# Earth-to-Earth Microwave Rain Attenuation Measurements: A Survey On the Recent Literature
## 4 Rainfall Measurements Through Backhaul Cellular Infrastructure
They managed to calculate with high accuracy the spatial distribution and thus the intensity of the rainfall [39]. In West Africa, in Burkina Faso, the marked and received signals were recorded every second with a precision of 1 dB over a 29 km wireless link while the operating frequency was 7 GHz [40]. Evaluation of signal data was done with a tipping bucket rain gauge in time intervals of five minutes. The rain gauge was on the MWL path. Data were received from July to September 2012. Additional high-resolution X band radar data were used to correlate the received data. The authors in [41] (\"Precipitation Classification Using Measurements from Commercial Microwave Links\") confronted the need for precipitation classification originated from RSL measurements inside various commercial wireless networks. They introduced a tree of classification whereas it resulted in an agreement (85%) to a meteorological device known as a disdrometer. The latter one acquired measurements with a rate of 15-min (resolution) while the measurements were distinguished into three categories such as (1) pure rain, (2) a mix of snow, sleet, and rain (\"sleet\") and (3) no precipitation (\"dry\"). Specifically, the proposed tree classification was directly related to different phenomena, i.e., wet periods were identified, and then their classification was accomplished concluding to pure rain or sleet as already mentioned. Nevertheless, the basic idea of a commercial microwave network (CMN) RSL measurements related to attenuation from precipitation was introduced by the same authors in [42]. Consequently in [41], a framework is given for classifying the precipitation by using CMN as a wireless distributed sensor network (WDSN) whereas the CMN RSL measurements served as input to the pattern recognition (PR) system. In turn, significant contributions were the prototype PR system for classifying the precipitation type and a novel method for the same purpose but only for existing measurements of CMN RSL. In turn, the validation purposes were based on testing under real conditions (a few fixed line-of-sight radio links of Israeli Cellcom with working frequencies at 18.36 GHz [vertical polarization] and 19.37 GHz [vertical and horizontal polarization] thus the classification performance was shown with the help of receiver operating characteristic (ROC) analysis [41]. A research team from Ateneo de Manila University used the existing structure of 5 GHz Smart Bro fixed wireless network in the Philippines [43]. Signal levels from over 700 subscribers with one min update were used. The data were obtained from July 2012 till the end of 2013. The classification of rain events was based on sigma level parameters. Visualization of sigma levels for highly intense rainfall events was also done via color code on maps. The main goal was to determine the rain-induced attenuation from measurements of a received signal level using wireless links at frequencies of 13 GHz and 15 GHz, leading to the construction of an empirical prediction model [44]. A polynomial attenuation model was considered and compared with the power-law of ITU-R and, it was found to have less error on predicting rain attenuations. In a case study in Prague, Czech Republic [45], microwave links with few seconds of temporal resolution were used to evaluate the precipitation along with multiple rain gauges. The experimental setup consisted of 14 microwave links operating at frequencies between 25 and 39 GHz, and 3 rain gauges covering a total area of 2.3 km\({}^{2}\). Data were collected remotely by the links with a rate of 5 times per min. Path-averaged quantitative precipitation estimations were computed according to power law, \(k=aR^{b}\), where \(R\) corresponds to the average rain rate which is measured in mm/h, \(k\) is the attenuation in dB/km and \(a\), \(b\) are the model parameters depending on frequency, polarization, rain drop temperature and size distribution [27], obtained directly by ITU [46].