Foundation Model Empowered Autonomous Network Management for QoS Optimization in 5G-Advanced and 6G Networks
Keywords:
foundation models, autonomous network management, quality of service, 5G-Advanced, 6G, network slicing, governance, sustainabilityAbstract
The move from fifth-generation advanced (5G-Advanced) systems to sixth-generation (6G) networks is predicated on hyper-specialised performance envelopes that demand granular, real-time quality of service (QoS) guarantees across extremely heterogeneous service classes. Traditional and even deep reinforcement learning based management approaches, while effective in narrow slices, encounter fundamental brittleness when confronted with domain shift, novel service descriptors, or the combinatorial complexity of multi-objective resource allocation in open multi-vendor environments. Foundation models, large-scale pre-trained neural architectures that acquire broad representational capabilities from vast and diverse data modalities, offer a paradigm shift toward generalist intelligence in autonomous network management. This paper presents a system-level architectural framework that embeds foundation models as the cognitive nuclei of closed-loop control, enabling intent-driven reasoning, cross-domain policy transfer, and anticipatory QoS assurance without exhaustive per-slice retraining. We examine the structural trade-offs that arise when unifying language-based policy interfaces, vision-based radio environment maps, and time-series telemetry through a shared model backbone, and we dissect the concomitant challenges of inference latency, energy consumption, and model governance. The discussion extends to fairness, accountability, and transparency in AI-driven resource allocation, as well as the deployment pathways that balance centralised model hosting against distributed inference at the network edge. By synthesising advances in model compression, retrieval-augmented generation, and responsible AI frameworks, we articulate a roadmap for foundation model empowered autonomous networks that are robust, sustainable, and aligned with the regulatory and ethical imperatives of the 6G era.
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This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
