Sensing as a Service in 6G Perceptive Networks: A Unified Framework for ISAC Resource Allocation
Not on the map. Why?
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.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Feb 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 1; 2026: 6.
7 papers.
- 2025Cross-Domain Continual Learning for Edge Intelligence in Wireless ISAC Networkscited by 2
- 2026Spectrum Shortage for Radio Sensing? Leveraging Ambient 5G Signals for Human Activity Detectioncited by 1
- 2026Rascene: High-Fidelity 3D Scene Imaging with mmWave Communication Signalscited by 0
- 2026X-Band UAV-enabled Integrated Sensing and Communications for Vehicular Networkscited by 0
- 2026Deep Reinforcement Learning for Adaptive Power Allocation in ISAC Systems with Mobile Targetcited by 0
- 2026Queue-Aware Graph Reinforcement Learning for UAV-ISAC-Assisted Maritime Data Collectioncited by 0
- 2026Sense Once, Serve Many: Common-Trace Factorized Constrained PPO for Online Sensing-Session Consolidation in Multi-Tenant ISAC Networkscited by 0
- 2026Sense Once, Serve Many: Common-Trace Factorized Constrained PPO for Online Sensing-Session Consolidation in Multi-Tenant ISAC Networks29 Aug 2026
- 2026Queue-Aware Graph Reinforcement Learning for UAV-ISAC-Assisted Maritime Data Collection1 Jul 2026
- 2026Deep Reinforcement Learning for Adaptive Power Allocation in ISAC Systems with Mobile Target10 Jun 2026
- 2026X-Band UAV-enabled Integrated Sensing and Communications for Vehicular Networks3 Jun 2026
- 2026Rascene: High-Fidelity 3D Scene Imaging with mmWave Communication Signals3 Apr 2026
- 2026Spectrum Shortage for Radio Sensing? Leveraging Ambient 5G Signals for Human Activity Detection3 Mar 2026
- 2025Cross-Domain Continual Learning for Edge Intelligence in Wireless ISAC Networks18 Feb 2025