Low Earth Orbit (LEO) satellites present a compelling opportunity for the establishment of a global quantum information network. However, satellite-based entanglement distribution from a networking perspective has not been fully investigated. Existing works often do not account for satellite movement over time when distributing entanglement and/or often do not permit entanglement distribution along inter-satellite links, which are two shortcomings we address in this paper. We first define a system model which considers both satellite movement over time and inter-satellite links. We next formulate the optimal entanglement distribution (OED) problem under this system model and show how to convert the OED problem in a dynamic physical network to one in a static logical graph which can be used to solve the OED problem in the dynamic physical network. We then propose a polynomial time greedy algorithm for computing satellite-assisted multi-hop entanglement paths. We also design an integer linear programming (ILP)-based algorithm to compute optimal solutions as a baseline to study the performance of our greedy algorithm. We present evaluation results to demonstrate the advantage of our model and algorithms.
Low Earth Orbit (LEO) satellites present a compelling opportunity for the establishment of a global quantum information network. However, satellite-based entanglement distribution from a networking perspective has not been fully investigated. Existing works often do not account for satellite movement over time when distributing entanglement and/or often do not permit entanglement distribution along inter-satellite links, which are two shortcomings we address in this paper. We first define a system model which considers both satellite movement over time and inter-satellite links. We next formulate the optimal entanglement distribution (OED) problem under this system model and show how to convert the OED problem in a dynamic physical network to one in a static logical graph which can be used to solve the OED problem in the dynamic physical network. We then propose a polynomial time greedy algorithm for computing satellite-assisted multi-hop entanglement paths. We also design an integer linear programming (ILP)-based algorithm to compute optimal solutions as a baseline to study the performance of our greedy algorithm. We present evaluation results to demonstrate the advantage of our model and algorithms.
Recent advances in space quantum communications envision Low Earth Orbit (LEO) satellites for global entanglement distribution. Entanglement distribution in such a network requires considerations such as satellite mobility, ground station mobility due to the Earth’s rotation, inter-satellite links, and multiple orbital shells, all of which have not been thoroughly studied in the networking literature. We ameliorate this deficit by defining a system model which accounts for all of the aforementioned factors. Using this system model, we formulate the dynamic optimal entanglement distribution (DOED) problem. We convert the DOED problem in a dynamic physical network to an instance of the problem in a static logical graph, the latter of which can be used to solve the former. We obtain a reduced logical graph from a logical graph, which can be used to reduce the complexity of solving the DOED problem. We propose two polynomial-time greedy algorithms for computing entanglement paths, as well as an integer linear programming (ILP)-based algorithm as a benchmark. We present evaluation results to demonstrate the advantages of our model and algorithms.
As LEO/VLEO satellites offer many attractive features, such as low transmission delay, they are expected to be an integral part of 6G. Global entanglement distribution over LEO and VLEO satellite network must reckon with satellite movement over time. Current studies do not fully capture the dynamic nature of satellite constellations. We model a dynamic LEO/VLEO satellite network as a time-varying graph and construct a sequence of static graphs to represent a dynamic network. We study the entanglement distribution problem between a set of source-destination node pairs in this dynamic network utilizing Multi-commodity Flow (MCF). Solving MCF over a sequence of graphs independently for each graph may produce a completely different set of paths. Changing the set of paths every time the graph topology changes may involve a significant amount of overhead, as an established set of paths must be taken down and a new set of paths established. We propose a technique that will avoid this overhead by computing only one set of paths P to be used over all the graphs in the sequence. The degraded performance offered byPmay be viewed as the cost of using P. The benefit of usingPis the overhead cost of path switching that can be avoided. We provide a cost-benefit analysis in a LEO/VLEO constellation for entanglement distribution between multiple source-destination pairs. Our extensive experimentation shows that a significant amount of savings in overhead can be achieved if one is willing to accept a slightly degraded performance.
