8 papers
Conditional Generative Learning Enabled Wireless UAV Sensing and Tracking via Point Cloud Imaging
Xinhong Dai, Yuan Gao, Hao Jiang +2
In this paper, we study an unmanned aerial vehicle (UAV) sensing and tracking problem, where a base station equipped with an antenna array continuously illuminates a flying UAV and…
Conditional Diffusion-Based Point Cloud Imaging for UAV Position and Attitude Sensing
Xinhong Dai, Yuan Gao, Hao Jiang +2
This paper studies an unmanned aerial vehicle (UAV) position and attitude sensing problem, where a base station equipped with an antenna array transmits signals to a predetermined…
Continuous Angular Power Spectrum Recovery From Channel Covariance via Chebyshev Polynomials
Shengsong Luo, Ruilin Wu, Chongbin Xu +3
This paper proposes a Chebyshev polynomial expansion framework for the recovery of a continuous angular power spectrum (APS) from channel covariance. By exploiting the orthogonalit…
Affine-Projection Recovery of Continuous Angular Power Spectrum: Geometry and Resolution
Shengsong Luo, Ruilin Wu, Chongbin Xu +3
This paper considers recovering a continuous angular power spectrum (APS) from the channel covariance. Building on the projection-onto-linear-variety (PLV) algorithm, an affine-pro…
Trajectory Design for UAV-Assisted Logistics Collection in Low-Altitude Economy
Zhiyuan Zhai, Yuan Gao, Wei Ni +2
Low-altitude economy (LAE) is rapidly emerging as a key driver of innovation, encompassing economic activities taking place in airspace below 500 meters. Unmanned aerial vehicles (…
Spectral-Convergent Decentralized Machine Learning: Theory and Application in Space Networks
Zhiyuan Zhai, Shuyan Hu, Wei Ni +2
Decentralized machine learning (DML) supports collaborative training in large-scale networks with no central server. It is sensitive to the quality and reliability of inter-device…
Decentralized Federated Learning with Distributed Aggregation Weight Optimization
Zhiyuan Zhai, Xiaojun Yuan, Xin Wang +1
Decentralized federated learning (DFL) is an emerging paradigm to enable edge devices collaboratively training a learning model using a device-to-device (D2D) communication manner…
Decentralized Federated Learning via MIMO Over-the-Air Computation: Consensus Analysis and Performance Optimization
Zhiyuan Zhai, Xiaojun Yuan, Xin Wang
Decentralized federated learning (DFL), inherited from distributed optimization, is an emerging paradigm to leverage the explosively growing data from wireless devices in a fully d…