collaborators
Showing eess.SPShow all

5 papers · 1 filter

eess.SP2026

Artificial Intelligence for Spatially Reconfigurable Antennas: Movable, Fluid, and Pinching Antenna Systems

Nguyen Cong Luong, Zeping Sui, Thai-Hoc Vu +10

Recently, sixth-generation (6G) wireless networks have moved beyond fixed-array designs toward antenna architectures that can adapt their spatial configuration to specific environm…

eess.SP2026

From Denoising to Decision Making: A Survey on Diffusion Model-Enabled Deep Reinforcement Learning for Wireless Networks

Nguyen Cong Luong, Zeping Sui, Jie Cao +9

Deep reinforcement learning (DRL) has long been a promising solution for sequential resource management in wireless networks. However, conventional DRL methods are fundamentally li…

eess.SP2026

Transformer-Enhanced Reinforcement Learning: Fundamentals and Applications in Communication Networks

Nguyen Cong Luong, Shaohan Feng, Nguyen Duc Hai +10

Reinforcement Learning (RL) has long been a powerful solution to various problems in communication networks. However, traditional RL models still face with several limitations. Not…

eess.SP2026

Dynamic Antenna Placement for Mobile Users in Urban Micro Pinching-Antenna Systems

Qiushi Zhao, Zihan Feng, Ximing Xie +3

The pinching-antenna systems (PASS) enable blockage mitigation in urban micro (UMi) networks through flexible antenna placement. However, the joint optimization of antenna position…

eess.SP2025

Intelligent Optimization of Wireless Access Point Deployment for Communication-Based Train Control Systems Using Deep Reinforcement Learning

Kunyu Wu, Qiushi Zhao, Zihan Feng +4

Urban railway systems increasingly rely on communication based train control (CBTC) systems, where optimal deployment of access points (APs) in tunnels is critical for robust wirel…