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Q-SATELLITE

A key issue in satellite networks, also relevant to wireless networks, is the coverage problem. In this application, we examine an optimization challenge: dividing a set of satellites into smaller groups, known as the Weighted K-Clique Problem. The objective is to assign each satellite to a subgroup in a way that maximizes total coverage over a specific region on Earth

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Citynow Asia
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telecommunication

KEY FEATURES

  1. Optimized Satellite Grouping: Efficiently divides satellite constellations into sub-groups to maximize Earth region coverage.

  2. Coverage Maximization: Ensures target regions are covered by at least one satellite for the maximum time possible.

  3. Quantum-Enhanced Optimization: Uses quantum annealing to solve the Weighted K-Clique Problem faster and more efficiently.

  4. Scalability: Reduces computational complexity with the Quantum Approximate Optimization Algorithm (QAOA).

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Added: 04/03/2024
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