proposed an optimal entropy-based cooperative spectrum sensing in maritime cognitive radio networks [PERSON] et al. (2017). [PERSON] et al. presented a solution to overcome this spectrum scarcity issue by utilizing cognitive radio (CR) technology in the maritime Automatic Identification System (AIS) VHF network [PERSON] et al. (2017). [PERSON] et al. designed a cognitive layer stack and established the idea of software-defined maritime cognitive radio [PERSON] et al. (2017). Compared with cognitive radio on land, maritime cognitive radio has several differences:  
* Communications take place on ships, and the CBS is responsible for resource allocation and does not need to participate in data transmission. * Maritime cognitive radio has unique services, such as position reporting, early warning information, chart updates, meteorological information, and so on. Services that involve navigational safety generally have higher priority levels. The packet lengths of different services are quite different. High-priority services usually have much smaller packets to ensure the efficiency of communication. * The nodes that are used as CBSs depend on the usage scenario. As the ships are located near the coast, a shore station can be used. Alternatively, as the ships are navigating offshore, at sea, a buoy station should be used [PERSON] et al. (2017); [PERSON] et al. (2017). Dynamic spectrum allocation is based on the fact that not all users are active at the same time; it is a method that allows users to use the channel when the channel is idle [PERSON] et al. (2017); [PERSON] et al. (2017). At present, the common spectrum allocation models and algorithms rarely involve the communication between SUs, and discussions of the priority of SUs according to the service type are still few. Therefore, it is necessary to study the dynamic spectrum allocation algorithm of a maritime cognitive radio communication system. This paper proposes a DSA algorithm for a maritime cognitive radio communication system. In brief, the contributions of this paper can be summarized as follows:  
1. Based on the characteristics of maritime cognitive radio, a communication model of the centralized maritime cognitive radio communication system is proposed;
2. According to the communication model, a queuing model that contains two queues and multiple servers is established. The pre-classifier is set to divide the SUs into two queues due to the maritime service type. A two-dimensional Markov chain is used to analyze the queuing model; and
3. A DSA algorithm with priority factor is proposed. The priority factor is decided by the maritime service. Simulation results show that the algorithm can significantly decrease system congestion. The rest of the paper is organized as follows: In Section 2, we introduce the maritime cognitive radio communication model. In Section 3, a queuing model based on the communication model is presented and a DSA algorithm is proposed. In Section 4, we use a two-dimensional Markov chain to analyze the queuing model and provide the steady-state probability of each state. Section 5 discusses the simulation results of our proposed algorithm. Finally, the paper is concluded in Section 6.