Due to the special environment of mines, further research is needed to study the wireless signal transmission characteristics in coal mine tunnels and establish a comprehensive and accurate wireless signal propagation model to ensure the stable operation of underground mine communication systems. The ray-tracing method and its hybrid versions are often used when studying the wireless signal transmission characteristics of mine roadways. The ray-tracing methods mainly include the image method and the shooting and bouncing ray (SBR) method. Ref. [16] improved the ray-tracing method and studied the transmission characteristics of wireless signals at two frequencies, 2.45 GHz and 5.7 GHz, in subway tunnels. In the improved ray-tracing method, the surface of the intersection point of the ray path, and the environment can be determined in advance, which improves the algorithm's efficiency. The calculation accuracy of the image method is related to the number of images, i.e., more images lead to a greater number of reflection points and reflection lines. As a result, the computational complexity of the image method increases dramatically with an increase in the number of images [17]. [PERSON]. [18] used the image method to establish a multipath model for a rectangular wireless signal in a coal mine, conducted simulations on the field strength at the receiving point, and simulated the transmission of ultrahigh-frequency (UHF) signals in the roadway. However, in complex roadway environments, the computational efficiency of imaging methods is poor. In the SBR method, the signal-receiving end is imagined as a very small circular area, the ray paths that reach the circular area are considered effective paths, and discrete ray trajectories are obtained based on the model. By introducing the height of the vector antenna, [PERSON]. [19] used the SBR method to calculate the additional loss caused by the shape of the tunnel, such as a curve. [PERSON]. [20; 21] utilize a hybrid algorithm composed of a recursive neural network (LSTM), an annealing algorithm, and a support vector machine (SVM) to establish a model for tunnel wireless signal loss and conduct field strength prediction. The results demonstrate the feasibility of SVM application in tunnels and its superiority in accuracy over traditional signal fading models. When support vector machines are used for model prediction, the prediction time is related to the number of support vectors. When the number of support vectors is large, the computational complexity is great. The hybrid ray-tracing model addresses the issue of a single model not simulating signal transmission characteristics well. Ref. [22] combined the ray-tracing model and the waveguide model, i.e., using the waveguide modeling method in the near-source region and the ray-tracing modeling method in the far-source region. This method improves the accuracy of the channel model but increases its complexity, and signal transmission in roadways is a continuously changing process; as a result, there is no obvious boundary condition for determining the near-source region or far-source region. To solve these problems, this paper proposes to use three-dimensional (3D) ray-tracing methods for studying the transmission characteristics of wireless signals in coal mine roadways. This study analyzes the effects of complex roadway environments (such as rough roadway walls) and lossy media (such as dust and fog droplets) on wireless signal attenuation and assesses the effects of parameters, such as transceiver antenna position and antenna gain, signal incidence angle, and the number of reflections, on the wireless signal field strength. This research will provide a theoretical foundation and practical guidance for the design and optimization of mine roadway communication systems. At the same time, it will also play a significant role in promoting research into the application of wireless signals in similar complex environments.