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Ke-Zhi Wang

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Open access 2026

Disturbance-Resilient Agentic AI Control for Age-Fair SPS in 5G V2I Networks

In fifth-generation (5G) New Radio (NR) vehicle-to-infrastructure (V2I) networks, semi-persistent scheduling (SPS) reduces signaling but may retain an unsuitable resource reservation interval (RRI) after the local load changes. We study age-fair keep/reselect control and distinguish a reward-aligned age-fair utility (R...

Jun-Cheng Bai, Qiong Wu, Ke-Zhi Wang et al. · 0 citations
Open access 2026

Agentic TokenCom: A Chain-of-Agents Framework for Multimodal Token Communications

In 6G networks, existing semantic communication systems struggle to achieve composable and generalizable end-to-end optimization under dynamic channel conditions and heterogeneous resource constraints. To address this challenge, we propose Agentic Token Communication (TokenCom), a hierarchical Chain-of-Agents autonomou...

Fei-Bo Jiang, Lei Mao, Li Dong et al. · 0 citations
Review 2026

From LLMs to Agentic and Embodied AI for Next-Generation Intelligent Vehicular Communications: A Comprehensive Survey

The internet of vehicles (IoV) is rapidly evolving into an artificial intelligence (AI)-driven, multi-agent collaborative ecosystem, yet traditional communication paradigms struggle to address the challenges posed by dynamic network topologies, stringent resource constraints, and heterogeneous service demands. To bridg...

Qiong Wu, Wen-Jun Zhang, Ping-Yi Fan et al. · 5 citations
Conference Aug 2026

Double-RIS-Aided Secure and Covert Communications for Symbiotic Radio Systems

In this paper, we propose a double-cooperative reconfigurable intelligent surfaces (RIS)-aided secure and covert framework in symbiotic radio (SR) systems in the presence of an eavesdropper and a warden. In particular, one RIS is deployed to establish the primary communication link, while another backscatter device (BD...

Alemayehu Kebede Abebe, Yi Zhou, Zheng Ma et al. · 0 citations
Open access 2026

Optimizing Federated Learning Efficiency via Slimmable Neural Networks and AirComp for Resource-Heterogeneous Devices

The Air-FedSNN framework, which integrates slimmable neural networks (SNNs) with over-the-air computation (AirComp) to improve communication, computation, and energy efficiency in heterogeneous IoT networks, and provides an efficient solution for resource-constrained environments.

Yue Zhang, Guopeng Zhang, Ke-Zhi Wang et al. · 0 citations
Aug 2026

LLM-enhanced-EA-driven automated optimization framework for joint indoor deployment of multiple BSs and RISs

This work uses the large language model (LLM)-enhanced non-dominated sorting genetic algorithm II (NSGA-II) to directly solve the bi-objective optimization problem, assisted by an LLM to enhance its concentrated exploration capability by extending the exploration in language space.

Si-Chong Liao, Jin-Bo Hou, Yi Zhao et al. · 1 citation
Jul 2026

Can We Trust AI in 6G? Verifiable and Auditable AI-Driven Trustworthy Wireless Networks

A general three-step auditing principle is set out that locates protocol-relevant features, verifies their causal role, and diagnoses how adaptation reshapes their use, grounding it throughout publicly available interpretability and telecommunications research.

Genze Jiang, Yizhou Huang, Ke-Zhi Wang · 0 citations

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