Connectivity-Based Centroid Localization Using Distributed Dense Reference Nodes

Abstract

Abstract-The accuracy of centroid localization based on the connectivity information between a target node and multiple randomly scattered reference nodes is investigated. First, the accuracy of the centroid localization is analyzed in a general fading environment and it is shown that the ambiguity area of this localization technique is inversely proportional to the density of the reference nodes. Additionally, this area is at the same order and in the best case half of the ambiguity area provided by estimating the location of a target node as the location of its nearest reference node. Furthermore, increasing the transmission power of a target node will increase the accuracy of the localization, but only up to a certain limit. Then, the findings on centroid localization are verified by computer simulations.

Connectivity-Based Localization in Ultra-Dense Networks: CRLB, Theoretical Variance, and MLE

“…Compared with range-based localization using the TOA, TDOA, RSS, and AOA measurements, the range-free method makes no assumption about the availability or validity of such information and only utilizes connectivity information to locate a BN. For a UDN, such as a wireless sensor network (WSN) or Internet of Things (IoT), nodes are usually low-cost and low-power and have no ability to obtain high-precision measurements of the TOA, TDOA, RSS, or AOA [26], [29]. Because of the hardware limitations and power constraints of nodes, range-free localization is often a preferred solution for UDNs [27].…”

“…Additionally, the high-density nodes in a UDN can further improve the performance of the range-free method. Several range-free methods have been addressed in the literature [26]- [31]. A well-known method of range-free localization is centroid-based localization (CL) [28], where the centroid of the RNs detecting a BN is estimated as the BN's position.…”

“…Subsequently, localization and tracking methods [27], [30], [31] that consider the connectivity information and motion model of a BN were designed for mobility-assisted WSNs. In addition to the above location schemes, some theoretical analyses for performance evaluation on range-free localization were presented in [26], [27], [31]. The authors in [27] derived the spatially averaged area of the location region and the localization error probability assuming that the RNs are scattered according to a Poisson point process.…”

“…The maximal localization error of mobility-assisted WSNs was addressed in [31]. A theoretical variance was presented in [26] to provide a performance analysis for the CL method based on the uniform distribution of RNs' positions.…”

“…Although several performance analyses have been presented for range-free localization [26], [27], [31], determining the best achievable positioning accuracy of range-free localization remains an open problem. All the current performance analyses [26], [27], [31] of range-free localization are used to evaluate the real performance of a given algorithm, whereas the proposed CRLB provides a benchmark to evaluate the performance of any unbiased range-free location algorithm and determines the physical impossibility of the variance of an unbiased estimator being less than the bound. To the best of our knowledge, this is the first time in the literature that the CRLB for range-free localization has been derived.…”