Blind estimation of wireless network topology and throughput

Wireless communications networks can be modelled as cascades of emission events, which makes them amenable to being modelled as multivariate Hawkes processes (MHPs). The MHP parameters can then be used to evaluate an attributability matrix, which describes the probability that each emission event can be attributed to previous events. Methods for inferring probabilistic adjacency matrices and network throughput estimates from these attributability matrices are demonstrated.