Cooperative Localization in Massive Networks

Network localization is capable of providing accurate and ubiquitous position information for numerous wireless applications. This paper studies the accuracy cooperative network in large-scale networks. Based on a decomposition equivalent Fisher matrix (EFIM), we develop random-walk-inspired approach analysis EFIM, propose routing interpretation localization. Using this approach, show that large lattice stochastic geometric networks, when anchors are uniformly distributed, average error agents grows logarithmically with reciprocal anchor density an asymptotic regime. The results further illustrated using numerical examples.