Dynamic power and frequency domain allocation for dedicated sensing signals in downlink ISAC

This paper presents a dynamic joint resource allocation framework for downlink Integrated Sensing and Communication (ISAC) systems. The proposed approach simultaneously optimizes power and frequency assignment using an iterative optimization algorithm that adapts to real-time channel state information and sensing requirements. A composite utility function is introduced to balance sensing accuracy and communication throughput, enabling flexible trade-offs for different application scenarios. Comparative analysis against benchmark schemes demonstrates that the proposed method achieves notable improvements in both sensing accuracy and communication rate, while also providing insights into power distribution across users and sensing tasks. These results highlight the potential of the framework as a practical and adaptive solution for ISAC-enabled 6G networks.

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Publication Details

Journal
Scientific Reports
Published
2025-12-20
DOI
https://doi.org/10.1038/s41598-025-32895-x
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamic power and frequency domain allocation for dedicated sensing signals in downlink ISAC

Ghani Ur Rehman, Riad Alharbey, Madeeha Aman, Daud Ali et al.
Scientific Reports
Radar Systems and Signal Processing
article

Dynamic power and frequency domain allocation for dedicated sensing signals in downlink ISAC

Ghani Ur Rehman, Riad Alharbey, Madeeha Aman, Daud Ali, Muhammad Zubair, Sajid Ullah Khan
article en

Abstract

This paper presents a dynamic joint resource allocation framework for downlink Integrated Sensing and Communication (ISAC) systems. The proposed approach simultaneously optimizes power and frequency assignment using an iterative optimization algorithm that adapts to real-time channel state information and sensing requirements. A composite utility function is introduced to balance sensing accuracy and communication throughput, enabling flexible trade-offs for different application scenarios. Comparative analysis against benchmark schemes demonstrates that the proposed method achieves notable improvements in both sensing accuracy and communication rate, while also providing insights into power distribution across users and sensing tasks. These results highlight the potential of the framework as a practical and adaptive solution for ISAC-enabled 6G networks.

Scientific ReportsVol. 16(1)
Prince Sattam Bin Abdulaziz University (SA), University of the Punjab (PK), Emirates Foundation (AE), Aga Khan Hospital, Kisumu (KE), Heriot-Watt University (GB), Heriot-Watt University Malaysia (MY), University of Jeddah (SA), Aktobe Regional State University named after K.Zhubanov (KZ), Khushal Khan Khattak University Karak
Prince Sattam bin Abdulaziz University
Openalex Percentile: Top 48%
Radar Systems and Signal Processing
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