In a practical molecular communication scenario such as monitoring air
pollutants released from an unknown source, it is essential to estimate the
location of the molecular transmitter (TX). This paper presents a novel Sensor
Network-based Localization Algorithm (SNCLA) for passive transmission by using
a novel experimental platform which mainly comprises a clustered sensor network
(SN) with 24 sensor nodes and evaporating ethanol molecules as the passive
TX. In SNCLA, a Gaussian plume model is employed to derive the location
estimator. The parameters such as transmitted mass, wind velocity, detection
time, and actual concentration are calculated or estimated from the measured
signals via the SN to be employed as the input for the location estimator. The
numerical results show that the performance of SNCLA is better for stronger
winds in the medium. Our findings show that evaporated molecules do not
propagate homogeneously through the SN due to the presence of the wind. In
addition, our statistical analysis based on the measured experimental data
shows that the sensed signals by the SN have a log-normal distribution, while
the additive noise follows a Student's t-distribution in contrast to the
Gaussian assumption in the literature