Propagation controlled cooperative positioning in wireless networks using bootstrap percolation

In this paper, bootstrap percolation is introduced to control the information propagation for efficient cooperative positioning in wireless networks. Particularly, we obtain a novel linear least square (LLS) estimator for the localization of agent nodes. Exploiting the idea of bootstrap percolation, agent nodes sequentially get activated and estimate their positions with an adaptive location updating rule. The rule is designed to first localize the more reliable agent nodes with at least three connections to the active nodes, and then gradually relax such connection constraints in each iteration so as to localize the agent nodes with fewer connections. Due to the activation characteristic, error propogation can be mitigated and energy is well managed. In addition, taking the uncertainty of the positional information into account, positioning errors can be further reduced. Simulations show that the proposed schemes improve the localization accuracy and use fewer links than traditional methods.