A Review on Rainfall Measurement Based on Commercial Microwave Links in Wireless Cellular Networks

Abstract

As one of the most critical elements in the hydrological cycle, real-time and accurate rainfall measurement is of great significance to flood and drought disaster risk assessment and early warning. Using commercial microwave links (CMLs) to conduct rainfall measure is a promising solution due to the advantages of high spatial resolution, low implementation cost, near-surface measurement, and so on. However, because of the temporal and spatial dynamics of rainfall and the atmospheric influence, it is necessary to go through complicated signal processing steps from signal attenuation analysis of a CML to rainfall map. This article first introduces the basic principle and the revolution of CML-based rainfall measurement. Then, the article illustrates different steps of signal process in CML-based rainfall measurement, reviewing the state of the art solutions in each step. In addition, uncertainties and errors involved in each step of signal process as well as their impacts on the accuracy of rainfall measurement are analyzed. Moreover, the article also discusses how machine learning technologies facilitate CML-based rainfall measurement. Additionally, the applications of CML in monitoring phenomena other than rain and the hydrological simulation are summarized. Finally, the challenges and future directions are discussed.

Recording Rainfall Intensity: Has an Optimum Method Been Found?

“…Essentially, the more intense the rainfall along the microwave path from transmitter to receiver (mm h −1 ), the greater the signal attenuation (dB). Figure 2 in Lian et al [185] illustrates this relationship with data from two days with intermittent rainfall. The potential utility of these CML-based methods is that there is a large network of devices already installed, and the network is particularly dense in urban areas where rapidly acquired rainfall data could be of great value in the prediction of flash flooding.…”

“…These include attenuation on commercial microwave links (CMLs) such as those that form cellular telephone networks (Roversi et al [184]), as well as links that carry data to and from satellites. Lian et al [185]) provided a recent review. Essentially, the more intense the rainfall along the microwave path from transmitter to receiver (mm h −1 ), the greater the signal attenuation (dB).…”

Special Issue “Rain Sensors”

“…The paper by Lian et al [ 20 ] contains a comprehensive survey on rainfall estimation based on opportunistic measurement of the extra attenuation introduced by the rain on CMLs, such as the fronthaul/backhaul communications among base stations of mobile networks. The paper introduces the basic principle of this technique, reviewing the state-of-the-art solutions for the different steps of signal processing, also addressing uncertainties and errors involved in each step, as well as their impacts on the accuracy of rainfall measurement.…”

An Online Training Procedure for Rain Detection Models Applied to Satellite Microwave Links

“…This mechanism removes the measures corresponding to the oldest day of observations from T α while adding the new day. By doing so, the number of data in the set remains constant during training, which helps to mitigate the bias introduced by the seasonality of the data [21].…”