  Heterogeneous network (HetNet) has been proposed as a promising solution for
handling the wireless traffic explosion in future fifth-generation (5G) system.
In this paper, a joint subchannel and power allocation problem is formulated
for HetNets to maximize the energy efficiency (EE). By decomposing the original
problem into a classification subproblem and a regression subproblem, a
convolutional neural network (CNN) based approach is developed to obtain the
decisions on subchannel and power allocation with a much lower complexity than
conventional iterative methods. Numerical results further demonstrate that the
proposed CNN can achieve similar performance as the Exhaustive method, while
needs only 6.76% of its CPU runtime.
