US-20260129479-A1 - METHODS AND SYSTEMS FOR OPTIMIZING COMMUNICATION RELIABILITY IN A WIRELESS NETWORK

US20260129479A1US 20260129479 A1US20260129479 A1US 20260129479A1US-20260129479-A1

Abstract

Methods for optimizing communication reliability in a wireless network are provided. The method includes receiving a communication performance message from a network consumer entity. The method selects network producer entity for network consumer entity based on a local reliability table and global reliability table, wherein local reliability table comprises network producer entity for requested network consumer entity with a highest global reliability score and global reliability table includes network producer entity based on aggregated local reliability scores of all consumers. The method determines based on highest local reliability score among local reliability score of network producers available for requested network consumer entity in local reliability table and global reliability score of network producer entities not available for requested consumer entity in local reliability table. The method further updates final selection of network producer entity with network consumer entity, based on combination of global reliability table and local reliability table.

Inventors

Karthikeyan Subramaniam
Senthilkumar Subramanian
Sudhakar BALUSAMY
Akash DAYALAN
Nivedya Parambath SASI
Varini GUPTA

Assignees

SAMSUNG ELECTRONICS CO., LTD.

Dates

Publication Date: 20260507
Application Date: 20251107
Priority Date: 20251023

Claims (20)

1 . A method performed by a network repository entity for optimizing communication reliability in a wireless network, the method comprising: receiving, by the network repository entity, a communication performance message from a network consumer entity, wherein the communication performance message is related to a network producer entity; determining, by the network repository entity, a reliability score for the network producer entity, the reliability score including a local reliability score indicating a reliability between the network consumer entity and the network producer entity and a global reliability score indicating reliability of the network producer entity based on aggregated local reliability scores across a plurality of network consumer entities including the network consumer entity; selecting, by the network repository entity, a network producer entity having a highest global reliability score among a plurality of network producer entities based on a global reliability table, wherein the global reliability table comprises a plurality of global reliability scores of the plurality of network producer entities; determining, by the network repository entity, whether the selected network producer entity is compatible with the network consumer entity based on the local reliability table, wherein the local reliability table comprises a plurality of local reliability scores between each of the plurality of network producer entities and the network consumer entity.
2 . The method of claim 1 , wherein the method further comprises: based on determining that the selected network producer entity is compatible with the network consumer entity, updating, by the network repository entity, the selection of the network producer entity with the network consumer entity, for communicating with the network consumer entity, based on a combination of the global reliability table and the local reliability table.
3 . The method of claim 1 , wherein the reliability score is received, from a network data analytics function (NWDAF), for the network producer entity.
4 . The method of claim 1 , wherein the reliability score for the network producer entity is determined based on at least one of: the received communication performance message or historical communication data.
5 . The method of claim 1 , wherein the method further comprises: determining, by the network repository entity, that the local reliability table indicates a suboptimal reliability for the selected network producer entity, wherein an artificial intelligence (AI) module generates the suboptimal reliability for checking the local reliability table to the selected network producer entity; and discarding, by the network repository entity, the selected network producer entity to continue selecting another network producer entity with a next highest global reliability score.
6 . The method of claim 1 , wherein the method further comprises selecting, by the network repository entity, the network producer entity in an iterative process.
7 . The method of claim 1 , wherein the communication performance message comprises at least one of: a network producer profile information or a computed packet loss percentage between the network consumer entity and the network producer entity.
8 . The method of claim 5 , wherein the method further comprises: computing, by the network consumer entity, a packet loss percentage based on a number of retransmitted packets during communication between the network consumer entity and the network producer entity, and transmitting, by the network consumer entity, the computed packet loss percentage to the network repository entity through a notification, and wherein the notification comprises a network producer profile information and the computed packet loss percentage between the selected network consumer entity and the network producer entity.
9 . The method of claim 1 , wherein an artificial intelligence (AI) module is configured to compute the reliability score for the network producer entity based on historical communication data, and wherein the AI module generates the reliability score comprising the global reliability score and the local reliability score.
10 . The method of claim 1 , wherein the network repository entity comprises: receiving a network discovery request from the network consumer entity, queries the highest local score; identifying that the score is available, use the queried score for the network producer entity; and identifying that the score is not available in the local reliability table, performs comparison with other producers in the global reliability table.
