How Quantum Solutions Drive Telecom Network Optimisation
Telecommunications operators face increasing complexity in network design, optimisation and resource allocation. Traditional computing techniques are often stretched to their limits by the sheer scale and complexity of these challenges, particularly when dealing with NP-hard problems that exhibit exponential growth in complexity. Quantum computing, however, offers a fundamentally new approach.
Leveraging Amazon Braket and Amazon Bedrock, telecoms providers can begin to explore quantum-enhanced optimisation without heavy upfront investment.
A recent case study highlights how one operator used Amazon Braket to solve a particularly challenging problem: upgrading a microwave backhaul network to fibre with minimal cost and disruption.
Quantum computing for telecoms: real applications today
While quantum computing has seen experimental uptake in finance, chemistry and materials science, it is increasingly gaining traction in the telecoms sector. Applications range from network topology design and channel assignment to bandwidth allocation, scheduling, load balancing and fault detection.
These problems are often combinatorial in nature, making them extremely difficult to solve using classical methods at scale.
“Even as classical computers become increasingly powerful, they cannot overcome the exponential complexity of certain problems,” explain experts at AWS.
Quantum systems, by contrast, exploit superposition and entanglement to scale more favourably with problem size, providing a compelling advantage.
Case study: optimising a fibre backhaul upgrade
In the example set out, a telecom operator aimed to upgrade its existing microwave backhaul to fibre connections. However, they wanted to do so economically—minimising the number of fibre deployments while ensuring all Radio Access Network (RAN) sites had high-speed connectivity.
- Every RAN site must either be directly connected to the Core Network (CN) via fibre Or be within one microwave link of a fibre-connected site.
- All microwave links must connect to at least one fibre-connected RAN site, avoiding two-hop microwave paths to the CN.
It’s not merely a planning problem; it’s a classical Minimum Vertex Cover (MVC) problem in disguise. RAN sites are modelled as nodes in a graph and links as edges.
The goal is to find the smallest number of nodes (RAN sites) that cover all edges, for example, by connecting via fibre so that all other nodes are adjacent to one with a fibre link.
From theory to quantum execution
With the problem modelled as an MVC, engineers transformed the graph to identify the Maximum Independent Set (MIS)—the complement of MVC—using the QuEra Aquila Quantum Processing Unit (QPU) available on Amazon Braket.
In classical computing, solving MIS requires a brute-force exploration of all combinations, which is untenable at scale.
On the quantum side, however, “we use an algorithm that drives the physical quantum system to an energy minimum that corresponds to the optimal solution,” said AWS engineers.
Amazon Braket provides a managed environment for running such quantum workloads. At the same time, Amazon Bedrock’s generative AI capabilities power the interface and logic transformation, converting image-based network maps into graph structures for processing by the QPU.
Generative AI frontend with streamlit
To simplify user interaction, a Streamlit-based frontend enables engineers to input images of their network topology. They are converted into graph structures using an Amazon Bedrock Agent, which prepares the Atom Arrangement needed by the QuEra Aquila QPU.
The seamless integration of AI and quantum technologies showcases a complete solution pipeline, from human input to quantum optimisation, without requiring deep quantum expertise from telecom engineers.
A new era of network optimisation
By combining Amazon Braket’s quantum compute capabilities with Amazon Bedrock’s AI services, telecom operators can now tackle real-world network optimisation problems more efficiently and innovatively.
The quantum solution delivered a fibre deployment plan that satisfied all constraints while significantly reducing cost, demonstrating how these technologies are not just theoretical but commercially and technically viable today.
As AWS concludes: “This approach allows telecoms to access the power of quantum computing for practical, high-impact use cases—without the need for upfront investment or in-house quantum talent.” The result is a robust foundation for next-generation telecom networks built on cutting-edge computing.
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