Next-Generation 6G Network Management with OSS-GPT

In the 6G era, the Management and Orchestration (MANO) layer must become more intelligent to support advanced use cases with stringent Quality of Service (QoS) requirements. These often span multiple domains, terrestrial, non-terrestrial, and edge, requiring efficient coordination across heterogeneous networks. To meet these demands, Mobile Network Operators (MNOs) are evolving their Operations Support Systems (OSS) toward a "network of networks" vision, built on standardized and interoperable APIs. Standards bodies such as 3GPP, ETSI, and TM Forum are addressing this by developing numerous OSS API specifications and intent-based request models in JSON or YAML. However, creating these intents remains challenging for users without deep domain knowledge. We present OSS-GPT, an agentic AI framework that enables users to interact with OSSs via natural language. By leveraging Large Language Models (LLMs), OSS-GPT translates high-level intents into executable sequences of OSS API calls and automates their execution.

Authors

Institutions

Publication Details

Published
2025-09-08
DOI
https://doi.org/10.1145/3744969.3748429
Citations
1
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
1.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Next-Generation 6G Network Management with OSS-GPT

Christos Verikoukis, Abdelkader Mekrache, Adlen Ksentini
1 citations
Distributed and Parallel Computing Systems
1.49
article

Next-Generation 6G Network Management with OSS-GPT

Christos Verikoukis, Abdelkader Mekrache, Adlen Ksentini
article en
1 citations

Abstract

In the 6G era, the Management and Orchestration (MANO) layer must become more intelligent to support advanced use cases with stringent Quality of Service (QoS) requirements. These often span multiple domains, terrestrial, non-terrestrial, and edge, requiring efficient coordination across heterogeneous networks. To meet these demands, Mobile Network Operators (MNOs) are evolving their Operations Support Systems (OSS) toward a "network of networks" vision, built on standardized and interoperable APIs. Standards bodies such as 3GPP, ETSI, and TM Forum are addressing this by developing numerous OSS API specifications and intent-based request models in JSON or YAML. However, creating these intents remains challenging for users without deep domain knowledge. We present OSS-GPT, an agentic AI framework that enables users to interact with OSSs via natural language. By leveraging Large Language Models (LLMs), OSS-GPT translates high-level intents into executable sequences of OSS API calls and automates their execution.

University of Patras (GR), EURECOM (FR), Industrial Systems Institute (GR)
Openalex Percentile: Top 13%
Distributed and Parallel Computing Systems
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.