Dynamic Spectrum Allocation Using Quantum Annealing Considering Burstiness of Traffic

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 cause a combinatorial explosion, which requires an enormous amount of computation time. Saito et al. proposed a method to solve this combinatorial optimization problem using quantum annealing, and succeeded in significantly reducing the computation time (1). However, they focused only on the frequency requirements divided by each time axis and did not consider the requirements regarding the length of the time axis. Furthermore, considering bursty streams is important in DSA since internet traffic includes bursty streams. In this paper, we focus on the DSA problem of maximizing the satisfaction of time-based requests from each base station including bursty traffic and prioritized sessions, and describe the formulation for solving the problem using quantum annealing. Experimental validation using capable annealing machines confirms the efficacy of the proposed formulation in optimizing base station traffic demands within DSA. These results validate the feasibility of quantum annealing for DSA and provide valuable insights for further advancements in spectrum management.