26 citations · 32 across the 16 of their papers we have counts for
17 papers
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-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…
Joint CFO-Channel Estimation under Strong Inter-Cell Interference for Low-Altitude Radio Mapping
Bowen Li, Haotian Zhang, Mu Jia +2
Extending terrestrial networks into low-altitude airspace is a practical way to support aerial services, and accurate low-altitude radio maps are essential for characterizing terre…
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…
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…
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…
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…
Probabilistic Prior Driven Attention Mechanism Based on Diffusion Model for Imaging Through Atmospheric Turbulence
Guodong Sun, Qixiang Ma, Liqiang Zhang +3
Atmospheric turbulence introduces severe spatial and geometric distortions, challenging traditional image restoration methods. We propose the Probabilistic Prior Turbulence Removal…
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…
Scheduling Drone and Mobile Charger via Hybrid-Action Deep Reinforcement Learning
Jizhe Dou, Haotian Zhang, Guodong Sun
Recently there has been a growing interest in industry and academia, regarding the use of wireless chargers to prolong the operational longevity of unmanned aerial vehicles (common…
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…
Intelligent Multi-Modal Sensing-Communication Integration: Synesthesia of Machines
Xiang Cheng, Haotian Zhang, Jianan Zhang +7
In the era of sixth-generation (6G) wireless communications, integrated sensing and communications (ISAC) is recognized as a promising solution to upgrade the physical system by en…
Nonmonontone submodular maximization under routing constraints
Haotian Zhang, Rao Li, Zewei Wu +1
In machine learning and big data, the optimization objectives based on set-cover, entropy, diversity, influence, feature selection, etc. are commonly modeled as submodular function…
Resilient Continuous-Time Consensus in Fractional Robust Networks
Heath J. LeBlanc, Haotian Zhang, Shreyas Sundaram +1
In this paper, we study the continuous-time consensus problem in the presence of adversaries. The networked multi-agent system is modeled as a switched system, where the normal age…
Consensus of Multi-Agent Networks in the Presence of Adversaries Using Only Local Information
Heath J. LeBlanc, Haotian Zhang, Shreyas Sundaram +1
This paper addresses the problem of resilient consensus in the presence of misbehaving nodes. Although it is typical to assume knowledge of at least some nonlocal information when…
Robustness of Complex Networks with Implications for Consensus and Contagion
Haotian Zhang, Elaheh Fata, Shreyas Sundaram
We study a graph-theoretic property known as robustness, which plays a key role in certain classes of dynamics on networks (such as resilient consensus, contagion and bootstrap per…
Robustness of Information Diffusion Algorithms to Locally Bounded Adversaries
Haotian Zhang, Shreyas Sundaram
We consider the problem of diffusing information in networks that contain malicious nodes. We assume that each normal node in the network has no knowledge of the network topology o…