# Sensing as a Service in 6G Perceptive Networks: A Unified Framework for ISAC Resource Allocation

arXiv: https://arxiv.org/abs/2202.09969 · HTML: https://mlsanity.com/paper/2202.09969/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2022.

## Built on by (most cited first, 7 of 7)

- [Cross-Domain Continual Learning for Edge Intelligence in Wireless ISAC Networks](https://mlsanity.com/paper/2502.12736/) (2025)
- [Spectrum Shortage for Radio Sensing? Leveraging Ambient 5G Signals for Human Activity Detection](https://mlsanity.com/paper/2603.03579/) (2026)
- [Rascene: High-Fidelity 3D Scene Imaging with mmWave Communication Signals](https://mlsanity.com/paper/2604.02603/) (2026)
- [X-Band UAV-enabled Integrated Sensing and Communications for Vehicular Networks](https://mlsanity.com/paper/2606.05262/) (2026)
- [Deep Reinforcement Learning for Adaptive Power Allocation in ISAC Systems with Mobile Target](https://mlsanity.com/paper/2606.12078/) (2026)
- [Queue-Aware Graph Reinforcement Learning for UAV-ISAC-Assisted Maritime Data Collection](https://mlsanity.com/paper/2607.00324/) (2026)
- [Sense Once, Serve Many: Common-Trace Factorized Constrained PPO for Online Sensing-Session Consolidation in Multi-Tenant ISAC Networks](https://mlsanity.com/paper/2608.29256/) (2026)

## Abstract (arXiv)

In the upcoming next-generation (5G-Advanced and 6G) wireless networks, sensing as a service will play a more important role than ever before. Recently, the concept of perceptive network is proposed as a paradigm shift that provides sensing and communication (S&C) services simultaneously. This type of technology is typically referred to as Integrated Sensing and Communications (ISAC). In this paper, we propose the concept of sensing quality of service (QoS) in terms of diverse applications. Specifically, the probability of detection, the Cramer-Rao bound (CRB) for parameter estimation and the posterior CRB for moving target indication are employed to measure the sensing QoS for detection, localization, and tracking, respectively. Then, we establish a unified framework for ISAC resource allocation, where the fairness and the comprehensiveness optimization criteria are considered for the aforementioned sensing services. The proposed schemes can flexibly allocate the limited power and bandwidth resources according to both S&C QoSs. Finally, we study the performance trade-off between S&C services in different resource allocation schemes by numerical simulations.