Improving RF Fingerprinting Methods by Means of D2D Communication Protocol

Abstract

Radio Frequency (RF) fingerprinting is widely applied for indoor positioning due to the existing Wi-Fi infrastructure present in most indoor spaces (home, work, leisure, among others) and the widespread usage of smartphones everywhere. It corresponds to a simple idea, the signal signature in a location tends to be stable over the time. Therefore, with the signals received from multiple APs, a unique fingerprint can be created. However, the Wi-Fi signal is affected by many factors which degrade the positioning error range to around a few meters. This paper introduces a collaborative method based on device-to-device (D2D) communication to improve the positioning accuracy using only fingerprinting and the direct communication to nearby devices. The results presented in this paper show that the positioning error can be reduced around 44% by considering D2D communication in the operational stage without adding new infrastructure for fingerprinting or complex resource-consuming filters. Moreover, the presence of very large errors is significantly reduced when the collaborative positioning based on D2D is available.

Collaborative Indoor Positioning Systems: A Systematic Review

“…A majority of research focuses on positioning scenarios in existing buildings, some of them re-using already existing infrastructure (i.e., signals of opportunity). Typical scenarios that are receiving a growing interest involve locating people within houses, offices [ 63 , 115 , 123 , 131 ], and universities [ 40 , 43 , 63 , 79 , 98 , 101 , 119 , 120 , 128 , 131 ], where the viability of installing complex infrastructure is low in terms of costs, unlike industrial or warehouse scenarios, which are capable of developing and deploying robust and costly infrastructures designed for positioning. As a result, our review indeed shows that infrastructure-less approaches are predominantly selected for CIPSs in research (see Figure 4 c), and that the majority of technologies used (see Figure 5 and Figure 6 ) are already present in the environment.…”

“…Regarding stand-alone positioning in the non-collaborative phase, the most used methods were PDR [ 43 , 63 , 92 , 97 , 98 , 100 , 101 , 102 , 106 , 107 , 110 , 117 , 118 , 120 , 123 , 127 , 128 , 129 , 131 , 141 , 144 , 145 , 146 , 147 ], Ranging [ 42 , 46 , 47 , 81 , 93 , 109 , 111 , 113 , 130 , 132 , 144 , 150 ], RSS-based [ 40 , 41 , 43 , 48 , 77 , 84 , 89 , 103 , 123 , 129 ], k -NN [ 63 , 79 , 108 , 114 , 118 , 119 ,…”

“…The study selection process, with step-wise results, is schematically depicted using the PRISMA flow diagram in Figure 2 . As a final set of eligible studies, 84 articles [ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 63 , 77 , 79 , 80 , 81 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 ,…”

“…Note that collaborative approaches should not be confused with data or sensor fusion approaches. Whereas collaborative positioning is focused in systems whose independent actors (users or devices) exchange information and compute relative distances between them to provide the position of the set of users [ 77 , 78 , 79 , 80 , 81 ], sensor fusion combines information from various sensors from a single actor for providing the position of a single user [ 30 , 31 , 32 , 33 ].…”

Green Communications in Smart Cities

“…The algorithm makes use of the new range of smartphones, which can simultaneously receive dual-frequency signals from multiple GNSS. For indoor environments, a new collaborative method based on D2D communication is proposed in [8] to improve the positioning accuracy provided by the Wi-Fi fingerprinting method. The use of D2D communication not only increases the localization accuracy but also reduces the overall infrastructure requirements and computational complexity, and therefore contributes to achieving the objectives of green communication in smart city applications.…”