Integrated Radio Sensing Capabilities for 6G Networks: AI/ML Perspective
Victor Shatov, Steffen Schieler, Charlotte Muth, Jos\'e Miguel Mateos-Ramos, Ivo Bizon, Florian Euchner, Sebastian Semper, Stephan ten Brink, Gerhard Fettweis, Christian H\"ager, Henk Wymeersch, Laurent Schmalen, Reiner Thom\"a, Norman Franchi

TL;DR
This paper surveys AI and ML techniques to enhance radio sensing in 6G networks, covering various sensing applications within integrated sensing and communication, and discusses challenges and future directions.
Contribution
It provides a comprehensive tutorial and review of AI/ML approaches for diverse radio sensing tasks in 6G, expanding the sensing scope beyond radar to include localization and spectrum sensing.
Findings
AI/ML significantly improve sensing accuracy and efficiency.
Integrated sensing and communication enable multimodal, multi-task networks.
Challenges include data scarcity, complexity, and real-time processing requirements.
Abstract
The sixth-generation wireless communications (6G) is often labeled as "connected intelligence". Radio sensing, aligned with machine learning (ML) and artificial intelligence (AI), promises, among other benefits, breakthroughs in the system's ability to perceive the environment and effectively utilize this awareness. This article offers a tutorial-style survey of AI and ML approaches to enhance the sensing capabilities of next-generation wireless networks. To this end, while staying in the framework of integrated sensing and communication (ISAC), we expand the term "sensing" from radar, via spectrum sensing, to miscellaneous applications of radio sensing like non-cooperative transmitter localization. We formulate the problems, explain the state-of-the-art approaches, and detail AI-based techniques to tackle various objectives in the context of wireless sensing. We discuss the advantages,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
