## 2 Related Work  
Traditional wireless channel modeling methods are mainly divided into deterministic modeling methods and statistical modeling methods. Deterministic channel modeling analyzes the fading mechanism of received signals based on electromagnetic wave transmission theory. [PERSON]'s equations, scatterers, environmental topography and other information are adopted by this method. In [1], [PERSON] et al. derived path loss and shadow models from simulated propagation data extracted from outdoor deterministic ray tracing models. Based on the statistical parameters of the urban environment in the target area, [PERSON] et al. proposed a radio frequency propagation model that predicted the path loss between the low-altitude platform and the ground receiver [2]. However, the accuracy of the deterministic modeling method depends on the database of the modeling environment, and it requires a lot of complex calculations. Thus this modeling method has certain limitations in the application scenario of emergency management. In addition, the Doppler frequency shift caused by the high-speed movement of the UAV was not considered in the above model building process. Statistical modeling methods can be divided into channel impulse response modeling and stochastic channel modeling. Channel impulse response modeling uses measurement equipment to measure and store the channel impulse response in real time. The stored  
Figure 1: The analysis of channel characteristics. data can be reused, and a simple mathematical model can be established based on the measured data. The models established by this method are mostly tapped delay line models. For example, [PERSON] et al. used a tapped delay line filter model with time-varying coefficients to model the channel [3]. It is assumed that the amplitude attenuation of the NLOS component obeys the Rayleigh distribution, and the multipath fading obeys the Gaussian distribution. Correspondingly, the probability density function is used by stochastic channel modeling to describe the channel fading parameters, and then the relevant parameters are adopted to establish a channel model of a similar communication environment. The classic stochastic channel model includes Rayleigh fading channel model [4], Rice fading model [5], lognormal fading model [6], [PERSON] model [7], and Clarke model [8] and other classic models. In addition, the stochastic model is helpful to analyze the time-varying characteristics of UAV channels [9]. The stochastic channel modeling method is suitable for designing various wireless communication systems. Statistical theory is adopted by this method to establish a reasonable channel model, and the physical meaning is relatively intuitive. Therefore, considering the channel characteristics and modeling complexity of the complex urban environment, the random channel modeling method is selected for follow-up research. In addition, in the past research on channel models, the research on typical ground-to-ground communications has been very mature. [PERSON] proposed a shadow fading model [10]. The statistics of the received signal are represented by the clustering of multipath components. However, the channel characteristics of the air-to-ground channel are different from that of the terrestrial communication channel. Compared with terrestrial communications, UAVs are in a complex and changeable wireless environment, and their BER requirements are much higher than those of traditional terrestrial wireless channels. The study of Doppler frequency shift which is a key parameter needs to be added to the calculation of channel parameters due to the high maneuverability of UAVs. On the other hand scholars have proposed improvements to the classic LOO model [11]. [PERSON] et al. researched on low-altitude channels in urban areas based on the LOO model, and also developed a narrowband time series generator [12]. However, this study did not pay attention to the important position of communication reliability in channel performance.