to the amount of data to be transmitted of UEs and measurement configuration information comprises:
determining initial candidate UEs; and deleting, from the initial candidate UEs, candidate UEs whose amount of data to be transmitted is less than a first threshold, and deleting, from the initial candidate UEs, candidate UEs in measurement gaps according to the measurement configuration information, to obtain at least one candidate UE.

15 . The method according to claim 13 , wherein the determining at least one candidate UE according to the amount of data to be transmitted of UEs, the measurement configuration information and a UE scheduling parameter comprises:
determining initial candidate UEs; and deleting, from the initial candidate UEs, candidate UEs whose amount of data to be transmitted is less than a first threshold, deleting, from the initial candidate UEs, candidate UEs in measurement gaps according to the measurement configuration information, and sorting the initial candidate UEs according to the UE scheduling parameter and/or deleting, from the initial candidate UEs, candidate UEs whos

Assignees

• Samsung Electronics Co Ltd

Inventors

• Zhou Xin
• Li Honghong
• Ren Junwei
• Zhu Ying
• Wang Zhigang
• Cao Nan

Classifications

• H04L1/1812

  Hybrid protocols; Hybrid automatic repeat request [HARQ] · CPC title

• H04L1/1887 Primary

  Scheduling and prioritising arrangements · CPC title

• H04W24/10

  Scheduling measurement reports {; Arrangements for measurement reports} · CPC title

• H04L41/16 Primary

  using machine learning or artificial intelligence · CPC title

• H04L2001/0093

  Point-to-multipoint · CPC title