Thermoacoustic instabilities are a major issue for industrial and domestic burners. One possible framework to study these instabilities is to represent the system by a network of Dimensionless Acoustic Transfer Matrices (DATM) that link pressure and velocity fluctu- ations upstream and downstream each element of the network. In this article, the DATM coefficients of a turbulent swirling combustor are determined for a thermoacoustically stable configuration using harmonic acoustic forcing. Since the dynamics of the whole system is controlled by nonlinearities, the impact of the forcing level needs to be considered. The four DATM coefficients are thus measured for reactive operating conditions (premixed flame) and cold flow conditions for increasing acoustic excitation levels. The velocity level is con- trolled by a hot wire located inside the injector, in a region with a laminar top-hat velocity profile. The upstream and downstream specific acoustic impedances are also measured. Results for the acoustic response under cold flow conditions are first presented. In this case, the DATM coefficients are found to be independent of the forcing level except for the modu- lus of the coefficients linking the downstream velocity fluctuations to the upstream pressure and velocity fluctuations. This behavior is linked to the nonlinear response of the injector but is not entirely captured by the acoustic network model developed in this work. For reac- tive operating conditions, measurements indicate that all DATM coefficients depend on the forcing level to a certain extent. The Flame Describing Function, linking heat release rate fluctuations to velocity fluctuations, is used to reconstruct the transfer matrix through an acoustic network model. This network model accurately predicts the trend of the measured coefficients but the impact of the forcing level is not reproduced. Saturation for reactive operating conditions is shown to be not only related to the nonlinear flame response but also to the nonlinear injector dynamics. Finally, a data-driven reconstruction of the FDF using the acoustic network model along with the hot wire and microphone measurements is per- formed. This data-driven acoustic reconstruction is subsequently compared with the FDF determined with an optical technique.