User Trajectory Prediction in Mobile Wireless Networks Using Quantum Reservoir Computing

Understand

This paper applies a quantum machine learning technique to predict mobile users' trajectories in mobile wireless networks using an approach called quantum reservoir computing (QRC).

• Mobile users' trajectories prediction belongs to the task of temporal information processing and it is a mobility management problem that is essential for self-organizing and autonomous 6G networks.
• Our aim is to accurately predict the future positions of mobile users in wireless networks using QRC.
• To do so, we use a real-world time series dataset to model mobile users' trajectories.