# Earth-to-Earth Microwave Rain Attenuation Measurements: A Survey On the Recent Literature
## 6 Research Challenges
These algorithms' performance considerably rely on the network's structure. In [99], the statistical nature of cellular microwave network (CMNs) has been studied along with the establishment for this kind of model which is based on empirical results. In [59], authors examined through network management systems (NMS) the acquired attenuation measurements from two microwave links during the period of multiple rain events. They empirically demonstrated that the output of the NMS included bias, which interfered with the rain-estimation process. With the intension of using attenuation measurements, acquired from microwave links, for estimating the rain, the baseline attenuation level is necessary to be obtained. Current methods regularly exploit the low attenuation values which are observed during the periods prior to the beginning of the rain that has been defined as dry for determining the baseline attenuation level in the period of rainy activity. In the next work [87] are reviewed significant results and technologies oriented in more detail to the opportunistic-sensing idea. As far as the measurements-results that can be acquired for environmental sensing from commercial microwave links (CMLs), these can be further enriched because there is a capability of employing a vast number of virtual sensors with no cost at all. Two different approaches for environmental monitoring exist and these are the active and the passive one. The latter scheme uses records of network management systems (NMS) for accomplishing weather monitoring. Only the level values of minimum and maximum received signal (RSL) along with the transmitted signal (TSL) are saved at a rate of 15 min and a power resolution of 0.1-1 dB as aforementioned. These measurements are rarely available in real-time because they are typically used for analysis purposes. On the contrary, the active approach uses the simple network management protocol (SNMP) for acquiring weather monitoring measurements in real-time at small intervals of even 10 s. The additional unnecessary cellular network traffic can be avoided with the use of a dedicated server for such a kind of RSL measurements but a problem still exists and that is the permission from the provider to access the system behind the firewall. Additionally, many studies are reported to have been conducted for environmental monitoring such as rainfall sensing, rainfall mapping, humidity and fog sensing, precipitation classification, dew and pollution detection, and wind estimation. Additionally, works have been reported to contribute relevant to error analysis, i.e., the sources of errors such as general, dry/wet, wet antenna, calibration, quantization bias, non-linear preprocessing, and network topology. Furthermore, works suggesting algorithms for rainfall monitoring are reported such as instantaneous rain mapping, dynamic rain mapping, and heavy rain detection, combined with other measurements, rainfall tomography, accumulated precipitation, and various open software tools. Then, various applications are mentioned which are relevant to large scale rainfall estimation/mapping,rainfall measurements, flood prediction, disaster alarm, calibration of other sensors, and hydrology. Finally, the potential use of the aforementioned reviewed technology is shown and i.e., the covering of blind spots (no near-ground measurements are available), the monitoring accuracy improvement and the improvement of various meteorological and hydrological models. In [100], authors presented a theoretical analysis that justified the use of the lower attenuation values and proposed a systematic method, in order to estimate the baseline attenuation level in real-time, without needing a dry/wet classification. In [101] the authors elaborated on the use of microwave links from commercial cellular communication networks which were used in The Netherlands since 2003. In that work, authors reported on their experience on this topic starting back to 1999.