Toward Experimentation-as-a-Service in 5G/6G: The Plaza6G Prototype for AI-Assisted Trials

2026-03-17

AI Summary

This work addresses the high complexity, poor reproducibility, and lack of a unified Experimentation-as-a-Service (ExaS) environment in existing 5G/6G wireless testbeds by introducing Plaza6G—the first integrated ExaS platform combining open-source and commercial 5G core networks, a programmable radio access network (RAN), and an AI-driven natural language interface. Plaza6G integrates GPU-accelerated clusters, multiple core networks (Free5GC and Cumucore), and sub-6GHz/mmWave dual-site over-the-air (OTA) testing capabilities. It features an intelligent experimentation assistant built upon LLM, RAG, and LoRA techniques to support machine-readable experiment specifications. The platform enables fully automated CI/CD deployment within ten minutes, facilitating low-barrier, reproducible, and interactive wireless experimentation, thereby laying the groundwork for future federated testbeds and policy-aware orchestration.

Technology Category

• Planning, Routing, and Scheduling: Planning with Language Models
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

This paper presents Plaza6G, the first operational Experiment-as-a-Service (ExaS) platform unifying cloud resources with next-generation wireless infrastructure. Developed at CTTC in Barcelona, Plaza6G integrates GPU-accelerated compute clusters, multiple 5G cores, both open-source (e.g., Free5GC) and commercial (e.g., Cumucore), programmable RANs, and physical or emulated user equipment under unified orchestration. In Plaza6G, the experiment design requires minimal expertise as it is expressed in natural language via a web portal or a REST API. The web portal and REST API are enhanced with a Large Language Model (LLM)-based assistant, which employs retrieval-augmented generation (RAG) for up-to-date experiment knowledge and Low-Rank Adaptation (LoRA) for continuous domain fine-tuning. Over-the-air (OTA) trials leverage a four-chamber anechoic facility and a dual-site outdoor 5G network operating in sub-6~GHz and mmWave bands. Demonstrations include automated CI/CD integration with sub-ten-minute setup and interactive OTA testing under programmable propagation conditions. Machine-readable experiment descriptors ensure reproducibility, while future work targets policy-aware orchestration, safety validation, and federated testbed integration toward open, reproducible wireless experimentation.

Problem

• Experimentation-as-a-Service
• 5G/6G
• wireless experimentation
• reproducibility
• AI-assisted trials

Innovation

• Experimentation-as-a-Service
• AI-assisted orchestration
• Large Language Model (LLM)
• Retrieval-Augmented Generation (RAG)
• Low-Rank Adaptation (LoRA)