## 5 Implementation and Performance Analysis
### Number of CCs Is Fixed  
The number of CCs is fixed, which means that SUs cannot meet the SUs' delay requirement by aggregating the different number of CCs. SUs can adjust the payload size \(F\) for each SU's packet transmission. Assume there are 4 CCs and all of CCs are used for the SUs' data transmission. Each CC has same condition as shown in Table 1. Here, we only analyze the performance of the proposed RT-CCCS scheme when the number of CCs is fixed and equal to 4.  
The simulation results presented in Figure 8 show the maximum payload size of each SU packet which can be reached within the system delay requirement for RT-CCCS under different SU and PU arrival rates. In this simulation, the system delay requirement is 200 ms. From Figure 8, it can be observed that the maximum payload size of each SU's packet is related to the SU and PU arrival rates. The maximum payload size decreases with the increase of the SU or PU arrival rate. This means that  
Figure 7: Resource efficiency of RT-CCCS and Ceq-CCCS under different SU and PU arrival rate (_F_ is fixed and equal to 1 Mbits).  
the maximum payload size of each SU's packet should be reduced to meet the system delay requirement when the SU or PU arrival rate increases.  
When \(F\) is equal to the corresponding maximum payload size of each SU's packet, the average delay times of RT-CCCS under different SU and PU arrival rates are shown in Figure 9. The corresponding maximum payload size of each SU packet is each SU packet's maximum payload size which can be reached within the system delay requirement under different SU and PUs arrival rates, and it is shown in Figure 8. In this simulation, the system delay requirement is 200 ms. The traffic dispatching granularity of RT-CCCS is a sub-frame duration and it is 1 ms. PUs will occupy the whole sub-frame duration when PUs' signals appear in the middle of a sub-frame duration. This indicates that the actual corresponding maximum payload size is lower than that calculated by Equations (11)-(13). Therefore, when there are PUs in the CR-based SA system, we adjust the actual corresponding maximum payload size by subtracting a fixed size from the maximum payload size shown in Figure 8. This leads to an average delay time of RT-CCCS (\(\lambda_{pu}=0\)) between other two cases, and this result is acceptable. We can see that the average delay time of RT-CCCS is approximately equal to 200 ms under different SU or PU arrival rates. These are the results that are expected in this paper.  
Figure 10 presents the resource efficiency of RT-CCCS under different SU and PU arrival rates when \(F\) is equal to the corresponding maximum payload size of each SU's packet. From Figure 10, we note that the SU and PU arrival rates have different effects on the resource efficiency of RT-CCCS. The different effects can be clearer and more obvious than that in Figure 7. The simulation results show that the resource efficiency of RT-CCSS is more influenced by the SU arrival rate than the PU arrival rate. The resource efficiency of RT-CCSS increases with the SU arrival rate, and it is much different with the PU arrival rate.  
Figure 8: Maximum payload size of each SU packet which can be reached within the system delay requirement for RT-CCCS under different SU and PU arrival rates.  
When the payload size of each SU packet is less than the corresponding maximum payload size, the average delay time of RT-CCCS can meet the delay requirement. Therefore, we can draw the conclusion that the proposed RT-CCCS scheme can be used to meet the SUs' delay requirement when SUs adopt the SA technology in the CR network.