Publications (12)
Multi-hop Parallel Image Semantic Communication for Distortion Accumulation Mitigation
Bingyan Xie, Jihong Park, Yongpeng Wu +2
Existing semantic communication schemes primarily focus on single-hop scenarios, overlooking the challenges of multi-hop wireless image transmission. As semantic communication is i…
Towards Sustainability in 6G and beyond: Challenges and Opportunities of Open RAN
Hamed Ahmadi, Mostafa Rahmani, Swarna Bindu Chetty +4
The transition to 6G is expected to bring significant advancements, including much higher data rates, enhanced reliability and ultra-low latency compared to previous generations. A…
ISAC-Enabled Beam Alignment for Terahertz Networks: Scheme Design and Coverage Analysis
Wenrong Chen, Lingxiang Li, Zhi Chen +3
As a key pillar technology for the future 6G networks, Terahertz (THz) communications can provide high-capacity transmissions, but suffers from severe propagation loss and line-of-…
Wireless Video Semantic Communication with Decoupled Diffusion Multi-frame Compensation
Bingyan Xie, Yongpeng Wu, Yuxuan Shi +4
Existing wireless video transmission schemes directly conduct video coding in pixel level, while neglecting the inner semantics contained in videos. In this paper, we propose a wir…
Consistent and Repeatable Testing of mMIMO O-RU across labs: A Japan-Singapore Experience
Thanh-Tam Nguyen, Mao V. Ngo, Binbin Chen +6
Open Radio Access Networks (RAN) aim to bring a paradigm shift to telecommunications industry, by enabling an open, intelligent, virtualized, and multi-vendor interoperable RAN eco…
Consistent and Repeatable Testing of O-RAN Distributed Unit (O-DU) across Continents
Tuan V. Ngo, Mao V. Ngo, Binbin Chen +6
Open Radio Access Networks (O-RAN) are expected to revolutionize the telecommunications industry with benefits like cost reduction, vendor diversity, and improved network performan…
Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach
Emilio Calvanese Strinati, Paolo Di Lorenzo, Vincenzo Sciancalepore +17
Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents. These advancements impose new requir…
Magnitude Matters: Fixing SIGNSGD Through Magnitude-Aware Sparsification in the Presence of Data Heterogeneity
Richeng Jin, Xiaofan He, Caijun Zhong +3
Communication overhead has become one of the major bottlenecks in the distributed training of deep neural networks. To alleviate the concern, various gradient compression methods h…
DiffPO: Diffusion-styled Preference Optimization for Efficient Inference-Time Alignment of Large Language Models
Ruizhe Chen, Wenhao Chai, Zhifei Yang +5
Inference-time alignment provides an efficient alternative for aligning LLMs with humans. However, these approaches still face challenges, such as limited scalability due to policy…
Breaking the Communication-Privacy-Accuracy Tradeoff with -Differential Privacy
Richeng Jin, Zhonggen Su, Caijun Zhong +3
We consider a federated data analytics problem in which a server coordinates the collaborative data analysis of multiple users with privacy concerns and limited communication capab…
Hierarchy-Aware and Channel-Adaptive Semantic Communication for Bandwidth-Limited Data Fusion
Lei Guo, Wei Chen, Yuxuan Sun +3
Obtaining high-resolution hyperspectral images (HR-HSI) is costly and data-intensive, making it necessary to fuse low-resolution hyperspectral images (LR-HSI) with high-resolution…
Sovereign AI for 6G: Towards the Future of AI-Native Networks
Swarna Bindu Chetty, David Grace, Simon Saunders +4
The advent of Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), and Large Telecom Models (LTM) significantly reshapes mobile networks, especially as the tel…