Research on the Optimization Method of Low Earth Orbit Integrated Sensing and Communication Based on Multi-Dimensional Resource Joint Scheduling

ZHAO Shiqiu; XIE Xuxu; LI Yuntao; DING Xiaojin; ZHANG Gengxin

doi:10.11999/JEIT240995

Volume 47 Issue 4

Apr. 2025

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Article Navigation > Journal of Electronics & Information Technology > 2025 > 47(4): 968-978

ZHAO Shiqiu, XIE Xuxu, LI Yuntao, DING Xiaojin, ZHANG Gengxin. Research on the Optimization Method of Low Earth Orbit Integrated Sensing and Communication Based on Multi-Dimensional Resource Joint Scheduling[J]. Journal of Electronics & Information Technology, 2025, 47(4): 968-978. doi: 10.11999/JEIT240995

Citation:

ZHAO Shiqiu, XIE Xuxu, LI Yuntao, DING Xiaojin, ZHANG Gengxin. Research on the Optimization Method of Low Earth Orbit Integrated Sensing and Communication Based on Multi-Dimensional Resource Joint Scheduling[J]. Journal of Electronics & Information Technology, 2025, 47(4): 968-978. doi: 10.11999/JEIT240995

Citation:

ZHAO Shiqiu, XIE Xuxu, LI Yuntao, DING Xiaojin, ZHANG Gengxin. Research on the Optimization Method of Low Earth Orbit Integrated Sensing and Communication Based on Multi-Dimensional Resource Joint Scheduling[J]. Journal of Electronics & Information Technology, 2025, 47(4): 968-978. doi: 10.11999/JEIT240995

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Research on the Optimization Method of Low Earth Orbit Integrated Sensing and Communication Based on Multi-Dimensional Resource Joint Scheduling

doi: 10.11999/JEIT240995 cstr: 32379.14.JEIT240995

1.
School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2.
Institute of Space-Air-Ground-Sea Integration, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Funds: The National Natural Science Foundation of China (62171234)

Received Date: 2024-11-06
Rev Recd Date: 2025-03-17

Available Online: 2025-03-28

Publish Date: 2025-04-01

Abstract

Abstract

Objective With the rapid development of Low Earth Orbit (LEO) satellite constellations and Integrated Sensing And Communication (ISAC) systems, performance optimization faces increasing challenges due to fixed power distribution, spectrum limitations, and interference between communication and sensing functions. This study proposes an optimization method based on multi-dimensional resource joint scheduling to address these constraints in LEO satellite environments. The method enhances the combined performance of communication and sensing by leveraging the high satellite visibility of LEO constellations. The optimization focuses on improving communication reach, data rate, radar mutual information, and positioning accuracy while ensuring efficient resource allocation. Methods The optimization problem is formulated as a multi-variable joint problem, incorporating satellite selection, subchannel function allocation, and power distribution. To address the complexity of this Mixed-Integer NonLinear Programming (MINLP) problem, it is decoupled into subproblems and solved iteratively using the Block Coordinate Descent (BCD) method. Satellite selection is optimized using a modified Multi-Population Genetic Algorithm (MPGA), which accounts for communication link quality, sensing capabilities, and satellite geometric distribution. Subchannel allocation and power distribution are iteratively optimized to maximize system performance while maintaining a balance between communication and sensing tasks. Results and Discussions The proposed optimization method is evaluated through simulations against benchmark schemes. Results indicate that, under the same resource constraints, the method enhances integrated communication and sensing performance by over 7% (Fig. 5). Improvements are observed in communication efficiency, radar detection mutual information, and positioning accuracy. Additionally, the number of cooperating satellites significantly affects system performance, though gains diminish beyond an optimal threshold (Fig. 4). This highlights the importance of strategic satellite selection and coordination to balance performance gains with complexity and resource usage. Moreover, the results confirm the convergence of the proposed method, demonstrating consistent performance across multiple scenarios (Fig. 3). Conclusions This study proposes an optimization approach for ISAC systems in LEO satellite constellations, addressing challenges related to resource allocation, power distribution, and interference management. The multi-dimensional resource joint scheduling method enhances overall system performance by optimizing satellite selection, subchannel allocation, and power distribution. Simulation results demonstrate that: (1) The proposed optimization method improves integrated communication and sensing performance in LEO satellite ISAC systems, achieving a performance gain of over 7% compared to benchmark solutions. (2) The multi-dimensional resource joint scheduling approach effectively balances communication and sensing tasks by optimizing satellite selection, subchannel function allocation, and power distribution, thereby mitigating interference and resource constraints. (3) The number of cooperating satellites significantly influences system performance. However, beyond an optimal threshold, additional satellites yield diminishing returns, emphasizing the need for efficient satellite coordination. This study assumes ideal sensing capabilities; future research should incorporate real-world constraints, such as satellite mobility and environmental factors, to enhance the practical applicability of the proposed approach.

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References(28)

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