Data-driven Integrated Sensing and Communication: Recent Advances, Challenges, and Future Prospects

TL;DR

This paper surveys recent advances in data-driven integrated sensing and communication (ISAC), highlighting machine learning techniques, applications in 6G networks, and outlining challenges and future research directions.

Contribution

It provides a comprehensive survey of ML-based ISAC systems, identifying key challenges and proposing future research avenues for 6G network integration.

Findings

ML techniques like DL, SVM, RL are widely used in ISAC.

Applications include vehicular networks, radar, localization, mmWave, THz, beamforming.

The paper outlines key challenges and future research directions.

Abstract

Integrated Sensing and Communication (ISAC), combined with data-driven approaches, has emerged as a highly significant field, garnering considerable attention from academia and industry. Its potential to enable wide-scale applications in the future sixth-generation (6G) networks has led to extensive recent research efforts. Machine learning (ML) techniques, including $K$-nearest neighbors (KNN), support vector machines (SVM), deep learning (DL) architectures, and reinforcement learning (RL) algorithms, have been deployed to address various design aspects of ISAC and its diverse applications. Therefore, this paper aims to explore integrating various ML techniques into ISAC systems, covering various applications. These applications span intelligent vehicular networks, encompassing unmanned aerial vehicles (UAVs) and autonomous cars, as well as radar applications, localization and tracking, millimeter wave (mmWave) and Terahertz (THz) communication, and beamforming. The contributions of this paper lie in its comprehensive survey of ML-based works in the ISAC domain and its identification of challenges and future research directions. By synthesizing the existing knowledge and proposing new research avenues, this survey serves as a valuable resource for researchers, practitioners, and stakeholders involved in advancing the capabilities of ISAC systems in the context of 6G networks.