# Integrating Sensing and Communications for Ubiquitous IoT: Applications, Trends and Challenges

arXiv: https://arxiv.org/abs/2104.11457 · HTML: https://mlsanity.com/paper/2104.11457/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Apr 2021.

## Built on by (most cited first, 20 of 20)

- [Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization](https://mlsanity.com/paper/2308.05384/) (2023)
- [WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication](https://mlsanity.com/paper/2502.06877/) (2025)
- [Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AI](https://mlsanity.com/paper/2207.00969/) (2022)
- [A Survey on Integrated Sensing, Communication, and Computation](https://mlsanity.com/paper/2408.08074/) (2024)
- [Joint Sensing and Semantic Communications with Multi-Task Deep Learning](https://mlsanity.com/paper/2311.05017/) (2023)
- [Integrated Sensing-Communication-Computation for Edge Artificial Intelligence](https://mlsanity.com/paper/2306.01162/) (2023)
- [Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AI](https://mlsanity.com/paper/2306.06603/) (2023)
- [Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access](https://mlsanity.com/paper/2312.13931/) (2023)
- [Attention-based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices](https://mlsanity.com/paper/2506.11892/) (2025)
- [Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classifications](https://mlsanity.com/paper/2507.00015/) (2025)
- [Near-field Beam training for Extremely Large-scale MIMO Based on Deep Learning](https://mlsanity.com/paper/2406.03249/) (2024)
- [CSI4Free: GAN-Augmented mmWave CSI for Improved Pose Classification](https://mlsanity.com/paper/2406.18684/) (2024)
- [VHetNets for AI and AI for VHetNets: An Anomaly Detection Case Study for Ubiquitous IoT](https://mlsanity.com/paper/2210.08132/) (2022)
- [Need of 6G for the Metaverse Realization](https://mlsanity.com/paper/2301.03386/) (2022)
- [Multi-Base Station Cooperative Sensing with AI-Aided Tracking](https://mlsanity.com/paper/2310.20403/) (2023)
- [Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifiers](https://mlsanity.com/paper/2404.15344/) (2024)
- [CSIYOLO: An Intelligent CSI-based Scatter Sensing Framework for Integrated Sensing and Communication Systems](https://mlsanity.com/paper/2509.19335/) (2025)
- [mmHSense: Multi-Modal and Distributed mmWave ISAC Datasets for Human Sensing](https://mlsanity.com/paper/2509.21396/) (2025)
- [Deep Learning-Driven Friendly Jamming for Secure Multicarrier ISAC Under Channel Uncertainty](https://mlsanity.com/paper/2603.05062/) (2026)
- [Robust Design of Integrated Sensing and Communication in LEO Satellite Systems](https://mlsanity.com/paper/2607.12337/) (2026)

## Abstract (arXiv)

Recent advances in wireless communication and solid-state circuits together with the enormous demands of sensing ability have given rise to a new enabling technology, integrated sensing and communications (ISAC). The ISAC captures two main advantages over dedicated sensing and communication functionalities: 1) Integration gain to efficiently utilize congested resources, and even, 2) Coordination gain to balance dual-functional performance or/and perform mutual assistance. Meanwhile, triggered by ISAC, we are also witnessing a paradigm shift in the ubiquitous IoT architecture, in which the sensing and communication layers are tending to converge into a new layer, namely, the signaling layer. In this paper, we first attempt to introduce a definition of ISAC, analyze the various influencing forces, and present several novel use cases. Then, we complement the understanding of the signaling layer by presenting several key benefits in the IoT era. We classify existing dominant ISAC solutions based on the layers in which integration is applied. Finally, several challenges and opportunities are discussed. We hope that this overview article will serve as a primary starting point for new researchers and offer a bird's-eye view of the existing ISAC-related advances from academia and industry, ranging from solid-state circuitry, signal processing, and wireless communication to mobile computing.