  Modern radars often adopt multi-carrier waveform which has been widely
discussed in the literature. However, with the development of civil
communication, more and more spectrum resource has been occupied by
communication networks. Thus, avoiding the interference from communication
users is an important and challenging task for the application of multi-carrier
radar. In this paper, a novel frequency allocation strategy based on the
historical experiences is proposed, which is formulated as a Markov decision
process (MDP). In a decision step, the multi-carrier radar needs to choose more
than one frequencies, leading to a combinatorial action space. To address this
challenge, we use a novel iteratively selecting technique which breaks a
difficult decision task into several easy tasks. Moreover, an efficient deep
reinforcement learning algorithm is adopted to handle the complicated spectrum
dynamics. Numerical results show that our proposed method outperforms the
existing ones.
