# A GNSS/5G Integrated Three-Dimensional Positioning Scheme Based on D2D Communication
## 4 Discussion  
The proliferation of various LBSs requires more precise and reliable positioning, whereas the emergence of 5G provides new visions for positioning. Its disruptive technologies are expected to achieve high-accuracy positioning, such as D2D communication, ultra-dense network, edge computing and mmWave communication. Thus, the combination of GNSS and 5G to provide accurate positioning has attracted much attention from researchers. Especially, D2D communication allows two MUs in proximity to communicate directly without being relayed by the BS, which makes it possible for a requesting user to connect other MUs and obtain more measurements for positioning. Actually, unlike the BSs, many MUs know their positions while the information is not accurate. We exploited the DBSCAN algorithm to reduce the uncertainty of their position information, and the positions of the requesting nodes were also obtained based on the GNSS and TOA/RSS measurements in the 5G network. After that, the PF algorithm was utilized to further improve the positioning accuracy of the requesting nodes.  
There are some conclusions based on the numerical simulation results as follows:  
1. It is clear in Figure 4 that, after the clustering, the data points that represent the positions of the MUs with high density gather in clusters, while the abnormal data points are deleted. In this case, the cooperative nodes can obtain more accurate position information, as well as the requesting nodes.
2. We can see in Figure 5 that, in the circumstance of inaccurate cooperative nodes' positions, we can hardly achieve accurate positioning for the requesting nodes with the PF algorithm only. Nevertheless, the positioning accuracy can be further improved by the PF algorithm after the DBSCAN process.
3. The joint TOA/RSS method was used in our scheme since these two kinds of measurements can complement each other with different advantages. Figure 6 verifies that the joint TOA/RSS method can achieve the best performance compared with the algorithms with only one kind of measurement.
4. Figure 7 illustrates the positioning performance of the proposed algorithm when the requesting node is on the move, and it proves that the algorithm also suits the dynamic condition well.
5. In terms of PF, it is found in Figure 8 that more particles result in lower RMSEs for positioning, which is consistent with the property of the PF algorithm.  
was proposed to further integrate the above results. Simulation results demonstrated that our proposed algorithm brings substantial performance improvement towards the RMSEs of the requesting nodes, whether they are fixed or on the move. Moreover, the proposed algorithm not only performed better than the other algorithms when the DBSCAN or PF algorithm is separately exploited, but it was also better than the algorithms using only the TOA or RSS measurements.  
Conceptualization, W.Z. and Y.Y.; methodology, W.Z. and A.Z.; software, W.Z. and Y.X.; validation, W.Z. and Y.X.; formal analysis, W.Z. and Y.Y.; investigation, W.Z. and A.Z.; resources, W.Z.; data curation, Y.X.; writing--original draft preparation, W.Z.; writing--review and editing, Y.Y. and Y.X.; visualization, W.Z.; supervision, A.Z.; project administration, Y.Y.; funding acquisition, Y.Y. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
This work is supported by National Natural Science Foundation of China (Grant No. 41931076) and National Key Research and Development Program of China (Grant No. 2020 YFB0505800).  
The authors declare no conflict of interest.