Deep Learning Based Resource Assignment for Wireless Networks

This paper studies a deep learning approach for binary assignment problems in wireless networks, which identifies variables permutation matrices. poses challenges designing structure of neural network and its training strategies generating feasible solutions. To this end, develop new Sinkhorn learns non-convex projection task onto set An unsupervised algorithm is proposed where the can be applied to problems. Numerical results demonstrate effectiveness method various scenarios.