  Based on the theory of the Federal Communications Commission, the spectrum
available on cognitive radio networks is limit and the non-optimal use of the
spectrum necessitates the need for a telecommunications model, so that this
pattern can exploit the existing spectral positions. In this spectrum
subscription scenario, when the primary users are not present, it is also
possible to assign this telecommunication to tenants who are unauthorized or
secondary. The challenge of using this scenario is to allocate time-frequency
resources to them and how to access nodes in one channel without any
interactions between primary and secondary users and the throughput will
increase. The main idea of this research is using chaotic recurrent neural
network for improving access to spectrum in congestion times and the main
purposes are reduce interference and increase throughput in cognitive radio
networks. In this method, in addition to the throughput, the amount of unwanted
blockage of packets, the reduction of the cost of operations for secondary
users, the hardware requirements for secondary users and the coefficient of
justice are considered which in fact, it is a new channel assignment process
with respect to the environment response, the updates the probability that the
channels are empty in subsequent periods, and increases the permeability by
reducing interference with chaotic recurrent neural network.
