# Gesture-Aware Indoor THz ISAC Systems for Adaptive Resource Allocation

arXiv: https://arxiv.org/abs/2605.29913 · HTML: https://mlsanity.com/paper/2605.29913/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 15 references that are in the map.
- First posted on arXiv 28 May 2026.

## Builds on (most cited first, 4 of 4)

- [SNR/CRB-Constrained Joint Beamforming and Reflection Designs for RIS-ISAC Systems](https://mlsanity.com/paper/2301.11134/) (2023)
- [Spectrum Allocation with Adaptive Sub-band Bandwidth for Terahertz Communication Systems](https://mlsanity.com/paper/2111.05629/) (2021)
- [Environment Reconstruction in Terahertz Monostatic Sensing: Joint Millimeter-level Geometry Mapping and Material Identification](https://mlsanity.com/paper/2508.10372/) (2025)
- [Adaptive Full Duplex Communications in Cognitive Radio Networks](https://mlsanity.com/paper/1710.05768/) (2017)

## Abstract (arXiv)

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.