A heterogeneous resource allocation strategy for cross-high and low orbit mixed satellite networks is proposed, which takes dynamic communication service demands as input and collaboratively allocates beam bandwidth, frequency, time slot, power and inter-satellite links and other heterogeneous resources.
Abstract
With the steady development of geostationary orbit (GEO) satellites in China and the accelerated construction of low-orbit (LEO) satellite internet, the integration application of high and low orbit heterogeneous constellations has become an important direction for future development. Current research mainly focuses on resource allocation within a single constellation, such as GEO constellations or LEO constellations, while there is insufficient attention to the collaborative allocation of heterogeneous resources in mixed high and low orbit and cross-constellation scenarios. Therefore, this paper takes the China-Sat, Asia-Pacific and LEO satellite internet systems as research objects, deeply analyzes the service transmission modes and resource characteristics of different satellite systems such as transparent forwarding, high throughput and LEO constellations. At the same time, from the current engineering construction status, a heterogeneous resource allocation strategy for cross-high and low orbit mixed satellite networks is proposed. This strategy takes dynamic communication service demands as input and collaboratively allocates beam bandwidth, frequency, time slot, power and inter-satellite links and other heterogeneous resources. The research results can provide support for the simulation modeling and business planning of high and low orbit mixed satellite networks.
To enable global connectivity through 6G, the efficient operation of hierarchical satellite networks that integrate geostationary (GEO) and low-earth orbit (LEO) satellites is paramount. A significant challenge in achieving this operational efficiency lies in the dynamic association between the extensive array of LEO satellites and ground stations (GSs). In LEO satellite constellations, accurately estimating the queuing delay experienced by data along end-to-end (E2E) paths is challenging because of the complex interleaving of routing paths from countless sources and destinations. In particular, the satellite-to-ground links, which possess lower transmission capacity than inter-satellite links, often become critical bottlenecks for delay. Therefore, this study focuses on GS traffic loads and mathematically demonstrates, through convexity verification of queuing delays, that minimizing the maximum load effectively reduces the E2E delay. Building on these findings, we propose a novel GS-LEO association method designed to reduce delay while suppressing the maximum GS load with low computational complexity. Simulation results utilizing real-world parameters, including IXP locations and traffic demand distributions, demonstrate that the proposed method achieves lower E2E delay than existing routing approaches while maintaining a significantly lower computational load compared with strict optimization methods.
Kazuma Mashiko, Hiroaki Hashida, Y. Kawamoto et al.· IEEE Transactions on Cogniti...· 0 citations
Comparative analyses against ablation experiment frameworks and multiple access benchmark frameworks demonstrate that the proposed joint resource allocation distributed rate-splitting multiple access framework can improve the performance of low Earth orbit satellite communication systems while satisfying multiple constraint conditions.
Xianpeng Wang, Xi Han, Mingqi Gao et al.· IEEE Access· 0 citations
Numerical results indicate that the proposed framework outperforms benchmark schemes while accounting for traffic demands and EE, resulting in a mixed-integer nonlinear program (MINLP) for which finding a globally optimal solution is generally intractable.
Wooseok Cha, Kyeongsoo Kim, Seonghoon Kim et al.· IEEE Transactions on Wireles...· 0 citations
Due to their resilience and global coverage, satellite networks are poised to become a key component for non-terrestrial networks in the future. However, given the scarcity of spectrum resources, the dense deployment of low Earth orbit (LEO) satellites introduces significant interference challenges. Meanwhile, the limited computing power and backhaul capacity of satellites have become bottlenecks hindering the development of advanced interference mitigation techniques. This paper studies beamforming in GEO-LEO heterogeneous multi-satellite systems. For the GEO system, we develop a multicast beamforming approach based on a nonlinear eigenvalue problem (NEPv) for beam direction design and Lagrange dual decomposition (LDD) for power allocation. For the LEO system, we propose a general distributed beamforming framework and two distributed beamforming methods. Specifically, we first leverage equivalent multi-dimensional fractional programming (FP) to decompose the objective function. The resulting subproblems are then optimized in a distributed manner across multiple satellites via the parallel block coordinate descent (PBCD) method. For the distributed optimization subproblems, we derive semi-closed-form solutions using Lagrangian dual ascent (LDA) and alternating direction method of multipliers (ADMM) for scenarios without and with GEO-LEO interference avoidance, respectively. Simulation results show that the proposed NEPv-LDD method strictly satisfies the QoS constraints of users and achieves near-optimal performance with low complexity. For the LEO beamforming, the developed distributed FP (DiFP) framework exhibits strong scalability in large-scale constellations. Built upon the DiFP framework, the proposed DiFP-NoSIA incurs almost no performance loss, while DiFP-ADMM shows only an 8.58% performance degradation compared to the centralized benchmark.
Xin Chen, Zhiyong Luo· IEEE Transactions on Wireles...· 0 citations
This paper introduces a quantitative framework designed to evaluate and compare Low Earth Orbit (LEO) satellite constellations for global broadband communications. The analysis considers four representative systems: Starlink, OneWeb, Telesat, and Amazon’s Project Kuiper, capturing both orbital configuration and network architecture as key design characteristics. The proposed methodology integrates a geometric coverage model together with a latency formulation that accounts for propagation delay and routing effects including Inter-Satellite Links (ISL). In addition, a service density metric is introduced to characterize the spatial distribution of satellites and its impact on system capacity. These metrics are combined into a normalized multi-criteria performance index, allowing a consistent and reproducible system-level comparison. The results reveal that, while coverage is primarily governed by orbital altitude, network architecture plays a dominant role in effective latency, with ISL-enabled constellations achieving improved routing efficiency compared to bent-pipe designs. The integrated performance index shows that low altitude, high-density constellations achieve superior overall performance under latency sensitive scenarios. Starlink ranking highest due to its reduced delay and high spatial density. Project Kuiper exhibits balanced performance across all metrics, while OneWeb and Telesat are constrained by higher latency and lower density despite their broader coverage.
Kleiverg Eulalio Encino Morales, Miguel Ángel Sidón Ayala, Rolando Díaz Castillo· Revista de Ciencias Tecnológ...· 0 citations
The railway communication network serves as the backbone of modern railway systems. However, in special operating environments such as wilderness and desert regions, terrestrial networks often fail to provide effective communication support, thereby compromising operational safety and user experience. To address this issue, low Earth orbit (LEO) satellite systems are considered a promising complementary solution. A coverage model tailored to railway scenarios is first established, incorporating coverage effectiveness, reliability, and regional heterogeneity. Subsequently, a survivability performance function is constructed based on inter‐satellite link establishment relationships. Furthermore, typical transportation hubs at representative time instants are selected to evaluate the communication capacity of the constellation, and a corresponding cost model is developed. Finally, an improved multiobjective particle swarm optimization (IMOPSO) algorithm is employed to solve the formulated multiobjective optimization problem (MOP), yielding the Pareto‐optimal front of constellation configurations. Simulation results demonstrate that the proposed algorithm achieves superior convergence performance and solution diversity.
Yuchen Cai, Jiahui Qiu, Zhaoyang Su et al.· International Journal of Sat...· 0 citations
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