11 . The method of claim 1 , wherein the method further comprises: comparing, by the network repository entity, the local reliability scores of the network producer entity that exist for requested network consumer entity in the local reliability table against the global reliability scores of network producer entities that do not exist for the requested network consumer entity in the local reliability table; and performing, by the network repository entity, the selection of the network producer entity with the highest reliability score based on the comparison.
12 . The method of claim 1 , wherein the method further comprises: ensuring, by the network repository entity, that an iterative process of querying the global reliability table and validating against the local reliability table to select appropriate network producer entity for the requesting network consumer entity based on the global reliability table and the local reliability table.
13 . The method of claim 12 , wherein the method further comprises: updating, by the network repository entity, the producer selection for the network consumer entity on completion of the iterative process, to facilitate reliability-aware pairing between the network consumer entity and the network producer entity.
14 . The method of claim 8 , wherein the AI module further comprises: a light gradient boosted machine (LightGBM) model configured to perform fast-path inference to generate reliability score; a graph neural network (GNN) configured to learn topological and contextual embeddings of network producer entity; and a temporal fusion transformer (TFT) configured to capture temporal dependencies and forecast reliability trends based on historical telemetry and feedback data.
15 . The method of claim 1 , wherein on detecting a failed communication session with the selected network producer entity, the network consumer entity is configured to transmit a service degraded notification to the network repository entity, and wherein the service degraded notification comprises at least one of: an indicating of a session failure, a packet loss percentage in the failed session, or a type of communication associated with the failed session.
16 . The method of claim 2 , wherein on receiving a service down notification from the network consumer entity, the network repository entity is configured to: update, by the NWDAF, a network producer profile status from a registered to a degraded state; generating, by the NWDAF, an updated reliability score for an affected network producer entity; update, by the NWDAF, a local reliability score table and a global reliability score table based on the notification; and update, by the NWDAF, a network producer profile on receiving multiple service down notifications from various network consumer entity.
17 . The method of claim 16 , wherein, in case of a failure, the network producer profile status is changed from registered to degraded.
18 . The method of claim 17 , wherein, when the network producer profile status is changed from registered to degraded, trigger recalculation of local and global reliability scores.
19 . A network repository entity, comprising: memory, comprising one or more storage media, storing instructions; a network repository controller; and one or more processors communicatively coupled with the network repository controller and the memory, wherein the instructions, when executed by the one or more processors individually or collectively, cause the network repository entity to: receive a communication performance message from a network consumer entity, wherein the communication performance message is related to a network producer entity, determine a reliability score for the network producer entity, the reliability score including a local reliability score indicating a reliability between the network consumer entity and the network producer entity and a global reliability score indicating reliability of the network producer entity based on aggregated local reliability scores across a plurality of network consumer entities including the network consumer entity, select a network producer entity having a highest global reliability score among a plurality of network producer entities based on a global reliability table, wherein the global reliability table comprises a plurality of global reliability scores of the plurality of network producer entities, determine whether the selected network producer entity is compatible with the network consumer entity based on the local reliability table, wherein the local reliability table comprises a plurality of local reliability scores between each of the plurality of network producer entities and the network consumer entity.
20 . One or more non-transitory computer-readable storage media storing one or more computer programs including computer-executable instructions that, when executed by one or more processors of a network repository entity individually or collectively, cause the network repository entity to perform operations, the operations comprising: receiving, by the network repository entity, a communication performance message from a network consumer entity, wherein the communication performance message is related to a network producer entity; determining, by the network repository entity, a reliability score for the network producer entity, the reliability score including a local reliability score indicating a reliability between the network consumer entity and the network producer entity and a global reliability score indicating reliability of the network producer entity across a plurality of network consumer entities including the network consumer entity; selecting, by the network repository entity, the reliability score including a local reliability score indicating a reliability between the network consumer entity and the network producer entity and a global reliability score indicating reliability of the network producer entity based on aggregated local reliability scores across a plurality of network consumer entities including the network consumer entity; determining, by the network repository entity, whether the selected network producer entity is compatible with the network consumer entity based on the local reliability table, wherein the local reliability table comprises a plurality of local reliability scores between each of the plurality of network producer entities and the network consumer entity.

