###### Abstract  
6G is already being planned and will employ much higher frequencies, leading to a revolutionary era in communication between people as well as things. It is well known that weather, especially rain, can cause increased attenuation of signal transmission for higher frequencies. The standard methods for evaluating the effect of rain on symbol error rate are based on long-term averaging. These methods are inaccurate, which results in an inefficient system design. This is critical regarding bandwidth scarcity and energy consumption and requires a more significant margin of effort to cope with the imprecision. Recently, we have developed a new and more precise method for calculating communication system performance in case of rain, using the probability density function of rain rate. For high rain rate (above 10 mm/h), for a typical set of parameters, our method shows the symbol error rate in this range to be higher by orders of magnitude than that found by ITU standard methods. Our model also indicates that sensing and measuring the rain rate probability is important in order to provide the required bit error rate to the users. This will enable the design of more efficient systems, enabling design of an adaptive system that will adjust itself to rain conditions in such a way that performance will be improved. To the best knowledge of the authors, this novel analysis is unique. It can constitute a more efficient performance metric for the new era of 6G communication and prevent disruption due to incorrect system design. atmospheric propagation; communication system performance; attenuation; communication 202222226269  
28 July 20228 August 20228 August 20  
signal attenuation began in the 1940s, using rain gauges along the link path in order to correlate uniform rainfall with signal attenuation, where the received power was measured at intervals of 30 s [9]. In recent years, most work focuses on measurements from existing commercial microwave links [9; 10] and references therein. The symbol error probability can be found as a function of the attenuation. Attenuation as a function of rain rate has been widely calculated and measured [7; 8; 9; 10; 11; 12; 13; 14; 15; 16], with the standard statistical method being the ITU-R recommendations [17; 18; 19], where we focus on outdoor long-distance communication as relevant to satellite-ground links. The challenge is that the symbol error probability is a non-linear function in terms of signal-to-noise ratio and attenuation, which is correlated with the rain rate. Therefore, the present statistical method, using the average attenuation, is less precise, especially for the high frequencies that will be used soon. It is inaccurate because it does not consider the dynamic change in rain rate, which may at one moment be 10 mm/h, then, a few seconds later, may drop to 5 mm/h, and so on. The dynamics imply that the rain rate changes during a single rain event. Where in a single event, the rain can begin weakly, strengthen, and then become weaker. We use the statistics of the dynamic changes to achieve greater imprecision in the calculation of error, the required transmitter power, and the level of interference. In this work, we derive a closed mathematical formula for the probability of symbol error rate as a function of the rain rate probability density function (pdf). The unique aspect of our work is that we consider the dynamic nature of the rain rate during a short-term rain event. Since the symbol error rate is a non-linear function, the use of various accepted methods can be imprecise in some cases. In addition, our work differs from accepted statistical methods, such as the ITU-R recommendations, as follows:  
ITU-Rec. 618-13 calculates long-term rain attenuation statistics from the point rainfall rate obtained through the power law [18]. In contrast, we are interested in the probability of symbol error for a particular rain event.