PRATA: A Framework to Enable Predictive QoS in Vehicular Networks via Artificial Intelligence

arXiv:2507.14211 · cs.NI, cs.AI · Submitted 2025-07-15 · Read on arXiv

cs.NI, cs.AI

Submitted: 2025-07-15

Updated: 2025-07-15

Code: https://github.com/signetlabdei/ns3-ran-ai

Terminology

• Reinforcement Learning — 15× in this paper · explained in 4 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• Artificial Intelligence — 10× in this paper
• Action Space — 8× in this paper · explained in 1 episode
• Quality of Service — 7× in this paper
• Predictive Quality of Service — 6× in this paper
• Deep Reinforcement Learning — 5× in this paper · explained in 2 episodes
• Q-learning — 5× in this paper · explained in 3 episodes
• Reward Function — 5× in this paper · explained in 2 episodes
• Vehicular Technology Conference — 5× in this paper
• Aggregation — 4× in this paper · explained in 1 episode
• Reinforcement Learning (RL) — 4× in this paper · explained in 25 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 3× in this paper · explained in 2 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Chamfer Distance — 2× in this paper
• Communication Overhead — 2× in this paper · explained in 2 episodes
• Digital Twin — 2× in this paper · explained in 5 episodes
• Double Q-learning — 2× in this paper
• IEEE Wireless Communications and Networking Conference — 2× in this paper
• Machine Learning — 2× in this paper
• Point Clouds — 2× in this paper · explained in 2 episodes
• Segmentation Aggressive — 2× in this paper
• Segmentation Conservative — 2× in this paper
• 3GPP Specifications — 1× in this paper · explained in 1 episode
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• Deep Reinforcement Learning (DRL) — 1× in this paper · explained in 2 episodes
• Federated Learning — 1× in this paper · explained in 15 episodes
• G Radio Access Network — 1× in this paper
• Long Short Term Memory — 1× in this paper
• Long Term Evolution — 1× in this paper
• Markov Decision Process — 1× in this paper
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Medium Access Control — 1× in this paper
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Next Generation Node Base — 1× in this paper
• Packet Data Convergence Protocol — 1× in this paper
• Point Cloud Data — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization — 1× in this paper
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• QoS and Quality of Experience — 1× in this paper
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• QUALINET White Paper on Definitions of Immersive Media Experience (IMEx)

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