Skip to content
AI Atlas
PaperActive

Decision Transformer for UAV-Mounted RIS-Assisted Dynamic D2D Communications

arxiv.org/abs/2609.09885

quality89

Updated 4 h ago · first seen 11 Sept 2026

paper_01M294GKCE290AGS10SBX98MCQ

Published
11 Sept 2026
T1 · 4 h ago
arXiv
2609.09885
T1 · 4 h ago
Category
cs.AI
T1 · 4 h ago

Abstract

This paper studies unmanned aerial vehicle (UAV)-mouted reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) communication with stochastic link activation. It models UAV motion and attitude, time-varying Rician angles, and angle-dependent RIS reflection. A joint optimization of UAV trajectory, attitude, and RIS phases is formulated to maximize average sum rate under mobility, energy, and hardware constraints. The problem is addressed using deep reinforcement learning and a Decision Transformer trained on expert trajectories from multiple scenarios. Results demonstrate effective cross-scenario generalization, with zero-shot transfer outperforming direct DRL transfer and online fine-tuning achieving competitive performance with fewer interactions.

Authors 1

Yaxuan Liu

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 4 h agohigh

Arxiv announce type
new

Source:arXiv (Atom API + RSS)T1observed 4 h agohigh

arXiv id
2609.09885

Source:arXiv (Atom API + RSS)T1observed 4 h agohigh

Categories
cs.AI, cs.RO

Source:arXiv (Atom API + RSS)T1observed 4 h agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 4 h agohigh

Primary category
cs.AI

Source:arXiv (Atom API + RSS)T1observed 4 h agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 4 h agohigh

Each value shows its source, tier and observation time. Conflicting claims are kept side by side and flagged — never averaged. How AI Atlas records facts →

Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

4 h ago

Conflicts

None