Title: High-Speed Resource Allocation Algorithm Using a Coherent Ising Machine for NOMA Systems Show Chinese title

Title: 基于相干伊辛机的非正交多址系统高速资源分配算法

Abstract: Non-orthogonal multiple access (NOMA) technique is important for achieving a high data rate in next-generation wireless communications. A key challenge to fully utilizing the effectiveness of the NOMA technique is the optimization of the resource allocation (RA), e.g., channel and power. However, this RA optimization problem is NP-hard, and obtaining a good approximation of a solution with a low computational complexity algorithm is not easy. To overcome this problem, we propose the coherent Ising machine (CIM) based optimization method for channel allocation in NOMA systems. The CIM is an Ising system that can deliver fair approximate solutions to combinatorial optimization problems at high speed (millisecond order) by operating optimization algorithms based on mutually connected photonic neural networks. The performance of our proposed method was evaluated using a simulation model of the CIM. We compared the performance of our proposed method to simulated annealing, a conventional-NOMA pairing scheme, deep Q learning based scheme, and an exhaustive search scheme. Simulation results indicate that our proposed method is superior in terms of speed and the attained optimal solutions. Show Chinese abstract

Abstract: 非正交多址接入（NOMA）技术对于实现下一代无线通信中的高数据速率非常重要。 充分利用NOMA技术的有效性的关键挑战是资源分配（RA）的优化，例如信道和功率。 然而，这种RA优化问题属于NP难问题，使用计算复杂度低的算法获得良好的近似解并不容易。 为了解决这个问题，我们提出了基于相干伊辛机（CIM）的优化方法，用于NOMA系统中的信道分配。 CIM是一种伊辛系统，可以通过基于相互连接的光子神经网络的操作优化算法，在高速（毫秒级）下提供公平的近似解。 我们使用CIM的仿真模型评估了所提出方法的性能。 我们将所提出方法的性能与模拟退火、传统NOMA配对方案、基于深度Q学习的方案和穷举搜索方案进行了比较。 仿真结果表明，所提出的方法在速度和获得的最优解方面具有优势。