Distributed Unsupervised Learning for Interference Management in Integrated Sensing and Communication Systems

Liu, Xiangnan; Zhang, Haijun; Long, Keping; Nallanathan, Arumugam; Leung, Victor C. M.

doi:10.1109/twc.2023.3269815

Cited by 12 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, AI can enhance ISAC performance in interference management. In [135], an unsupervised learning-based communication-sensing-intelligence converged network architecture is proposed to coordinate interference. Each base station is equipped with a deep neural network for power allocation and beamforming.…”

Section: Artificial Intelligencementioning

confidence: 99%

ISAC towards 6G Satellite–Terrestrial Communications: Principles, Status, and Prospects

Gu,

Xu,

Feng

et al. 2024

Electronics

View full text Add to dashboard Cite

With the evolution of fifth-generation (5G) to sixth-generation (6G) communication systems, the utilization of spectrum resources faces incremental challenges. Integrated sensing and communication (ISAC) technology, as a crucial element in 6G technology, is expected to enhance energy efficiency and spectrum utilization efficiency by integrating radar and communication signals, achieving environmental awareness, and enabling scene interconnection. Simultaneously, to realize the vision of seamless coverage in 6G, research on integrated satellite-terrestrial communication has been prioritized. To integrate the advantages, ISAC for integrated satellite–terrestrial networks (ISTNs) in 6G has emerged as a potential research direction. This paper offers an extensive overview of the present state of key technologies for ISAC and the development of ISTNs. Meanwhile, with a focus on the ISTN-oriented 6G ISAC system, several hotspot topics, including future application scenarios and key technological developments, are outlined and demonstrated.

show abstract

Section: Artificial Intelligencementioning

confidence: 99%

ISAC towards 6G Satellite–Terrestrial Communications: Principles, Status, and Prospects

Gu,

Xu,

Feng

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…The proper action is predicted by a deep Q-network (DQN) given the state of the dynamic environment and previous actions. Liu et al [64] proposed a DL network architecture for interference management in ISAC systems via proper power allocation. Unsupervised learning was utilized, and then transfer learning was used to predict a proper beamforming scheme for interference management.…”

Section: Data-driven Approaches For Beamforming In Isacmentioning

confidence: 99%

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

Salem,

Quamar,,

Magad

et al. 2023

Preprint

View full text Add to dashboard Cite

<p>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.</p>

show abstract

Intelligent integrated sensing and communication: a survey

Zhang,

Lu,

Xing

et al. 2024

Sci. China Inf. Sci.

View full text Add to dashboard Cite

Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

show abstract

Distributed Unsupervised Learning for Interference Management in Integrated Sensing and Communication Systems

Cited by 12 publications

References 31 publications

ISAC towards 6G Satellite–Terrestrial Communications: Principles, Status, and Prospects

ISAC towards 6G Satellite–Terrestrial Communications: Principles, Status, and Prospects

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

Intelligent integrated sensing and communication: a survey

Contact Info

Product

Resources

About