AdaPTwin proposes an adaptive multi-fidelity network digital twin with cloud-edge architecture, transformer-based trajectory prediction, and ray-tracing to enable proactive radio resource management in vehicular networks.
Digital twin for 6g: Taxonomy, research challenges, and the road ahead
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A digital twin-based INC-MEC framework models XR user interactions as a Stackelberg Markov game and uses a Nash-asynchronous hybrid multi-agent RL algorithm to achieve Nash Equilibrium, improving system utility, uplink rate, and energy efficiency in simulations.
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AdaPTwin: Adaptive Multi-Fidelity Predictive Digital Twin for Proactive Radio Resource Management in Vehicular Networks
AdaPTwin proposes an adaptive multi-fidelity network digital twin with cloud-edge architecture, transformer-based trajectory prediction, and ray-tracing to enable proactive radio resource management in vehicular networks.
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Digital Twin-Assisted In-Network and Edge Collaboration for Joint User Association, Task Offloading, and Resource Allocation in the Metaverse
A digital twin-based INC-MEC framework models XR user interactions as a Stackelberg Markov game and uses a Nash-asynchronous hybrid multi-agent RL algorithm to achieve Nash Equilibrium, improving system utility, uplink rate, and energy efficiency in simulations.