Clock synchronization and ranging are important topics in the field of wireless networks, where internode time measurement allows both tasks to be completed in one. Such networks are generally time-variant due to possible changes in environmental conditions and mobility of network nodes. We present a fully distributed filtering algorithm for combined clock synchronization and ranging based on message passing by belief propagation on a factor graph representation of a time-variant wireless network. The resulting message passing equations can be interpreted as a variant of Kalman filtering locally on each network node. Simulation results show that tracking estimation parameters improves estimation accuracy significantly without additional communication effort.

Many emerging technologies for wireless networks (WNs) require decentralized synchronization and ranging, i.e., distance estimation between neighboring pairs of nodes. Both tasks are related to each other when they are based on time measurements between nodes. Revealing this connection, we present a mean field (MF) message passing algorithm for cooperative simultaneous ranging and synchronization (CoSRAS), which jointly estimates the internode distances and clock parameters in a fully distributed way. It is shown that the use of the MF method reduces the computation and communication efforts compared to other message passing methods. For MF message exchange between nodes, only broadcast communication is required. Our simulation results demonstrate the equivalence in performance with centralized state-of-the-art joint ranging and synchronization algorithms.