## 2 Current Cognitive Radio Research and Development for Military Usage  
Currently, the United States uses Link-16 tactical communications networks that are equipped with direct sequence spread spectrum (DSSS) and frequency hopping (FH) for jamming the enemy's communications and defending against attacks [10,11]. Link-16 is based on a non-IP-type fixed hardware platform. Due to the limited spectrum resource, it is necessary to define the number of users and the frequency hopping pattern beforehand. Because of Link-16's style of predefined fixed wireless resource allocation, it is difficult to use in a modern weapon system' wireless network, which has an increased need for high-capacity data transmission.  
DARPA in the United States developed its XG program to realize a cognitive engine whose major role is the acquisition of the surrounding radio resources via spectrum sensing equipped with a cognitive radio engine, which consists of a policy engine (composed of the learning and reasoning engines) that helps new entrants of tactical wireless networks to acquire appropriate frequencies while avoiding interference with preexisting incumbent users [10]. The cognitive radio engine platform is based on the policy engine developed by DARPA XG, and it is broadly composed of \"policy language\", \"on-node policy components\", and \"off-node policy components\" [12]. One of the \"on-node policy components\" is the \"Policy Database\", which stores the policy reasoning data and policy priorities generated by the \"Policy Conformance Reasoner\", including the policy data for using cognitive radio nodes [13]. The learning engine introduced in the XG program stores policy strategies on the existing PU-occupied channels, and the reasoning engine arranges the priority of these channel for data transmission by the learning engine. The policy strategy, expressed in data format, is renewed by comparing the PU's occupied channel data acquired at the current time point with a reference--the previously-stored occupied channel history--and then, the renewed data are sent to the learning engine. The proposed learning engine can be seen as the \"Policy Database\" entity in DARPA's policy engine, and the reasoning engine can be considered to play the role of the \"Policy Conformance Reasoner\".  
The IEEE P1900.5 standard presents the functional definition and requirements relevant to a cognitive radio engine and policy language deployable to policy-based wireless systems [14; 15; 16]. Table 1 shows the main components and functions that comprise the cognitive radio engine proposed by the IEEE P1900.5 standard. Figure 2 shows the data transfer flow and the related interface between the cognitive radio engine components described in Table 1.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Components** & **Main Functions** \\ \hline \multirow{3}{*}{\begin{tabular}{c} PMP \\ (policy management point) \\ \end{tabular} } & Provide and manage policy information related to radio regulations \\  & and provide new policy data. This corresponds to frequency managers, \\  & system administrators, and operators \\ \hline \multirow{3}{*}{\begin{tabular}{c} SSRC \\ (system strategy \\ reasoning capability) \\ \end{tabular} } & Opportunistically check for access opportunities using REM (radio \\  & environment map) data and request information on whether or not \\  & transmission to PCR is possible \\ \hline \multirow{3}{*}{\
\begin{tabular}{c} PCR \\ (policy conformance \\ reasoner) \\ \end{tabular} } & Compare SSRC requests and existing policies transmitted from the PMP, \\  & perform the reasoning process, verify the suitability of changed policies, and \\ \cline{1-1}  & approve or reject SSRC requests \\ \hline \multirow{3}{*}{
\begin{tabular}{c} PE \\ (policy enforcer) \\ \end{tabular} } & Execute communications service based on verified policy information \\ \cline{1-1}  & transmitted from the PCR or SSRC \\ \hline \hline \end{tabular}
\end{table}
Table 1: IEEE P1900.5 standard’s cognitive radio engine components [17].