## 6 Conclusions and Outlook  
In this article, we provide a systematic overview of rainfall measurement techniques based on CMLs and summarize current challenges and possible future research directions. Compared to dedicated rain sensors, CMLs can economically provide near-surface precipitation information with a high spatial and temporal resolution and wide coverage,which can effectively complement dedicated precipitation observations. Within the past 20 years, scholars have comprehensively studied the processing flow of CML data and made great progress. However, the technology still faces some challenges [40; 221; 222]. Most importantly, breakthroughs must be made in data acquisition and CML data with high temporal and quantization resolutions may bring new insights into dry and wet period classification, baseline estimation and WAA correction. Encouragingly, a number of research groups have recently openly shared their high-quality datasets [169; 170; 223], making a critical contribution to the investigation of CML technology.  
Another practical challenge is the gradual replacement of CMLs by fiber optic communication technologies. Due to the advantages of fiber optic transmission, such as high speed, low loss, high interference immunity and large information-carrying capacity, there is a tendency for the proportion of fiber optics to gradually increase in cellular communication networks. However, considering the difficulty and high cost of fiber deployment, developing countries, where CMLs have the greatest potential, will continue to rely on CMLs for a long time to come. Moreover, low-frequency non-line-of-sight links between cell towers and cellphone terminals have also shown potential to estimate precipitation, which could be an alternative in areas where the number of CMLs is decreasing.  
As the demand for bandwidth continues to increase, the frequency of CMLs will expand towards higher frequencies in the future, which opens up the possibility of monitoring water vapor and improving the accuracy of light rain inversion. However, a systematic error analysis of rainfall inversion with high-frequency CMLs, especially for the \(\gamma\)-\(R\) relationship, is needed before application.  
An additional issue that has not been widely investigated but is highly desirable is the productization and commercialization of rainfall estimates based on CMLs. While many studies have demonstrated that CMLs can provide reliable rainfall estimates or improve dedicated precipitation products, only a few operational precipitation products from CMLs have been reported so far [196]. On the one hand, rainfall inversion algorithms based on CMLs still face some challenges, as described in Section 4. On the other hand, and more importantly, in order to provide 24/7 real-time rainfall products, operators need to ensure reliable real-time availability of CML data, which entails additional costs and potential commercial confidentiality issues. Achieving this goal may be able to enhance collaboration between researchers and mobile network operators.  
To conclude, we hope that our analysis and comments on the technique will help researchers recognize the current challenges and conduct further research.  
Conceptualization, P.Z. and X.L.; methodology, P.Z. and X.L.; validation, P.Z. and K.P.; formal analysis, P.Z. and K.P.; investigation, P.Z. and K.P.; resources, X.L.; writing--original draft preparation, P.Z.; writing--review and editing, X.L. and K.P.; visualization, P.Z. and K.P.; supervision, X.L.; project administration, X.L.; funding acquisition, X.L. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China (Grant No. 42222505) and the Excellent Youth Scholars of Natural Science Foundation of Hunan Province of China (Grant No. 2021 JJ20046). The authors thank the editor and anonymous reviewers for providing helpful advice. The authors declare no conflict of interest.