  We consider the problem of spectrum sharing in a cognitive radio system
consisting of a primary user and a secondary user. The primary user and the
secondary user work in a non-cooperative manner. Specifically, the primary user
is assumed to update its transmit power based on a pre-defined power control
policy. The secondary user does not have any knowledge about the primary user's
transmit power, or its power control strategy. The objective of this paper is
to develop a learning-based power control method for the secondary user in
order to share the common spectrum with the primary user. To assist the
secondary user, a set of sensor nodes are spatially deployed to collect the
received signal strength information at different locations in the wireless
environment. We develop a deep reinforcement learning-based method, which the
secondary user can use to intelligently adjust its transmit power such that
after a few rounds of interaction with the primary user, both users can
transmit their own data successfully with required qualities of service. Our
experimental results show that the secondary user can interact with the primary
user efficiently to reach a goal state (defined as a state in which both users
can successfully transmit their data) from any initial states within a few
number of steps.
