# Towards Distributed and Intelligent Integrated Sensing and Communications for 6G Networks

arXiv: https://arxiv.org/abs/2402.11630 · HTML: https://mlsanity.com/paper/2402.11630/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Feb 2024.

## Built on by (most cited first, 5 of 5)

- [Over-the-Air Edge Inference via End-to-End Metasurfaces-Integrated Artificial Neural Networks](https://mlsanity.com/paper/2504.00233/) (2025)
- [Universal Approximation with XL MIMO Systems: OTA Classification via Trainable Analog Combining](https://mlsanity.com/paper/2504.12758/) (2025)
- [Graph-CNNs for RF Imaging: Learning the Electric Field Integral Equations](https://mlsanity.com/paper/2503.14439/) (2025)
- [Integrating Stacked Intelligent Metasurfaces and Power Control for Dynamic Edge Inference via Over-The-Air Neural Networks](https://mlsanity.com/paper/2509.18906/) (2025)
- [On the Detection of Non-Cooperative RISs: Scan B-Testing via Deep Support Vector Data Description](https://mlsanity.com/paper/2411.03237/) (2024)

## Abstract (arXiv)

This paper introduces the distributed and intelligent integrated sensing and communications (DISAC) concept, a transformative approach for 6G wireless networks that extends the emerging concept of integrated sensing and communications (ISAC). DISAC addresses the limitations of the existing ISAC models and, to overcome them, it introduces two novel foundational functionalities for both sensing and communications: a distributed architecture (enabling large-scale and energy-efficient tracking of connected users and objects, leveraging the fusion of heterogeneous sensors) and a semantic and goal-oriented framework (enabling the transition from classical data fusion to the composition of semantically selected information).