Parametric Message-Passing for Joint Localization and Synchronization in Cooperative Networks

Location awareness becomes an essential requirement for numerous applications and services in the future wireless communications. This paper addresses the problem of joint localization and synchronization in a network with cooperative nodes. The focus of this work is on the design of a low-complexity yet near-optimal message-passing implementations. To avoid the high-complexity of applying particle filtering-based approaches, we suitably augment the factor graph by introducing auxiliary variables. Then we propose a hybrid method that combines belief propagation (BP) and mean field (MF) message passing, which are used for message updating in the synchronization and localization parts of the factor graph, respectively. As a result, all messages on factor graph can be represented in parametric forms such that the proposed algorithm features a significantly low complexity while achieving near-optimal positioning performance.