Signal Prediction for Loss Mitigation in Tactile Internet: A Leader-Follower Game-Theoretic Approach

TL;DR

This paper introduces a leader-follower game-theoretic method for signal prediction in Tactile Internet, improving latency and reliability by accurately predicting signals to mitigate packet loss and delay.

Contribution

The paper proposes a novel Stackelberg game-based approach for cooperative signal prediction in Tactile Internet, enhancing robustness and prediction accuracy in teleoperation systems.

Findings

Prediction accuracy ranges from 80.62% to 95.03% for human signals.

Prediction accuracy ranges from 70.44% to 89.77% for robot signals.

Established an upper bound for maximum signal loss using Taylor Expansion.

Abstract

Tactile Internet (TI) requires achieving ultra-low latency and highly reliable packet delivery for haptic signals. In the presence of packet loss and delay, the signal prediction method provides a viable solution for recovering the missing signals. To this end, we introduce the Leader-Follower (LeFo) approach based on a cooperative Stackelberg game, which enables both users and robots to learn and predict actions. With accurate prediction, the teleoperation system can safely relax its strict delay requirements. Our method achieves high prediction accuracy, ranging from 80.62% to 95.03% for remote robot signals at the Human ($H$) side and from 70.44% to 89.77% for human operation signals at the remote Robot ($R$) side. We also establish an upper bound for maximum signal loss using Taylor Expansion, ensuring robustness.