In this paper, we introduce a secure wireless agentic AI network comprising one supervisor AI agent and multiple other AI agents to provision quality of service (QoS) for users' reasoning tasks while ensuring confidentiality of private knowledge and reasoning outcomes. Specifically, the supervisor AI agent can dynamically assign other AI agents to participate in cooperative reasoning, while the unselected AI agents act as friendly jammers to degrade the eavesdropper's interception performance. To extend the service duration of AI agents, an energy minimization problem is formulated that jointly optimizes AI agent selection, base station (BS) beamforming, and AI agent transmission power, subject to latency and reasoning accuracy constraints. To address the formulated problem, we propose two resource allocation schemes, ASC and LAW, which first decompose it into three sub-problems. Specifically, ASC optimizes each sub-problem iteratively using the proposed alternating direction method of multipliers (ADMM)-based algorithm, semi-definite relaxation (SDR), and successive convex approximation (SCA), while LAW tackles each sub-problem using the proposed large language model (LLM) optimizer within an agentic workflow. The experimental results show that the proposed solutions can reduce network energy consumption by up to 59.1% compared to other benchmark schemes. Furthermore, the proposed schemes are validated using a practical agentic AI system based on Qwen, demonstrating satisfactory reasoning accuracy across various public benchmarks.
AINTMA: Agentic AI Architecture for Autonomous Test Management with Generative Intelligence, Secure Cloud Communication and Adaptive Quality Analytics
International Business Machines (IBM)（国际商业机器公司（IBM））；Global Atlantic Financial（全球大西洋金融公司）；Docusign（DocuSign公司）；Salesforce Inc（Salesforce公司）；The Home Depot（家得宝公司）
From Agentification to Self-Evolving Agentic AI for Wireless Networks: Concepts, Approaches, and Future Research Directions
College of Computing and Data Science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）；College of Computer Science and Technology, Jilin University（计算机科学与技术学院，吉林大学）；Department of Electrical and Computer Engineering, Western University（电气与计算机工程系，西方大学）；Department of Electrical and Computer Engineering, Auburn University（电气与计算机工程系，阿伯茨罕大学）；School of Electrical and Computer Engineering, University of Sydney（电气与计算机工程学院，悉尼大学）
Federated Agentic AI for Wireless Networks: Fundamentals, Approaches, and Applications
Research Center of 6G Mobile Communications, School of Cyber Science and Engineering, Huazhong University of Science and Technology（6G移动通信研究中心，信息科学与工程学院，华中科技大学）；College of Computing and Data Science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）；School of Engineering, Edith Cowan University（工程学院，埃迪斯·科文大学）；School of Computer Science and Engineering, University of New South Wales (UNSW)（计算机科学与工程学院，新南威尔士大学）；School of Electrical and Computer Engineering, University of Sydney（电气与计算机工程学院，悉尼大学）；Graduate School of Information Sciences, Tohoku University（信息科学研究生院，东北大学）
WirelessAgent++: Automated Agentic Workflow Design and Benchmarking for Wireless Networks
College of Electronics and Information Engineering, Shenzhen University（深圳大学电子与信息工程学院）；Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology（香港理工大学电子与计算机工程系）
Advanced Architectures Integrated with Agentic AI for Next-Generation Wireless Networks
Munster Technological University（穆斯廷技术大学）；School of Computing（计算学院）；Dublin City University（都柏林城市大学）；ADAPT Centre（ADAPT中心）；Centre Tecnològic de Telecomunicacions de Catalunya（加泰罗尼亚电信技术中心）；National Sun Yat-sen University（国立成功大学）；Khalifa University（哈利法大学）
本文提出面向下一代无线网络的先进架构，涵盖高效 6G 控制面与用户面、资源和能耗优化 AI 智能体、跨域无服务器后端编排，以及可将功耗降低一个数量级的高速低时延光交换架构。
Agentic TinyML for Intent-aware Handover in 6G Wireless Networks
Center for Ubiquitous Computing（无处不在计算中心）；University of Oulu（奥卢大学）；Department of Communication Systems（通信系统系）；EURECOM；Department of Computer Science（计算机科学系）；University of Helsinki（赫尔辛基大学）；RISE Research Institutes of Sweden（瑞典研究机构）；Department of Computer Science, Electrical and Space Engineering（计算机科学、电气与空间工程系）；Luleå University of Technology（卢勒奥技术大学）
Large AI Model-Enabled Secure Communications in Low-Altitude Wireless Networks: Concepts, Perspectives and Case Study
College of Computer Science and Technology, Jilin University（吉林大学计算机科学与技术学院）；Singapore University of Technology and Design（新加坡科技设计大学）；College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University（吉林大学计算机科学与技术学院、教育部符号计算与知识工程重点实验室）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算机与数据科学学院）
