2 citations · 3 across the 16 of their papers we have counts for
18 papers
DS-Net: A Dynamic Split Network for Edge-Cloud Collaborative Inference
Xinyun Zhang, Li Wang, Lei Jin +2
Collaborative inference serves as a critical methodology in edge intelligence. Existing collaborative inference methods operate by splitting the deep neural network (DNN) model bet…
Rethinking the State Update Gate for Long-Sequence Recurrent 3D Reconstruction
Kejun Ren, Lei Jin, Tianxin Huang +2
Streaming 3D reconstruction under a strict constant-memory budget hinges on how the recurrent state is updated as the stream evolves. We profile TTT3R-style per-token gates across…
MARS: Radio Map Super-resolution and Reconstruction Method under Sparse Channel Measurements
Chuyun Deng, Na Liu, Wei Xie +2
Radio maps reflect the spatial distribution of signal strength and are essential for applications like smart cities, IoT, and wireless network planning. However, reconstructing acc…
Measurements and Modeling of Air-Ground Integrated Channel in Forest Environment Based on OFDM Signals
Zhe Xiao, Shu Sun, Na Liu +2
Forests are frequently impacted by climate conditions, vegetation density, and intricate terrain and geology, which contribute to natural disasters. Personnel engaged in or support…
DULRTC-RME: A Deep Unrolled Low-rank Tensor Completion Network for Radio Map Estimation
Yao Wang, Xin Wu, Lianming Xu +2
Radio maps enrich radio propagation and spectrum occupancy information, which provides fundamental support for the operation and optimization of wireless communication systems. Tra…
DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices
Xian Peng, Xin Wu, Lianming Xu +2
Distributed DNN inference is becoming increasingly important as the demand for intelligent services at the network edge grows. By leveraging the power of distributed computing, edg…
Two-Stage Radio Map Construction with Real Environments and Sparse Measurements
Yifan Wang, Shu Sun, Na Liu +2
Radio map construction based on extensive measurements is accurate but expensive and time-consuming, while environment-aware radio map estimation reduces the costs at the expense o…
RemoteDet-Mamba: A Hybrid Mamba-CNN Network for Multi-modal Object Detection in Remote Sensing Images
Kejun Ren, Xin Wu, Lianming Xu +1
Unmanned Aerial Vehicle (UAV) remote sensing, with its advantages of rapid information acquisition and low cost, has been widely applied in scenarios such as emergency response. Ho…
Toward Adaptive Tracking and Communication via an Airborne Maneuverable Bi-Static ISAC System
Mingliang Wei, Ruoguang Li, Li Wang +2
In this letter, we propose an airborne maneuverable bi-static integrated sensing and communication system where both the transmitter and receiver are unmanned aerial vehicles. By t…
Multimodal generative semantic communication based on latent diffusion model
Weiqi Fu, Lianming Xu, Xin Wu +2
In emergencies, the ability to quickly and accurately gather environmental data and command information, and to make timely decisions, is particularly critical. Traditional semanti…
Failure-Resilient Distributed Inference with Model Compression over Heterogeneous Edge Devices
Li Wang, Liang Li, Lianming Xu +2
The distributed inference paradigm enables the computation workload to be distributed across multiple devices, facilitating the implementations of deep learning based intelligent s…
Emergency Caching: Coded Caching-based Reliable Map Transmission in Emergency Networks
Zeyu Tian, Lianming Xu, Liang Li +2
Many rescue missions demand effective perception and real-time decision making, which highly rely on effective data collection and processing. In this study, we propose a three-lay…
Emergency Computing: An Adaptive Collaborative Inference Method Based on Hierarchical Reinforcement Learning
Weiqi Fu, Lianming Xu, Xin Wu +2
In achieving effective emergency response, the timely acquisition of environmental information, seamless command data transmission, and prompt decision-making are crucial. This nec…
An Improved Virtual Force Approach for UAV Deployment and Resource Allocation in Emergency Communications
Hongying Guo, Li Wang, Ruoguang Li +3
In this paper, we consider an unmanned aerial vehicle (UAV)-enabled emergency communication system, which establishes temporary communication link with users equipment (UEs) in a t…
Emergency Localization for Mobile Ground Users: An Adaptive UAV Trajectory Planning Method
Zhihao Zhu, Jiafan He, Luyang Hou +3
In emergency search and rescue scenarios, the quick location of trapped people is essential. However, disasters can render the Global Positioning System (GPS) unusable. Unmanned ae…
UAV-assisted Emergency Integrated Sensing and Communication Networks: A CNN-based Rapid Deployment Approach
Zao Wang, Lianming Xu, Luyang Hou +2
UAV-assisted integrated sensing and communication (ISAC) network is crucial for post-disaster emergency rescue. The speed of UAV deployment will directly impact rescue results. How…
Deep Learning for Efficient CSI Feedback in Massive MIMO: Adapting to New Environments and Small Datasets
Zhenyu Liu, Li Wang, Lianming Xu +1
Deep learning (DL)-based channel state information (CSI) feedback has shown promising potential to improve spectrum efficiency in massive MIMO systems. However, practical DL approa…
Propagation Path Loss Models in Forest Scenario at 605 MHz
Zhe Xiao, Shu Sun, Zhenyu Liu +4
When signals propagate through forest areas, they will be affected by environmental factors such as vegetation. Different types of environments have different influences on signal…