论文标题
Next-G O-Ran网络的AI测试框架：需求，设计和研究机会
AI Testing Framework for Next-G O-RAN Networks: Requirements, Design, and Research Opportunities
论文作者
论文摘要
开放性和智力是下一代无线网络中引入的两个能力，例如超越5G和6G，以支持服务异质性，打开硬件，最佳资源利用和按需服务部署。开放无线电访问网络（O-RAN）是通过虚拟化网络元素和明确定义的接口实现开放性和智能的有前途的架构。在O-Ran中部署人工智能（AI）模型变得更加容易时，长期以来一直忽略的一个重大挑战是对其在现实环境中的性能进行全面测试。本文介绍了一个通用的自动化，分布式和AI支持的测试框架，以测试O-RAN中部署的AI模型，以其决策性能，脆弱性和安全性。该框架采用了主操作架构来管理许多最终设备进行分布式测试。更重要的是，它利用AI自动而智能地探索O-RAN中AI模型的决策空间。支持软件仿真测试和软件定义的无线电硬件测试，从而可以快速的概念证明和无线研究平台实验研究。
Openness and intelligence are two enabling features to be introduced in next generation wireless networks, e.g. Beyond 5G and 6G, to support service heterogeneity, open hardware, optimal resource utilization, and on-demand service deployment. The open radio access network (O-RAN) is a promising RAN architecture to achieve both openness and intelligence through virtualized network elements and well-defined interfaces. While deploying artificial intelligence (AI) models is becoming easier in O-RAN, one significant challenge that has been long neglected is the comprehensive testing of their performance in realistic environments. This article presents a general automated, distributed and AI-enabled testing framework to test AI models deployed in O-RAN in terms of their decision-making performance, vulnerability and security. This framework adopts a master-actor architecture to manage a number of end devices for distributed testing. More importantly, it leverages AI to automatically and intelligently explore the decision space of AI models in O-RAN. Both software simulation testing and software-defined radio hardware testing are supported, enabling rapid proof of concept research and experimental research on wireless research platforms.
