Dynamic Spectrum Allocation for Bursty Traffic Using Quantum Annealing
Shuta Inoue, Yuusuke Kawakita, Yoshito Tobe · 2023
As the demand for wireless communications continues to grow, securing limited spectrum resources has become an issue. Under such circumstances, Dynamic Spectrum Allocation (DSA), in which existing frequency bands are jointly used and allocated to carriers, has been attracting attention. However, the problem is that a large number of base stations and interferers causes a combinatorial explosion, which requires an enormous amount of computation time. In a previous study, this problem was viewed as a combinatorial optimization problem and formulated to be solved by quantum annealing for the time slot-specific requirements of each base station. However, each base station uses the frequency band differently, and the timeslot length requirement must also be considered. In this paper, we focus on the DSA problem of maximizing the satisfaction of the time-based requirements of each base station and describe a formulation for solving the problem using quantum annealing. These time-based requirements can accommodate the demand for bursty traffic, which was not the case in previous papers. We also present implementation results using Fixstars Amplify and discuss future prospects.