Description

CROSS REFERENCE TO RELATED APPLICATION(S) This application is a continuation application, claiming priority under 35 U.S.C. § 365(c), of an International application No. PCT/KR2025/018036, filed on Nov. 5, 2025, which is based on and claims the benefit of an Indian Provisional patent application number 202441084755, filed on Nov. 5, 2024, in the Indian Intellectual Property Office, and of an Indian Complete patent application number 202441084755, filed on Oct. 23, 2025, in the Indian Intellectual Property Office, the disclosure of each of which is incorporated by reference herein in its entirety. TECHNICAL FIELD The disclosure relates to a wireless communication network. More particularly, the disclosure relates to methods and a network repository entity for optimizing communication reliability between a network producer entity and a network consumer entity using the network repository entity. BACKGROUND Currently, fifth-generation (5G) Ultra-Reliable Low-Latency Communication (URLLC) requires stringent end-to-end latency guarantees, ranging from 1 to 5 milliseconds as defined by the Third Generation Partnership Project (3GPP), to support mission-critical applications such as autonomous driving, industrial automation, remote surgery, and smart grid control. Achieving such low latency necessitates optimization across all segments of a wireless network (or wireless communication network), including a 5G Core (5GC). In modern 5GC deployments, a network producer entity and a network consumer entity (e.g., Access and Mobility Management Function (AMF) and Session Management Function (SMF)) may be instantiated within a data center or distributed across different data centers in a public cloud environment. Such distributed deployments introduce complex network paths between the network consumer entity and the network producer entity. The network consumer entity relies on a network repository entity to discover network producer entity using Network Function (NF) profiles, which indicate the availability and health status of network producer instances. However, the network profile may report the network producer instance as healthy even though the network consumer entity experiences network connectivity issues such as high latency, increased packet loss, or complete communication failure with that instance. The discrepancy can severely impact URLLC control signal establishment, leading to a failure in meeting stringent end-to-end latency Key Performance Indicators (KPIs). Hence, there is need of a mechanism whereby the network consumer entity detects such network-level issues in real time and proactively notifies the network repository entity to update the status of the affected network producer instance. Thus, enabling the subsequent network consumer instances to select alternative network producer instances, improving the packet delay budget by 47% for URLLC and 39% for Enhanced Mobile Broadband (eMBB) in the distributed 5GC (for example). FIG. 1A is an example graph illustrating the relevant key performance indicators (KPIs) of the uRLLC and the eMBB, comprising end-to-end Packet Delay Budget (PDB) and Packet Error Rate (PER) according to the related art. Referring to FIG. 1A, it illustrates the comparison between the current network producer discovery and a smart network producer discovery, with the differences in the PDB and the PER for 5G communication network. Therefore, currently no existing method is related to smart reliable network producer discovery and the reduction of C-P establishment time. Further, in the fifth generation (5G) core architecture, the network repository entity relies on heartbeat or status notifications from the network producer entity to assess the health of the network producer. Therefore, the limitations such in the delayed failure detection, if the network producer entity fails immediately after the last heartbeat, the network repository entity continues to advertise until the timeout period expires, so as to lead to failed communications from the network consumer entity. In other limitation, such as in the network path ignorance, the network may failure in a transport path about packet loss (for example) between the network consumer entity and the network producer entity go unnoticed, as the network repository entity has no visibility into transport-level failures. FIG. 1B is an example diagram illustrating the existing reliability gap in the 5G core according to the related art. Referring to FIG. 1B, the reliability in the 5G Service-Based Architecture (SBA) is a critical factor in ensuring compliance with Service Level Agreements (SLAs) and meeting Quality Flow Indicator (QFI) requirements across service categories such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communication (URLLC), and massive Machine Type Communication (mMTC). In the current design, Network Function (NF) producers periodically notify the Network Repository Function (NRF) about their stat