# Digital Twin-Assisted Adaptive Multi-Agent DRL for Intelligent Spectrum and Resource Management in Open-RAN UAV-Enabled 6G Networks

arXiv: https://arxiv.org/abs/2606.01324 · HTML: https://mlsanity.com/paper/2606.01324/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 16 references that are in the map.
- First posted on arXiv 31 May 2026.

## Builds on (most cited first, 3 of 3)

- [Emerging Technologies for 6G Non-Terrestrial-Networks: From Academia to Industrial Applications](https://mlsanity.com/paper/2403.07763/) (2024)
- [Joint Optimization of 3D Placement and Radio Resource Allocation for per-UAV Sum Rate Maximization](https://mlsanity.com/paper/2305.04519/) (2023)
- [Deep Reinforcement Learning for Network Energy Saving in 6G and Beyond Networks](https://mlsanity.com/paper/2408.10974/) (2024)

## Abstract (arXiv)

The evolution toward 6G wireless networks envisions a seamlessly intelligent, Open-RAN-enabled architecture where unmanned aerial vehicles (UAVs) play a pivotal role in extending coverage, enhancing resilience, and ensuring reliable connectivity for ground users deployment. However, efficiently managing spectrum and resources in such highly dynamic UAV-assisted environments remains a major challenge due to nonlinear system interactions, mobility-induced topology variations, and stringent latency and energy constraints. To address these challenges, we propose a digital twin (DT)-assisted adaptive deep reinforcement learning (DRL) framework that enables intelligent spectrum sharing and resource allocation across distributed ground users. The complex optimization problem is decomposed into UAV trajectory optimization using particle swarm optimization (PSO) and dynamic spectrum-power-association management via multi-agent DRL (MADRL). This hybrid DT-driven approach empowers intelligent, context-aware decision-making and adaptive coordination among UAVs. Extensive simulations demonstrate significant gains in spectral efficiency, data rates, and energy utilization, showcasing a transformative path toward self-evolving, autonomous 6G UAV and ground users (GUs) connectivity.