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From the 1 of 37 linked papers with an AI index.

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37 papers

cs.NI2026

Active Movable-Element RIS Assisted Vehicular Semantic Communications: Modeling and Optimization

Maoxin Ji, Qiong Wu, Jingbo Zhang +5

The paper proposes a vehicular semantic communication system that employs a row‑movable active reconfigurable intelligent surface (RM‑A‑RIS) whose elements can both move and amplif…

cs.LG2026

Federated Client Selection under Partial Visibility: A POMDP Approach with Spatio-Temporal Attention

Qijun Hou, Yuchen Shi, Pingyi Fan +1

Federated learning relies on effective client selection to alleviate the performance degradation caused by data heterogeneity. Most existing methods assume full visibility of all c…

eess.SP2026

Satellite NOMA for Direct-to-Cell Communications: Fundamentals, Protocols, and Opportunities

Xiangyu Li, Bodong Shang, Junchao Ma +3

Direct-to-cell (DTC) satellite communication is regarded as one of the most recent technologies that provides global connectivity. However, with the growing number of wireless user…

cs.LG2026

FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference

Qijun Hou, Yuchen Shi, Pingyi Fan +1

Federated Learning (FL) facilitates collaborative model training across decentralized clients while preserving data privacy by avoiding raw data exchange. Despite its potential, FL…

cs.NI2026

Joint Optimization of Trajectory Control, Resource Allocation, and Task Offloading for Multi-UAV-Assisted IoV

Maoxin Ji, Qiong Wu, Pingyi Fan +4

This paper investigates a multi-Unmanned Aerial Vehicle (UAV) joint base station-assisted Internet of Vehicles (IoV) task offloading system in dense urban environments. To minimize…

cs.NI2026

Single-Step Six-Dimensional Movable Antenna Reconfiguration for High-Mobility IoV: Modeling, Analysis, and Optimization

Maoxin Ji, Qiong Wu, Pingyi Fan +4

The Six-Dimensional Movable Antenna (6DMA) system has emerged as a promising technology to enhance wireless capacity by fully exploiting spatial degrees of freedom. However, applyi…