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Wireless communication technology, including both radio and optical frequencies, has become a critical aspect of modern life. The accurate description and understanding of wireless signals are of paramount importance. Statistical channel modeling, which provides an accurate characterization of the propagation channel, is essential for the system design and performance analysis of different applications. Recently, various types of new wireless communication systems have emerged, such as device-to-device (D2D), millimeter-wave (mmWave) and terahertz, massive multiple-input multiple-output (MIMO), and unmanned aerial vehicle (UAV) systems. However, traditional and well-established fading models, such as Rayleigh, Rician, and Nakagami-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>, may not accurately model the random fluctuations of the received signal. There is a strong, credible body of evidence suggesting that the complex electromagnetic propagation phenomena encountered in new wireless systems should be taken into account by general and unifying physically based channel models.

IEEE Access Special Section Editorial: Advances in Statistical Channel Modeling for Future Wireless Communications Networks