Gesture-Aware Indoor THz ISAC Systems for Adaptive Resource Allocation

2026-05-28

AI Summary

This work addresses the challenge of dynamic resource allocation in indoor terahertz integrated sensing and communication (ISAC) systems caused by time-varying hand gestures. To this end, the authors propose a gesture recognition–driven adaptive joint optimization framework that leverages an extended Kalman filter for high-precision gesture tracking. Based on real-time gesture estimates, the system dynamically adjusts power allocation and beamforming strategies to simultaneously satisfy the quality-of-service (QoS) requirements of communication links associated with different gestures and enhance sensing performance. This study represents the first effort to deeply integrate gesture recognition into terahertz ISAC systems, enabling synergistic adaptation between sensing and communication functionalities. Simulation results demonstrate that the proposed method significantly outperforms conventional single-variable optimization baselines in both sensing signal-to-interference-plus-noise ratio (SINR) and communication performance.

Abstract

This paper investigates a multi-user indoor integrated sensing and communication (ISAC) system operating in the terahertz (THz) band, designed for adaptive communication based on gesture recognition. Leveraging gesture tracking through an extended Kalman filter (EKF), the access point (AP) dynamically adjusts resource allocation in response to detected gesture variations, thereby improving sensing accuracy. Based on the gesture recognition results, the AP further updates the communication quality requirements of different users, enabling efficient resource allocation. To this end, an adaptive joint optimization algorithm for power allocation and beamforming is developed to maximize the overall sensing signal-to-interference-plus-noise ratio (SINR) while satisfying the gesture-dependent communication quality of service (QoS) constraints. Simulation results demonstrate that the proposed method effectively responds to gesture dynamics, achieving superior sensing accuracy and communication performance compared with conventional single-variable optimization baselines.

Problem

• gesture recognition
• THz ISAC
• adaptive resource allocation
• indoor communication
• QoS constraints

Innovation

• THz ISAC
• gesture-aware resource allocation
• adaptive beamforming
• extended Kalman filter
• joint optimization