4 citations · 5 across the 5 of their papers we have counts for
7 papers · 1 filter
Communicate Less, Synthesize the Rest: Latency-aware Intent-based Generative Semantic Multicasting with Diffusion Models
Xinkai Liu, Mahdi Boloursaz Mashhadi, Li Qiao +3
Generative diffusion models (GDMs) have recently shown great success in synthesizing multimedia signals with high perceptual quality, enabling highly efficient semantic communicati…
Token-Domain Multiple Access: Exploiting Semantic Orthogonality for Collision Mitigation
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +1
Token communications is an emerging generative semantic communication concept that reduces transmission rates by using context and transformer-based token processing, with tokens s…
Text-Guided Token Communication for Wireless Image Transmission
Bole Liu, Li Qiao, Ye Wang +4
With the emergence of 6G networks and proliferation of visual applications, efficient image transmission under adverse channel conditions is critical. We present a text-guided toke…
Generative Semantic Communication via Textual Prompts: Latency Performance Tradeoffs
Mengmeng Ren, Li Qiao, Long Yang +6
This paper develops an edge-device collaborative Generative Semantic Communications (Gen SemCom) framework leveraging pre-trained Multi-modal/Vision Language Models (M/VLMs) for ul…
CSI-GPT: Integrating Generative Pre-Trained Transformer with Federated-Tuning to Acquire Downlink Massive MIMO Channels
Ye Zeng, Li Qiao, Zhen Gao +5
In massive multiple-input multiple-output (MIMO) systems, how to reliably acquire downlink channel state information (CSI) with low overhead is challenging. In this work, by integr…
Massive Digital Over-the-Air Computation for Communication-Efficient Federated Edge Learning
Li Qiao, Zhen Gao, Mahdi Boloursaz Mashhadi +1
Over-the-air computation (AirComp) is a promising technology converging communication and computation over wireless networks, which can be particularly effective in model training,…