Optimization of connection patterns between mobile phones and base stations using quantum annealing

Area of Science:

• Computer Science
• Quantum Computing
• Telecommunications Engineering

Background:

• Optimizing mobile phone connections to base stations is vital for communication quality.
• This is a complex combinatorial optimization challenge in mobile networks.
• Current methods face limitations with increasing network complexity.

Purpose of the Study:

• To optimize base station connection patterns for mobile phones using quantum annealing.
• To develop a qubit-efficient formulation for quantum annealing in this application.
• To compare the performance of the new formulation against conventional methods.

Main Methods:

• Utilized quantum annealing, a heuristic optimization algorithm leveraging quantum fluctuations.
• Developed and applied a variable reduction formulation to minimize qubit requirements.
• Conducted experiments on quantum annealing and simulated annealing to evaluate solutions.

Main Results:

• The variable reduction formulation significantly reduced qubit requirements compared to naive approaches.
• Quantum annealing experiments showed superior accuracy with the new formulation.
• The new formulation outperformed conventional methods as problem size increased, even with simulated annealing.

Conclusions:

• The proposed variable reduction formulation is effective for optimizing mobile network connections using quantum annealing.
• This approach offers a more qubit-efficient and accurate solution for base station selection.
• The findings suggest quantum computing can address complex optimization problems in telecommunications.