3 citations · 3 across the 21 of their papers we have counts for
24 papers
WiFo-INR: A Wireless Foundation Model Based on Implicit Neural Representations
Boxun Liu, Xuanyu Liu, Shijian Gao +2
Wireless foundation models are emerging as a promising paradigm for AI-native physical-layer design. However, existing methods typically model channel state information (CSI) as im…
WiFo-E: A Scalable Wireless Foundation Model for End-to-End FDD Precoding in Communication Networks
Weibo Wen, Shijian Gao, Haotian Zhang +2
Accurate precoding in massive multiple-input multiple-output (MIMO) frequency-division duplexing (FDD) systems relies on efficient channel state information (CSI) acquisition. End-…
WiFo-MUD: Wireless Foundation Model for Heterogeneous Multi-User Demodulator
Zonghui Yang, Shijian Gao, Xuesong Cai +2
Multi-user signal demodulation is critical to wireless communications, directly impacting transmission reliability and efficiency. However, existing demodulators underperform in ge…
WiFo-M: Empower Wireless Communications With Plug-and-Play Environment Sensing via Foundation Model
Haotian Zhang, Shijian Gao, Xiang Cheng
The emerging convergence of next-generation wireless networks and agentic artificial intelligence (AI) is inspiring a new vision: embodied intelligent network entities utilize envi…
Embodied Intelligent Wireless (EIW): Synesthesia of Machines Empowered Wireless Communications
Xiang Cheng, Weibo Wen, Haotian Zhang +4
The evolution toward the sixth-generation (6G) and beyond mobile communication systems is marked by a fundamental shift from merely connecting devices to enabling pervasive and emb…
WiFo-2: a generalist foundation model unifies heterogeneous wireless system design
Boxun Liu, Xuanyu Liu, Shijian Gao +3
Emerging sixth-generation wireless systems are increasingly heterogeneous, with compatibility across diverse configurations, ubiquitous coverage, and expanded functionalities. Alth…
Tiny-WiFo: A Lightweight Wireless Foundation Model for Channel Prediction via Multi-Component Adaptive Knowledge Distillation
Haotian Zhang, Shijian Gao, Xiang Cheng
The massive scale of Wireless Foundation Models (FMs) hinders their real-time deployment on edge devices. This letter moves beyond standard knowledge distillation by introducing a…
WiFo-CF: Wireless Foundation Model for CSI Feedback
Xuanyu Liu, Shijian Gao, Boxun Liu +2
Deep learning-based channel state information (CSI) feedback schemes demonstrate strong compression capabilities but are typically constrained to fixed system configurations, limit…
Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network
Zonghui Yang, Shijian Gao, Xiang Cheng +1
Integrated sensing and communication (ISAC) within sub-THz frequencies is crucial for future air-ground networks, but unique propagation characteristics and hardware limitations pr…
Synesthesia of Machines (SoM)-Aided Online FDD Precoding via Heterogeneous Multi-Modal Sensing: A Vertical Federated Learning Approach
Haotian Zhang, Shijian Gao, Weibo Wen +2
This paper investigates a heterogeneous multi-vehicle, multi-modal sensing (H-MVMM) aided online precoding problem. The proposed H-MVMM scheme utilizes a vertical federated learnin…
LLM4WM: Adapting LLM for Wireless Multi-Tasking
Xuanyu Liu, Shijian Gao, Boxun Liu +2
The wireless channel is fundamental to communication, encompassing numerous tasks collectively referred to as channel-associated tasks. These tasks can leverage joint learning base…
Synesthesia of Machines (SoM)-Aided FDD Precoding with Sensing Heterogeneity: A Vertical Federated Learning Approach
Haotian Zhang, Shijian Gao, Weibo Wen +1
High complexity in precoding design for frequency division duplex systems necessitates streamlined solutions. Guided by Synesthesia of Machines (SoM), this paper introduces a heter…
Synesthesia of Machine (SoM)-Driven Analog Precoder Optimization for Enhanced ISAC Performance in Sub-THz Systems
Zonghui Yang, Shijian Gao, Xiang Cheng
Integrated sensing and communication (ISAC) is anticipated to be widely used in future sub-terahertz (sub-THz) systems. With the line-of-sight (LoS) propagation characteristics of…
WiFo: Wireless Foundation Model for Channel Prediction
Boxun Liu, Shijian Gao, Xuanyu Liu +2
Channel prediction permits to acquire channel state information (CSI) without signaling overhead. However, almost all existing channel prediction methods necessitate the deployment…
Synesthesia of Machines (SoM)-Enhanced ISAC Precoding for Vehicular Networks with Double Dynamics
Zonghui Yang, Shijian Gao, Xiang Cheng +1
Integrated sensing and communication (ISAC) technology is vital for vehicular networks, yet the time-varying communication channels and rapid movement of targets present significan…
Synesthesia of Machines (SoM)-Enhanced Wideband Multi-User CSI Learning With LiDAR Sensing
Haotian Zhang, Shijian Gao, Xiang Cheng +1
Light detection and ranging (LiDAR) has been utilized for optimizing wireless communications due to its ability to detect the environment. This paper explores the use of LiDAR in c…
Multi-Modal Fusion-Based Multi-Task Semantic Communication System
Zengle Zhu, Rongqing Zhang, Xiang Cheng +1
In recent years, there has been significant progress in semantic communication systems empowered by deep learning techniques. It has greatly improved the efficiency of information…
LLM4CP: Adapting Large Language Models for Channel Prediction
Boxun Liu, Xuanyu Liu, Shijian Gao +2
Channel prediction is an effective approach for reducing the feedback or estimation overhead in massive multi-input multi-output (m-MIMO) systems. However, existing channel predict…
Doubly-Dynamic ISAC Precoding for Vehicular Networks: A Constrained Deep Reinforcement Learning (CDRL) Approach
Zonghui Yang, Shijian Gao, Xiang Cheng
Integrated sensing and communication (ISAC) technology is essential for supporting vehicular networks. However, the communication channel in this scenario exhibits time variations,…
Beam Pattern Modulation Embedded Hybrid Transceiver Optimization for Integrated Sensing and Communication
Boxun Liu, Shijian Gao, Zonghui Yang +2
Integrated sensing and communication (ISAC) emerges as a promising technology for B5G/6G, particularly in the millimeter-wave (mmWave) band. However, the widely utilized hybrid arc…
Superposed IM-OFDM (S-IM-OFDM): An Enhanced OFDM for Integrated Sensing and Communications
Zonghui Yang, Shijian Gao, Xiang Cheng +1
Integrated sensing and communications (ISAC) is a critical enabler for emerging 6G applications, and at its core lies in the dual-functional waveform design. While orthogonal frequ…
Beam Pattern Modulation Embedded mmWave Hybrid Transceiver Design Towards ISAC
Boxun Liu, Shijian Gao, Zonghui Yang +1
Integrated Sensing and Communication (ISAC) emerges as a promising technology for B5G/6G, particularly in the millimeter-wave (mmWave) band. However, the widespread adoption of hyb…
A Survey on Federated Learning in Intelligent Transportation Systems
Rongqing Zhang, Hanqiu Wang, Bing Li +2
The development of Intelligent Transportation System (ITS) has brought about comprehensive urban traffic information that not only provides convenience to urban residents in their…
Integrated Sensing and Communications Towards Proactive Beamforming in mmWave V2I via Multi-Modal Feature Fusion (MMFF)
Haotian Zhang, Shijian Gao, Xiang Cheng +1
The future of vehicular communication networks relies on mmWave massive multi-input-multi-output antenna arrays for intensive data transfer and massive vehicle access. However, rel…