Optimizing E2E low-earth orbit satellite network

Abstract

Recent studies have shown promising results indicating the potential of Noisy Intermediate Scale Quan- tum (NISQ) devices. In this work, Low-earth Orbit (LEO) satellite network design problem is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem, and Quantum Annealing (QA) is utilized to solve the resulting problem in a real-world setting. Compare to classical approaches, the experimental results indicate improvements in terms of network path length and number of satellite hops in network path that amount to network latency. Further, an iterative post-processing method, Statis- tical Qubit Freezing (SQF), which freezes initial states of qubits and reduces the size of the problem in each annealing cycle, is proposed and evaluated. Solution found with SQF indicates that SQF in fact allows the system to reach lower energy state.