204 citations · 278 across the 17 of their papers we have counts for
19 papers
Intention-Aware Semantic Agent Communications for AI Glasses
Peiwen Jiang, Fangyu Liu, Jiajia Guo +3
Smart glasses are emerging as a promising interface between humans and artificial intelligence (AI) agents, enabling first-person perception, contextual awareness, and real-time as…
AgentComm: Semantic Communication for Embodied Agents
Peiwen Jiang, Yushuo Feng, Jiajia Guo +2
The increasing deployment of agentic artificial intelligence (AI) systems has intensified the demand for efficient agent to agent communication, particularly over bandwidth limited…
Semantic Satellite Communications for Synchronized Audiovisual Reconstruction
Fangyu Liu, Peiwen Jiang, Wenjin Wang +2
Satellite communications face severe bottlenecks in supporting high-fidelity synchronized audiovisual services, as conventional schemes struggle with cross-modal coherence under fl…
Bures-Wasserstein Importance-Weighted Evidence Lower Bound: Exposition and Applications
Peiwen Jiang, Takuo Matsubara, Minh-Ngoc Tran
The Importance-Weighted Evidence Lower Bound (IW-ELBO) has emerged as an effective objective for variational inference (VI), tightening the standard ELBO and mitigating the mode-se…
Conditional Diffusion Model-Enabled Scenario-Specific Neural Receivers for Superimposed Pilot Schemes
Xingyu Zhou, Le Liang, Xinjie Li +4
Neural receivers have demonstrated strong performance in wireless communication systems. However, their effectiveness typically depends on access to large-scale, scenario-specific…
Semantic Communications with World Models
Peiwen Jiang, Jiajia Guo, Chao-Kai Wen +2
Semantic communication is a promising technique for emerging wireless applications, which reduces transmission overhead by transmitting only task-relevant features instead of raw d…
Foundation Model-Based Adaptive Semantic Image Transmission for Dynamic Wireless Environments
Fangyu Liu, Peiwen Jiang, Wenjin Wang +3
Foundation model-based semantic transmission has recently shown great potential in wireless image communication. However, existing methods exhibit two major limitations: (i) they o…
LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks
Jiajia Guo, Peiwen Jiang, Chao-Kai Wen +2
Accurate channel state information (CSI) is critical to the performance of wireless communication systems, especially with the increasing scale and complexity introduced by 5G and…
Position-Aided Semantic Communication for Efficient Image Transmission: Design, Implementation, and Experimental Results
Peiwen Jiang, Chao-Kai Wen, Shi Jin +1
Semantic communication, augmented by knowledge bases (KBs), offers substantial reductions in transmission overhead and resilience to errors. However, existing methods predominantly…
Adaptive Wireless Image Semantic Transmission: Design, Simulation, and Prototype Validation
Jiarun Ding, Peiwen Jiang, Chao-Kai Wen +1
The rapid development of artificial intelligence has significantly advanced semantic communications, particularly in wireless image transmission. However, most existing approaches…
Generative Diffusion Models for High Dimensional Channel Estimation
Xingyu Zhou, Le Liang, Jing Zhang +3
Along with the prosperity of generative artificial intelligence (AI), its potential for solving conventional challenges in wireless communications has also surfaced. Inspired by th…
Adaptive Wireless Image Semantic Transmission and Over-The-Air Testing
Jiarun Ding, Peiwen Jiang, Chao-Kai Wen +1
Semantic communication has undergone considerable evolution due to the recent rapid development of artificial intelligence (AI), significantly enhancing both communication robustne…
Semantic Satellite Communications Based on Generative Foundation Model
Peiwen Jiang, Chao-Kai Wen, Xiao Li +2
Satellite communications can provide massive connections and seamless coverage, but they also face several challenges, such as rain attenuation, long propagation delays, and co-cha…
Semantic Communications using Foundation Models: Design Approaches and Open Issues
Peiwen Jiang, Chao-Kai Wen, Xinping Yi +3
Foundation models (FMs), including large language models, have become increasingly popular due to their wide-ranging applicability and ability to understand human-like semantics. W…
RIS-Enhanced Semantic Communications Adaptive to User Requirements
Peiwen Jiang, Chao-Kai Wen, Shi Jin +1
Semantic communication significantly reduces required bandwidth by understanding semantic meaning of the transmitted. However, current deep learning-based semantic communication me…
Wireless Semantic Transmission via Revising Modules in Conventional Communications
Peiwen Jiang, Chao-Kai Wen, Shi Jin +1
Semantic communication has become a popular research area due its high spectrum efficiency and error-correction performance. Some studies use deep learning to extract semantic feat…
Wireless Semantic Communications for Video Conferencing
Peiwen Jiang, Chao-Kai Wen, Shi Jin +1
Video conferencing has become a popular mode of meeting even if it consumes considerable communication resources. Conventional video compression causes resolution reduction under l…
Deep Source-Channel Coding for Sentence Semantic Transmission with HARQ
Peiwen Jiang, Chao-Kai Wen, Shi Jin +1
Recently, semantic communication has been brought to the forefront because of its great success in deep learning (DL), especially Transformer. Even if semantic communication has be…
AI-Aided Online Adaptive OFDM Receiver: Design and Experimental Results
Peiwen Jiang, Tianqi Wang, Bin Han +5
Orthogonal frequency division multiplexing (OFDM) has been widely applied in current communication systems. The artificial intelligence (AI)-aided OFDM receivers are currently brou…