# Improving RF Fingerprinting Methods by Means of D2D Communication Protocol
## 2 Related Work  
D2D cooperative localization has received extensive interest from the robotics, optimization, and wireless positioning research communities [23; 24; 25]. The core concept of cooperative localization is the information exchange among users in order to increase their localization accuracy. Cooperative localization was initially considered for addressing the localization problem with limited information about the current position of the mobile unit [26], but this positioning approach can also been extended to those cases where the accuracy is around a few meters, as in Wi-Fi based fingerprinting, in order to obtain more accurate position estimates and reduce positioning ambiguities [27]. [PERSON] et al. [28] showed real-time fingerprint exchange among the users to refine UE's initial location. They achieved up to 43% error reduction for 200 user collaboration, but a collaboration of such a high amount of users might be impractical in some cases or scenarios. For 20 users collaboration, they found 16% mean location error reduction through their cooperative location refinement algorithm. For the experiments, they simulated a radiomap with the IEEE 802.11 channel and the indoor log-distance path loss model in a rectangular area of 80 \(\times\) 80 m\({}^{2}\) with 5 AP. [PERSON] at al. [29] proposed a solution to reduce the accumulative positioning error through cooperative positioning among multiple pedestrians using smartphone and pedestrian dead reckoning. Their proposed method introduces linkage structures to simplify the trajectories of pedestrians. These structures work as a constraint to reduce the number of variables to be estimated. Moreover, they introduced the concept of communications points, where the Wi-Fi ranging error is expected to be low. Therefore, the user's tracks can be correct using this information. They found the positioning accuracy improved as the number of participants in the cooperative positioning operation increased. Two experiments were conduced: the first one was indoors and using real data from smartphones and up to 8 people, the second one corresponded to a large-scale simulation. [PERSON] et al. [30] used round-trip time measurement for cooperative localization technique in LTE network, according to the performed simulations the higher number of collaborator, the higher positioning accuracy, but increasing number of candidates increases the complexity exponentially. They concluded ten candidates provide a balance between complexity and the performance under a LTE communication and positioning scenario. [PERSON] et al. [31] used particle filter to integrate RSS and TOA of RF signal for improving cooperative localization precise in indoor environment. But they used only three moving objects in their simulation along with eight fixed anchors. They concluded improvised positioning trend stemming from hybrid cooperative mode. [PERSON] et al. [32] showed smartphone based Wi-Fi signal measurements exchange via Bluetooth connection between the users. They used Bluetooth signal strength difference between users to calculate relative distance, which is used to evaluate the probability distribution functions of their states. Two simulation scenarios were carried out with 10 and 100 users. Their proposed method increases the average positioning performance by 28% and 22% respectively for the two cases. [PERSON] et al. [33] proposed a cooperative localization method to combine the fingerprint-based algorithm and the physical constraint of pairwise physical distances to refine the localization estimates for multiple users simultaneously. They found the number of peers and peers selection have a substantial impact on accuracy performance. The experimental area was a corridor surrounding a rectangular area. They selected 80 reference points in the corridor, where the distances between two adjacent points were around 1.5-3 m. A total of 150 combination of several predefined positions were used to simulate the multiple users condition.