  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.
