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IEEE Globecom Workshops (GC Wkshps)

Cost-Efficient Network Planning for Quantum Communication Infrastructure

Ilora Maity, Symeon Chatzinotas

Published Dec 4, 2023• 3 citations
Publisher

Abstract

Quantum communication infrastructure (QCI) is gradually becoming a favorable choice for transmitting secure data across the globe. Network operators often prefer to utilize the existing network infrastructure to reduce network setup costs to build a QCI. This implies transforming traditional network nodes to quantum nodes (QNs) by equipping them with quantum processors. Trusted repeater nodes (TRNs) are used to connect distant QNs. However, the network infrastructure cost increases with the number of TRNs due to the usage of dark fibers. Therefore, it is challenging for the network planning to build a QCI that connects all QNs with a minimum number of TRNs to reduce the infrastructure cost. In this work, we construct a minimum cost spanning tree for the QCI to connect all QNs with a minimum number of links and TRNs. The proposed approach considers node distance and attenuation cost of the physical connections. Compared to the traditional spanning tree approach, our proposed approach reduces the cost of QCI deployment by 10.90%.

DOI
10.1109/gcwkshps58843.2023.10464831

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cs.NICross-listedarXiv:2604.06764•Apr 9, 2026•0 citations
Quantum communication infrastructure (QCI) is gradually becoming a favorable choice for transmitting secure data across the globe. Network operators often prefer to utilize the existing network infrastructure to reduce network setup costs to build a QCI. This implies transforming traditional network nodes to quantum nodes (QNs) by equipping them with quantum processors. Trusted repeater nodes (TRNs) are used to connect distant QNs. However, the network infrastructure cost increases with the number of TRNs due to the usage of dark fibers. Therefore, it is challenging for the network planning to build a QCI that connects all QNs with a minimum number of TRNs to reduce the infrastructure cost. In this work, we construct a minimum cost spanning tree for the QCI to connect all QNs with a minimum number of links and TRNs. The proposed approach considers node distance and attenuation cost of the physical connections. Compared to the traditional spanning tree approach, our proposed approach reduces the cost of QCI deployment by 10.90%.
Quantum key distribution (QKD) provides a secure method to exchange encrypted information between two parties in a quantum communication infrastructure (QCI). The primary challenge in deploying a QCI is the cost of using optical fibers and trusted repeater nodes (TRNs). Practical systems combine quantum and classical channels on the same fiber to reduce the cost of fibers dedicated to QKD. In such a system with quantum-classical coexistence, the optimal distribution of QKD requests with minimal deployment cost and power usage on the multiplexed links is challenging due to the diverse key rate demands of the requests, number of classical and quantum channels, guard band spacing between classical and quantum channels, and secret key rate of the quantum channels that decreases with distance. To address these challenges, in this work, we propose a Steiner tree-based approach for constructing a QCI that connects all quantum nodes with minimum TRNs. In addition, we propose a genetic algorithm-based solution to optimally distribute the end-to-end QKD requests over the QCI. We also determine feasible optical bypass routes to reduce the overall energy consumption in the network further. The proposed approach reduces the QCI deployment cost by 19.42% compared to the benchmark MST-Baseline. Also, on average, TAQNet with optical bypass achieves 4.69 kbit per Joule more energy efficiency compared to the nonbypass approach.
This article proposes an optimization model for the design of quantum communication infrastructures (QCI) with the aim of minimizing capital expenditure (CAPEX), focusing on the costs associated with the deployment of quantum links and trusted repeater nodes. The model is formulated using an integer linear programming (ILP) program that incorporates physical and operational constraints to ensure efficient resource allocation. The simulation results obtained using an ILP solver show that increasing wavelength availability leads to significant reductions in CAPEX while consistently producing solutions that satisfy all constraints. However, because ILP becomes computationally expensive for large-scale networks, we propose two genetic algorithms ( GA1\text{GA}_{1}GA1​ and GA2\text{GA}_{2}GA2​ ) designed to improve scalability. Both GA1\text{GA}_{1}GA1​ and GA2\text{GA}_{2}GA2​ offer competitive computation times compared with the ILP solver and provide near-optimal solutions compared with the ILP solution. Overall, this approach is effective for small, medium, and large-scale QCI deployments, offering a scalable and practical solution suitable for real-world implementation. For example, in the small network topology with nine nodes and nine requests, we observe a reduction of CAPEX up to 33% when the number of available wavelengths increases from 1 to 2, and we note that GAs in a large topology, such as NET-4 network, reduce CAPEX by 34.6% ( GA1\text{GA}_{1}GA1​ ), and 21.1% ( GA2\text{GA}_{2}GA2​ ) compared to the benchmarks.
