activity
20242026
most citedRobust Deep Learning-Based Physical Layer Communications: Strategies and Approaches

7 citations · 15 across the 13 of their papers we have counts for

collaborators

19 papers

cs.CL2026

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…

cs.IT2026

QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks

Zhihan Zeng, Kaihe Wang, Zhongpei Zhang +1

Static radio maps provide location-dependent propagation priors, but they cannot capture short-term blockage caused by moving objects. Direct sensing-assisted beam prediction is al…

eess.SP2026

Full-Domain Coupler: A Wireless Native Neural Backbone for Channel Representation and Deduction

Zirui Chen, Ziqing Xing, Zhaoyang Zhang +5

Data representation is a fundamental issue in deep learning. However, as wireless data scales and deeply couples across many physical domains such as time, space, and frequency, ex…

eess.SP2026

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…

eess.SP20267 cited

Physics-Inspired Target Shape Detection and Reconstruction in mmWave Communication Systems

Ziqing Xing, Zhaoyang Zhang, Xin Tong +2

The integration of sensing and communication (ISAC) is an essential function of future wireless systems. Due to its large available bandwidth, millimeter-wave (mmWave) ISAC systems…

cs.IT2026

One-Step Generative Channel Estimation via Average Velocity Field

Zehua Jiang, Fenghao Zhu, Siming Jiang +5

Generative models have shown immense potential for wireless communication by learning complex channel data distributions. However, the iterative denoising process associated with t…