Ultra-High-Speed Optimization for 5G Wireless Resource Allocation by Simulated Bifurcation Machine

Fifth-generation (5G) wireless communications technologies and beyond are expected to provide new value as basic technologies supporting the future of industry and society. To meet challenging 5G requirements such as increased capacities, faster data speeds, and lower latencies, it is increasingly important to rapidly optimize an enormous number of parameters. This paper focuses on resource allocation in ultra-reliable low-latency communication (URLLC) when mini-slots are used to allow user equipments (UEs) to communicate simultaneously at lower latency. We also propose an efficient algorithm for ultra-low-delay allocation. URLLC resource allocation with mini-slot optimization is complicated, and it is difficult to find optimal solutions within the low delays that 5G requires, even when using a simulated bifurcation machine, which is known to solve the optimization problem at high speeds. Therefore, we propose a two-step algorithm. In the first step, we solve a relaxed optimization problem, for which the simulated bifurcation algorithm works well. In the second step, we find the desired resource allocation by solving another optimization problem using the solution found in the first step and prepared statistical information on that solution. The experimental results show that the proposed SBM algorithm can be applied to URLLC resource allocation and achieves better quality than a greedy algorithm. Furthermore, we showed that the resource allocation can be completed in less than 0.5 ms, as required to achieve the minimum transmission delay of the 5G specification.