4 citations · 10 across the 19 of their papers we have counts for
12 papers · 1 filter
TokenComSR: Task-Sensitivity-Guided Token Communication for Wireless Image Super-Resolution
Ye Wang, Li Qiao, Zhen Gao +1
For resource-constrained wireless edge devices over bandwidth-limited fading channels, wireless image transmission using traditional separate coding suffers from the cliff-effect c…
Ada-TokenCom: Rate-Adaptive Token Communications via Large-Model-Driven Token Compression and Generation
Zijun Zhang, Li Qiao, Mahdi Boloursaz Mashhadi +3
Token Communications (TokenCom) has recently emerged as a new paradigm in which tokens serve as unified units for communication and computation, enabling efficient multimodal seman…
Knowledge Distillation Driven Semantic NOMA with GAN Refinement for 6G Robotic Vehicle Networks
Qifei Wang, Zhen Gao, Li Qiao +4
To achieve sustainable intelligent mobility, 6G-empowered robotic vehicles (RVs) require high-fidelity visual perception under stringent bandwidth and energy constraints. Semantic…
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…
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…
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…
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,…
Latency-Aware Generative Semantic Communications with Pre-Trained Diffusion Models
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +3
Generative foundation AI models have recently shown great success in synthesizing natural signals with high perceptual quality using only textual prompts and conditioning signals t…
Near-Space Communications: the Last Piece of 6G Space-Air-Ground-Sea Integrated Network Puzzle
Hongshan Liu, Tong Qin, Zhen Gao +16
This article presents a comprehensive study on the emerging near-space communications (NS-COM) within the context of space-air-ground-sea integrated network (SAGSIN). Specifically,…
Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication
Zhen Gao, Malong Ke, Yikun Mei +4
The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires adva…