Quantum entanglement routing in dynamic Low Earth Orbit (LEO) satellite networks is important for achieving scalable and high-fidelity quantum communication. However, the dynamic characteristics of satellite network topology, limited quantum resources, and strict coherence time constraints pose significant challenges to reliable entanglement routing. An entanglement distribution analysis model for this unique environment is critical and helpful for entanglement routing research. We address the fundamental challenge of establishing and maintaining quantum entanglement links between satellites operating in free space, where links are subject to both transmission losses and quantum memory decoherence. This paper presents a comprehensive Markov chain model with a state space defined by link storage age and physical distance for analyzing entanglement distribution in noisy dynamic LEO satellite quantum networks. We construct transition matrices that capture system dynamics under varying request arrival rates, and derive analytical expressions for key performance metrics, including request satisfaction rate, average waiting time, link utilization efficiency, and average consumed link fidelity. Our analysis reveals that the critical trade-offs of higher request rates lead to faster link consumption with higher fidelity but potentially lower satisfaction rates, while lower request rates allow longer storage times at the cost of lower fidelity of increased decoherence effect. Moreover, this paper proves it is reasonable to leave out polarization rotation when the transmission distance is very short (40-50 km). In summary, this work provides theoretical foundations for designing and optimizing quantum entanglement distribution strategies in satellite networks, with applications to global-scale quantum communications.
This paper addresses the complexities of entanglement distribution in LEO satellite networks, particularly those arising from their dynamic topology. Traditional static and dynamic entanglement distribution methods often result in high entanglement drop rates and reduced end-to-end throughput. We introduce a novel framework that leverages the dynamic nature of LEO satellite networks to enhance entanglement distribution efficiency. Employing a space-time graph model to represent the network's temporal evolution, we propose an entanglement distribution strategy based on path utility, incorporating pointing errors, non-ideal link transmittance for intersatellite links, and atmospheric effects for downlinks. Our approach demonstrates superior performance in reducing entanglement drop rates and improving throughput compared to conventional methods. This study advances the field of quantum communication in satellite networks, offering resilient and efficient entanglement distribution strategies that support practical applications such as distributed computing, quantum multipartite cryptography, and distributed quantum sensing. The findings underscore the potential of integrating dynamic satellite networks with quantum technologies to create a reliable and secure quantum internet.
Quantum satellite networks enable entanglement distribution between ground stations, but existing single-satellite solutions relying solely on satellite-to-ground downlinks cannot effectively support long-distance entanglement distribution. To overcome this limitation, we propose a hybrid approach,Entanglement Distribution using Hybrid Links(ED-HL), which integrates bothentanglement distribution using a single satellite(ED-SS) andentanglement distribution assisted by inter-satellite links(ED-IS), where satellites are equipped with quantum memories. The key challenge in ED-HL is to effectively coordinate satellites to distribute entanglement to ground stations via inter-satellite links and downlinks.We formulate this entanglement distribution problem as an integer programming problem, establish its submodularity, monotonicity and non-negativity properties, and design a greedy algorithm for its solution. Simulations based on real-world constellation data show that ED-HL significantly extends the entanglement distribution distance compared to single-satellite approaches.
Quantum satellite networks offer a promising solution for achieving long-distance quantum communication by enabling entanglement distribution across global scales. This work formulates and solves the quantum satellite network scheduling problem by optimizing satellite-to-ground station pair assignments under realistic system and environmental constraints. Our framework accounts for limited satellite and ground station resources, fairness, entanglement fidelity thresholds, and real world non-idealities including atmospheric losses, weather and background noise. In addition, we incorporate the complexities of multi-satellite relays enabled via inter-satellite links. We propose an integer linear programming (ILP) based optimization framework that supports multiple scheduling objectives, allowing us to analyze tradeoffs between maximizing total entanglement distribution rate and ensuring fairness across ground station pairs. Our framework can also be used as a benchmark tool to measure the performance of other potential transmission scheduling policies.