# A GNSS/5G Integrated Three-Dimensional Positioning Scheme Based on D2D Communication
## 1 Introduction
It is obviously beneficial to improve the positioning accuracy and robustness by using different information from these two sources. Positioning based on D2D communication, referred to as D2D positioning, mainly depends on the distance estimation between the requesting nodes and the reference nodes, where the requesting nodes refer to the MUs requesting for their positions and the reference nodes refer to the BSs or the other MUs with known positions [21; 22]. Different measurements can be exploited for the distance estimation, such as time of arrival (TOA) and received signal strength (RSS). The TOA method requires time synchronization between the nodes, which increases the complexity and cost, while the RSS method is more cost-effective because of the intuitive transmitting and receiving features of the nodes. It is also proven in [23] that the TOA method is more accurate at long range in distance estimation, and on the contrary, the RSS method is more accurate at short distances. As such, the TOA and RSS measurements are usually jointly exploited for positioning in the mobile network. A hybrid TOA/RSS method was proposed in [24] to estimate the positions and obtain the CRLB of the positioning. The authors in [25] presented a data fusion framework based on the relationship between the TOA/RSS measurements and the distances. Notice that the distances obtained from the TOA/RSS measurements are three-dimensional, while the above literature only consider two-dimensional distances between the users. Certainly, it is essential to integrate the measurements from GNSS and D2D communication. As one of the most important algorithms for data fusion, particle filter (PF) is widely used in the integration of GNSS and other navigation methods [26]. [PERSON] et al. in [27] combined GNSS and cellular measurements by several kinds of Kalman filters (KFs), where the result of PF is represented as the lower bound because of its high accuracy. [PERSON] et al. in [28] integrated GNSS and D2D measurements by using PF and proved that the integrated algorithm outperforms the nonintegrated ones. Note that there are two kinds of nodes in cooperative positioning [29]: (i) fixed nodes, such as the BSs in 5G network (the positions of the fixed nodes are accurate), and (ii) cooperative nodes, such as the MUs (the position information of the cooperative nodes is usually inaccurate due to the instability of the positioning source signals and the influence of the signal transmission) [29]. According to the above literature, most of the positioning methods are based on the accurate position information of the known nodes, while it is not realistic. Therefore, it is nontrivial to consider the position accuracy of the cooperative nodes, which certainly influences the accuracy of the requesting nodes' positions. The authors in [29] proposed a D2D co-localization algorithm exploiting density-based spatial clustering of applications with noise (DBSCAN) to reduce the position errors of the cooperative nodes and show its effectiveness in the simulation results. In practice, more information results in heavier computation, whereas MUs only have limited computational capacity [9]. Due to the deployment of a large amount of ultra-dense edge devices, such as small-cell BSs and smart devices, the idle computation capacity of them is sufficient to enable ubiquitous mobile computing, denoted as edge computing [30]. Indeed, it is suitable for ubiquitous positioning in the GNSS/5G integrated positioning scheme. Thus, it has the potential to provide high positioning accuracy and robustness for the MUs. Motivated by the above literature, we study the GNSS/5G integrated three-dimensional positioning scheme based on D2D communication and consider the inaccurate position information of the cooperative nodes. The main contributions are summarized as follows:  
1. A GNSS/5G integrated three-dimensional positioning scheme is proposed, in which D2D communication is utilized to share the measurements and position information between the MUs.