13 citations · 41 across the 26 of their papers we have counts for
28 papers
DeepTelecom: A Differentiable Multimodal Framework for Channel Twinning in Dynamic Heterogeneous Wireless Environments
Bohao Wang, Tianen Yuan, William Yen +12
Large-scale multimodal data are a key enabler for integrating large generative artificial intelligence models into wireless networks. However, existing wireless datasets offer limi…
RF-Agent: Hierarchical Language-Agent Control for Instruction-Conditioned Active Spectrum Sensing
Hao Zhang, Dongfang Xu, Hang Zou +7
Active radio-frequency (RF) sensing must acquire evidence under receiver limits while following confirmation, recovery, and stopping instructions. \newhl{We propose RF-Agent, a clo…
TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Tasks
Bohao Wang, Chenwei Wu, Hang Zou +7
Large language models (LLMs) offer great potential to automate a broad range of telecom engineering tasks by reasoning over standards, network configurations, mathematical models,…
OTel: Building Domain-Specialized Telecom LLM Foundations for Intelligent Networks
Farbod Tavakkoli, Roderic Paulk, Jorden Terrazas +9
Frontier AI models have advanced rapidly, but they still struggle with telecom-specific tasks. We present Open Telco (OTel), an open telecom AI resource with derived datasets for r…
A JEPA-Based Field-Layer World Model for Bridging Channel Prediction and Estimation
Yuzhi Yang, Brahim Mefgouda, Hang Zou +5
Channel state information (CSI) acquisition, reconstruction, and prediction are fundamental yet costly tasks in modern MIMO-OFDM wireless systems. Direct coefficient-level predicti…
TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stack
Bohao Wang, Chenwei Wu, Haoyu Li +8
Telecommunications is a high-leverage domain for large language model (LLM)-based reasoning because routine engineering workflows require joint grounding in normative specification…
LLM-Based Digital Twin Intelligence for Application-Aware Network Selection in 6G Heterogeneous Wireless Networks
Brahim Mefgouda, Anis Bara, Lina Bariah +3
Future 6G heterogeneous wireless networks (HWNs) are expected to support multiple radio access technologies (RATs), dynamic wireless environments, and applications with diverse qua…
SEM-RAG: Structure-Preserving Multimodal Graph Compilation and Entropy-Guided Retrieval for Telecommunication Standards
Yuzhi Yang, Lina Bariah, Yuhuan Lu +2
Telecommunication standards pose a unique challenge for retrieval systems, where accuracy depends on semantic relevance as well as on preserving the structural logic embedded in th…
RF-Analyzer: Can Vision-Language Models Learn RF Understanding from Synthetic Data?
Anis Bara, Lina Bariah, Hang Zou +2
Understanding the wireless spectrum is a fundamen- tal requirement for intelligent communication systems, however, interpreting spectrograms requires extracting multiple physical a…
Telecom World Models: Unifying Digital Twins, Foundation Models, and Predictive Planning for 6G
Hang Zou, Yuzhi Yang, Lina Bariah +15
The integration of machine learning tools into telecom networks, has led to two prevailing paradigms, namely, language-based systems, such as Large Language Models (LLMs), and phys…
Diffusion-Based Generative Priors for Efficient Beam Alignment in Directional Networks
Esraa Fahmy Othman, Lina Bariah, Merouane Debbah
Beam alignment is a key challenge in directional mmWave and THz systems, where narrow beams require accurate yet low-overhead training. Existing learning-based approaches typically…
TelcoAgent-Bench: A Multilingual Benchmark for Telecom AI Agents
Lina Bariah, Brahim Mefgouda, Farbod Tavakkoli +3
The integration of large language model (LLM) agents into telecom networks introduces new challenges, related to intent recognition, tool execution, and resolution generation, whil…
RF-GPT: Teaching AI to See the Wireless World
Hang Zou, Yu Tian, Bohao Wang +4
Large language models (LLMs) and multimodal models have become powerful general-purpose reasoning systems. However, radio-frequency (RF) signals, which underpin wireless systems, a…
Seeing Radio: From Zero RF Priors to Explainable Modulation Recognition with Vision Language Models
Hang Zou, Bohao Wang, Yu Tian +4
Current RF machine-learning pipelines rely on task-specific deep networks for modulation classification and related tasks, but these models require custom architectures and labeled…
MX-AI: Agentic Observability and Control Platform for Open and AI-RAN
Ilias Chatzistefanidis, Andrea Leone, Ali Yaghoubian +5
Future 6G radio access networks (RANs) will be artificial intelligence (AI)-native: observed, reasoned about, and re-configured by autonomous agents cooperating across the cloud-ed…
Advancing THz Radio Map Construction and Obstacle Sensing: An Integrated Generative Framework in ISAC
Tianyu Hu, Shuai Wang, Yunhang Xie +7
Integrated sensing and communication (ISAC) in the terahertz (THz) band enables obstacle detection, which in turn facilitates efficient beam management to mitigate THz signal block…
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…
Goal-Oriented State Information Compression for Linear Dynamical System Control
Li Wang, Chao Zhang, Samson Lasaulce +2
In this paper, we consider controlled linear dynamical systems in which the controller has only access to a compressed version of the system state. The technical problem we investi…
TelecomGPT: A Framework to Build Telecom-Specfic Large Language Models
Hang Zou, Qiyang Zhao, Yu Tian +4
Large Language Models (LLMs) have the potential to revolutionize the Sixth Generation (6G) communication networks. However, current mainstream LLMs generally lack the specialized k…
Large Language Models for Power Scheduling: A User-Centric Approach
Thomas Mongaillard, Samson Lasaulce, Othman Hicheur +6
While traditional optimization and scheduling schemes are designed to meet fixed, predefined system requirements, future systems are moving toward user-driven approaches and person…
Generative AI for Immersive Communication: The Next Frontier in Internet-of-Senses Through 6G
Nassim Sehad, Lina Bariah, Wassim Hamidouche +3
Over the past two decades, the Internet-of-Things (IoT) has become a transformative concept, and as we approach 2030, a new paradigm known as the Internet of Senses (IoS) is emergi…
GenAINet: Enabling Wireless Collective Intelligence via Knowledge Transfer and Reasoning
Hang Zou, Qiyang Zhao, Samson Lasaulce +3
Generative Artificial Intelligence (GenAI) and communication networks are expected to have groundbreaking synergies for 6G. Connecting GenAI agents via a wireless network can poten…
Wireless Multi-Agent Generative AI: From Connected Intelligence to Collective Intelligence
Hang Zou, Qiyang Zhao, Lina Bariah +2
The convergence of generative large language models (LLMs), edge networks, and multi-agent systems represents a groundbreaking synergy that holds immense promise for future wireles…
Digital Twin-Empowered Communications: A New Frontier of Wireless Networks
Lina Bariah, Hikmet Sari, Merouane Debbah
The future of wireless network generations is revolving toward unlocking the opportunities offered by virtualization and digitization services, with the aim to realize improved qua…