# Fast Connectivity Construction via Deep Channel Learning Cognition in Beyond 5G D2D Networks
## 4 Performance Analysis
### Experimental Results  
Figure 3 shows comparison results on the prediction success ratio of LMK according to the number of epochs for context training as well as the number of DNN layers of LMK. As shown in Figure 3a, the prediction success ratio converges to 0.86 at 900 epochs within 6.48 s of the training time. Figure 3b represents the results and changes in the number of DNN layers from 3 to 9. The results show that the number of layers affects decreasing prediction success ratio. Thus, 3 layers of DNN training are the best performance of prediction success ratio and training time.  
Figure 4 shows the comparison results for latency. The latency time of DN1, DN2, and DN3 for the proposed scheme is 15, 15, and 19, respectively. For the general connectivity scheme, the latency time of DN1, DN2, and DN3 are 23, 27, and 33, respectively. According to the results, the smartphone can maintain the network connection over the best MAC link to the DNs with low latency even though it is continuously moving. On average, the latency of the proposed scheme in terms of connectivity reconstruction is 11.3 s faster than general connectivity construction.  
In Figure 5, 100 data packets are transmitted for analyzing the connectivity construction. As shown in Figure 5a, total delivery time of the general connectivity construction take a long time than the proposed scheme because the general connectivity construction maintains the link connection even though the state of the link is not good. In addition,  
Figure 4: Latency of Routing Paths.  
Figure 3: Comparison of Prediction Success Ratio: (**a**) Numbers of Epochs and (**b**) Numbers of DNN Layers.  
there is a delay in which information to be sent cannot be transmitted for a reconnection time. On the other hand, since the proposed scheme is based on the MLP that can be used to detect the relative position when a specific signal combination is measured, the best link is selected. Therefore, in the case of D2D communication in which mobile nodes frequently reconnect, the proposed scheme can transmit data with low latency faster than the general connectivity scheme. In Figure 5b, the general connectivity scheme shows that the transmission ratio for packet data transmission is lower than that of the proposed scheme. The proposed scheme shows 100% of packet delivery ratio, while the general connectivity scheme shows 88% of packet delivery ratio.  
Figure 6a shows 70 data packets are transmitted while the mobile smartphone moves among DN1, DN2, DN3. The proposed scheme performs direct connection between devices to be transmitted irrespective of the link signal strength, and L3 transmission between nodes can be performed directly. Thus, it can be seen that 70 data packets are delivered directly to each DN. On the other hand, in the general connectivity construction method, data is transmitted only through the connection link to DN1, so both data to be sent to DN2 and DN3 are sent to DN1. Figure 6b measures the total delivery times to transmit the entire data with 70 data packets. The proposed scheme takes 96 s, whereas the general connectivity scheme takes 124 s of transmission time. This means that the proposed scheme shows performance improvement in relation to the transmission delay.