The technological maturity of Quantum Key Distribution (QKD) products have generated high demand for secure key distribution in transmitting sensitive data. To provide this service, long-haul network operators are exploring strategies for network-wide deployment of QKD devices while utilizing existing infrastructure. One approach is to place trusted nodes at existing in-line amplifier huts in the network. In this study, we present a near-optimal fiber span aggregation algorithm, which effectively minimizes the number of trusted nodes between Points-of-Presences (PoPs) in the network. In this study, we evaluate six different topological QKD network deployments and eight different technological QKD network deployments in terms of the total secure key rate, as well as the number of QKD fiber pairs deployed. Our results indicate that the span aggregation algorithm increases the distance between each trusted node by up to 20%, thereby reducing the overall number of trusted nodes. Capacity planning for various topologies and technology deployments on simulated Secure Application Entity (SAE) requests is undertaken. Our proposed capacity planning shows that a baseline deployment with span aggregation using a QKD device with a cut-off distance of 140 km can save up to 3 times the number of QKD deployed fibers as compared to a minimum spanning tree-based low-cost deployment.
Long-distance quantum communication presents a significant challenge due to the degrading fidelity of transmitted qubits. Quantum repeaters are proposed to overcome this issue through Bell measurements on entangled qubit pairs. However, despite its necessity to enable wide-area quantum internet, the deployment cost of quantum repeaters can be prohibitively expensive; thus, developing a quantum repeater deployment model that can strike a balance between cost and effectiveness is essential. In this work, we present novel heuristic models to quickly determine a minimum number of quantum repeaters to deploy in large-scale networks to provide end-to-end connectivity between all end hosts. The results show that, compared to the integer linear programming approach, the heuristic methods can find near-optimal solutions while reducing the execution time from days to seconds when evaluated against several synthetic and real-world networks such as SURFnet and ESnet. As reliability is critical for any network, we demonstrate that the heuristic method can estimate deployment models to endure up to two link/node failures.
Long-distance quantum communication presents a significant challenge as maintaining the fidelity of qubits can be difficult. This issue can be addressed through the use of quantum repeaters to transmit entanglement information through Bell measurements. However, despite its necessity to enable wide-area quantum internet, the deployment cost of quantum repeaters can be prohibitively expensive, thus it is important to develop a quantum repeater deployment model that can strike a balance between cost and effectiveness. In this work, we present novel heuristic models to quickly determine a minimum number of quantum repeaters to deploy in large-scale networks to provide end-to-end connectivity between all end hosts. The results show that, compared to the linear programming approach, the heuristic methods can find near-optimal solutions while reducing the execution time from days to seconds when evaluated against several synthetic and real-world networks such as SURFnet and ESnet. As reliability is key for any network, we also demonstrate that the heuristic method can determine deployment models that can endure up to two link/node failures.
The European Union is developing the European Quantum Communication Infrastructure (EuroQCI) as a pan-European network to provide secure communication capabilities across Member States, including governmental and critical-infrastructure domains. While the strategic objective is defined at EU level, the required scale and structure of national quantum key distribution (QKD) networks remain largely unspecified. This work addresses the question of how to plan and size national terrestrial QKD networks to support critical infrastructure and public authorities. We propose a reproducible planning methodology that estimates network size, total fiber length, and the number of required QKD components based on a small set of explicit assumptions. The approach is demonstrated for Austria, where a synthetic but structured network model is constructed and evaluated using Monte Carlo simulation. The model focuses on terrestrial QKD infrastructure and explicitly excludes space-based segments. It estimates endpoint counts, trusted repeater node requirements, and hop-length distributions under realistic operational constraints. The Austrian case is then used as a baseline to derive scaling rules for other EU Member States based on population and geographic extent. The results provide first-order planning estimates for national QKD backbone sizes across Europe. These estimates are not intended as deployment designs but as planning-level references that support early-stage cost assessment and infrastructure dimensioning under the EuroQCI framework.