5 citations · 9 across the 13 of their papers we have counts for
14 papers
Agents That Model Agents: Five Principles Toward a Theory of Mind for 6G Networks
Hatim Chergui, Carolina Fernández-Martínez, Mehdi Bennis +1
Future 6G networks will rely on Large Language Model (LLM) agents to manage the Radio Access Network (RAN). However, current architectures assume inter-agent messages convey object…
Electromagnetic Neural Network for Direction-of-Arrival Estimation
Shining Lin, Jiancheng An, Lu Gan +4
Accurate and real-time direction of arrival (DOA) estimation is crucial for beamforming in unmanned aerial vehicle (UAV) communication systems. However, the existing high-precision…
Distributed Electromagnetic Neural Networks for Task-Oriented Semantic Communications
Jinbao Li, Jiancheng An, Hao Liu +4
Semantic communications (SemCom) is a promising paradigm that prioritizes the transmission of task-relevant information, thereby enabling superior communication efficiency over tra…
Stacked Intelligent Metasurface-Aided Wave-Domain Signal Processing: From Communications to Sensing and Computing
Jiancheng An, Chau Yuen, Marco Di Renzo +3
Artificial neural networks possess remarkable capabilities for abstract feature extraction, while electromagnetic computing leverages wave propagation to execute complex mathematic…
LiQSS: Post-Transformer Linear Quantum-Inspired State-Space Tensor Networks for Real-Time 6G
Farhad Rezazadeh, Hatim Chergui, Amir Ashtari Gargari +4
Proactive and agentic control in Sixth-Generation (6G) Open Radio Access Networks (O-RAN) requires control-grade prediction under stringent Near-Real-Time (Near-RT) latency and com…
Compositional Distributed Learning for Multi-View Perception: A Maximal Coding Rate Reduction Perspective
Zhuojun Tian, Mehdi Bennis
In this letter, we formulate a compositional distributed learning framework for multi-view perception by leveraging the maximal coding rate reduction principle combined with subspa…
LLM-Based Agentic Negotiation for 6G: Addressing Uncertainty Neglect and Tail-Event Risk
Hatim Chergui, Farhad Rezazadeh, Mehdi Bennis +2
A critical barrier to the trustworthiness of sixth-generation (6G) agentic autonomous networks is the uncertainty neglect bias; a cognitive tendency for large language model (LLM)-…
Active Inference Framework for Closed-Loop Sensing, Communication, and Control in UAV Systems
Guangjin Pan, Liping Bai, Zhuojun Tian +3
Integrated sensing and communication (ISAC) is a core technology for 6G, and its application to closed-loop sensing, communication, and control (SCC) enables various services. Exis…
Communication-Efficient Personalized Distributed Learning with Data and Node Heterogeneity
Zhuojun Tian, Zhaoyang Zhang, Yiwei Li +1
To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis (DSLTH), based on which a commu…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
The Rendezvous Between Extreme Value Theory and Next-generation Networks
Srinivas Sagar, Athira Subhash, Chen-Feng Liu +6
Promising technologies such as massive multiple-input and multiple-output, reconfigurable intelligent reflecting surfaces, non-terrestrial networks, millimetre wave communication,…
Zero-Shot Generalization for Blockage Localization in mmWave Communication
Rafaela Scaciota, Malith Gallage, Sumudu Samarakoon +1
This paper introduces a novel method for predicting blockages in millimeter-wave (mmWave) communication systems towards enabling reliable connectivity. It employs a self-supervised…
Stacked Intelligent Metasurfaces for Task-Oriented Semantic Communications
Guojun Huang, Jiancheng An, Zhaohui Yang +3
Semantic communication (SemCom) leveraging advanced deep learning (DL) technologies enhances the efficiency and reliability of information transmission. Emerging stacked intelligen…
Stacked Intelligent Metasurfaces for Wireless Communications: Applications and Challenges
Hao Liu, Jiancheng An, Xing Jia +6
The rapid growth of wireless communications has created a significant demand for high throughput, seamless connectivity, and extremely low latency. To meet these goals, a novel tec…