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Resource Allocation for Multi-LEO Satellite-Enabled Integrated Communication and Positioning System
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AI
DOI：10.1109/TCOMM.2026.3677155.png)
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Abstract
En 中文
In order to realize the internet of everything in sixth generation (6G), the emerging 6G applications have brought increasing demands for the high-speed communication and high-accuracy positioning concurrently. Relying on the potentials of high transmission power, large quantity and excellent geometric topology, low earth orbit (LEO) satellites have become strong candidates for providing integrated communication and positioning (ICAP) services. However, the resource competition between services and high dynamics of space-ground environment make it intractable to strike a balance between communication and positioning performance, which is one of the key design issue in LEO-ICAP networks. Against this backdrop, we consider an ICAP system with multiple LEO satellites, and adopt communication rate and squared position error bound (SPEB) as performance evaluation metrics. Based on that, we further formulate a weighted utility maximization problem, where the balance between communication and positioning performance can be achieved by jointly optimizing the subcarrier and power allocation, while simultaneously satisfying users’ quality of service (QoS) requirements. To solve this mixed-integer nonlinear programming problem, we propose a compressed sensing-based resource allocation algorithm, where the sparsity property of optimization variables is exploited to reformulate the problem into a continuous form, and the sequential convex programming method is then applied to solve the problem iteratively until convergence. Extensive simulations verify the superiority of our proposed algorithm compared to various benchmark schemes, where the proposed algorithm achieves a sum-rate improvement of at least 22% and a SPEB reduction of at least 28%, showing its effectiveness in realizing the balanced optimization of communication and positioning performance.
Keywords:
Low earth orbit (LEO) satellites
integrated communication and positioning (ICAP)
resource allocation
compressed sensing
Journal
IF:
8.3
Papers:
1.2W
Citations:
3.6W