  Resource allocation is of great importance in the next generation wireless
communication systems, especially for cognitive radio networks (CRNs). Many
resource allocation strategies have been proposed to optimize the performance
of CRNs. However, it is challenging to implement these strategies and achieve
real-time performance in wireless systems since most of them need accurate and
timely channel state information and/or other network statistics. In this paper
a resource allocation strategy based on deep neural networks (DNN) is proposed
and the training method is presented to train the neural networks. Simulation
results show that our proposed strategy based on DNN is efficient in terms of
the computation time compared with the conventional resource allocation
schemes.
