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智能体 arxiv.org ·

Agentic RDZ:利用 AI 智能体实现自主区域管理及 FR3 共存用例

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该论文提出 A-RDZ,据作者称是首个由 LLM 智能体执行频谱管理、实验管理、策略解释和区域编排的 Radio Dynamic Zones 实现,基于 GENESIS 智能体框架,将自主推理与确定性策略门及近实时反射机制结合,使智能体可改善结果但不削弱区域保护保证。作者在 FR3(7.125-24.25 GHz)O-RAN 硬件在环测试台上验证,5G NR 实验与模拟 FSS 地球站共存;端到端用例中监控智能体从实时频谱证据检测到发射违规,编排器选择缓解措施恢复干扰预算并保持实验运行,动作经 O-RAN 控制面应用并验证。论文报告了检测到缓解的延迟分解,并讨论了智能体运行的实际限制,包括非确定性推理和决策到动作的翻译。

AI推荐理由 arXiv 论文(cs.NI),作者来自东北大学等机构,摘要信息密度高、方法描述具体。核心新信息是提出 A-RDZ:首个用 LLM 智能体执行频谱管理、实验管理、策略解释与区域编排的 Radio Dynamic Zones 实现,基于 GENESIS 智能体框架,将自主推理与确定性策略门和近实时反射机制结合,声称智能体可改善结果但不会削弱保护保证。在 FR3(7.125-24.25 GHz)O-RAN 硬件在环测试台上验证,5G NR 实验与模拟 FSS 地球站共存,端到端用例中监控智能体从实时频谱证据检测到发射违规,编排器选择缓解措施恢复干扰预算并保持实验运行,经 O-RAN 控制面应用和验证,并报告检测到缓解的延迟分解。局限:论文自述智能体运行的实际限制,包括非确定性推理和决策到动作的翻译问题;摘要未给出量化性能数据,效果需看全文。

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Computer Science > Networking and Internet Architecture arXiv:2609.17110 (cs) [Submitted on 15 Sep 2026] Title:Agentic RDZ: Autonomous Zone Management with AI Agents and an FR3 Coexistence Use Case Authors:Minh Dat Nguyen, Gabriele Gemmi, Tamerlan Aghayev, Paolo Testolina, Michele Polese, Tommaso Melodia View a PDF of the paper titled Agentic RDZ: Autonomous Zone Management with AI Agents and an FR3 Coexistence Use Case, by Minh Dat Nguyen and 5 other authors View PDF HTML (experimental) Abstract:Radio Dynamic Zones (RDZs) allow wireless experiments to operate outside conventional spectrum regulations while continuously guaranteeing protection for incumbent users. Existing RDZ prototypes automate this task procedurally, through handcrafted rules and predefined workflows, and become brittle when experiments encounter hardware impairments, user workflows and devices, or interference mechanisms not anticipated at design time. This paper introduces the agentic RDZ (A-RDZ), which, to the best of our knowledge, is the first RDZ realization in which agents use Large Language Models (LLMs) to perform spectrum management, experiment management, policy interpretation, and zone orchestration. Built on the GENESIS agentic framework, the architecture pairs autonomous reasoning with a deterministic policy gate and near-real-time (near-RT) reflexes, so that agents can improve outcomes but never weaken the zone's protection guarantee. We validate the A-RDZ on a hardware-in-the-loop Frequency Range 3 (FR3) (7.125-24.25 GHz) Open Radio Access Network (O-RAN) testbed in which a 5G New Radio (NR) experiment coexists with an emulated Fixed Satellite Service (FSS) earth-station incumbent. In an end-to-end use case, the monitoring agent detects an emission violation from live spectrum evidence, the orchestrator selects a mitigation that restores the interference budget while keeping the experiment running, and the action is applied and verified through the O-RAN control plane. We report the detection-to-mitigation latency decomposition and discuss the practical limits of agentic operation, including non-deterministic reasoning and decision-to-action translation. Subjects: Networking and Internet Architecture (cs.NI) Cite as: arXiv:2609.17110 [cs.NI] (or arXiv:2609.17110v1 [cs.NI] for this version) https://doi.org/10.48550/arXiv.2609.17110 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Minh Dat Nguyen [view email] [v1] Tue, 15 Sep 2026 12:40:25 UTC (31 KB) Full-text links: Access Paper: View a PDF of the paper titled Agentic RDZ: Autonomous Zone Management with AI Agents and an FR3 Coexistence Use Case, by Minh Dat Nguyen and 5 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.NI new | recent | 2026-09 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

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