Applying Coherent Ising Machines for Enhancing Communication Efficiency in Large-Scale UAV-Aided Networks

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Abstract
Unmanned aerial vehicles (UAVs) are used widely in wireless communications to enhance the service experience of mobile users on the ground. This study investigates a dynamic resource management problem in a large-scale UAV-aided wireless network, where multiple UAVs operate as aerial base stations to serve ground users. To enhance communication efficiency for all users in the presence of co-channel interference, we proposed the use of an Ising model-based optimization method for fast and accurate UAV-user association and resource allocation. First, we formulated the dynamic user association and resource allocation problem as a combinatorial optimization problem. Subsequently, We transformed the objective function in the formulated problem into the energy function of a quadratic unconstrained binary optimization (QUBO) model and applied Coherent Ising Machine (CIM), which has been proven to be robust for solving dense Ising problems. We elevated our proposed method through simulations using CIM for optimization. Additionally, we compared our method with simulated annealing, steepest descent, and exhaustive search. Simulation results indicate that our proposed method is superior in terms of computational time and data rate.
Funding Information
  • Japan Society for the Promotion of Science (JP22K14263, JP20H05921, JP22H05197, JP23K22763)
  • Institute of AI and Beyond of UTokyo
  • AI Center of UTokyo
  • Japan Agency for Medical Research and Development (P23dm0307009)
  • Japan Science and Technology Agency (JPMJMS2021)

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