Interference Management for Integrated Sensing and Communication Systems: A Survey
Emerging applications, such as autonomous driving and Internet of Things (IoT) services put forward the demand for simultaneous sensing and communication functions in the same system. Integrated sensing and communication (ISAC) has the potential to meet the demands of ubiquitous communication and high-precision sensing due to the advantages of spectrum and hardware resource sharing, as well as the mutual enhancement of sensing and communication. However, the ISAC system faces severe interference requiring effective interference suppression, avoidance, and exploitation techniques. This article provides a comprehensive survey on the interference management techniques in ISAC systems, involving network architecture, system design, signal processing, and resource allocation. We first review the channel modeling and performance metrics of the ISAC system. Then, the methods for managing self-interference (SI), mutual interference (MI), and clutter in a single base station (BS) system are summarized, including interference suppression, interference avoidance, and interference exploitation methods. Furthermore, cooperative interference management methods are studied to address the cross-link interference (CLI) in a coordinated multipoint ISAC (CoMP-ISAC) system. Finally, future trends are revealed. This article may provide a reference for the study of interference management in ISAC systems.
Authors
- Zhiyong Feng (ORCID: https://orcid.org/0000-0001-5322-222X)
- Huici Wu (ORCID: https://orcid.org/0000-0001-7689-482X)
- Lin Wang (ORCID: https://orcid.org/0000-0001-9373-764X)
- Zhiqing Wei (ORCID: https://orcid.org/0000-0001-7940-2739)
- Yangyang Niu (ORCID: https://orcid.org/0009-0006-0633-8768)
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2024-11-28
- DOI
- https://doi.org/10.1109/jiot.2024.3506162
- Citations
- 69
- Primary Topic
- Energy Efficient Wireless Sensor Networks
- Type
- article
- Field-Weighted Citation Impact
- 24.07
Funders
- National Natural Science Foundation of China