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Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. WiFi-based indoor localization has been attractive due to its open access and low cost properties. However, the distance estimation based on received signal strength indicator (RSSI) is easily affected by the temporal and spatial variance due to the multipath effect, which contributes to most of the estimation errors in current systems. In this work, we analyze this effect across the physical layer and account for the undesirable RSSI readings being reported. We explore the frequency diversity of the subcarriers in orthogonal frequency division multiplexing systems and propose a novel approach called FILA, which leverages the channel state information (CSI) to build a propagation model and a fingerprinting system at the receiver. We implement the FILA system on commercial 802.11 NICs, and then evaluate its performance in different typical indoor scenarios. The experimental results show that the accuracy and latency of distance calculation can be significantly enhanced by using CSI. Moreover, FILA can significantly improve the localization accuracy compared with the corresponding RSSI approach. [ABSTRACT FROM AUTHOR]

Globally unique ID allocation is usually not applicable in a sensor network due to the massive production of cheap sensor nodes, the limited bandwidth, and the size of the payload. However, locally unique IDs are still necessary for nodes to implement unicast communications to save power consumption. Several solutions have been proposed for locally unique ID assignment in sensor networks. However, they bring much communication overhead, which is not desirable due to the limited power supply in a sensor node. Combined with a directed diffusion communication paradigm, a reactive ID assignment scheme with security mechanisms is proposed in this paper. It defers ID conflict resolution until data communications are initiated and thus saves communication overhead. [ABSTRACT FROM AUTHOR]