## 1 Introduction  
With the advent of 5G new radio (NR) systems, operators promise to deliver radically higher user data rates at the access interface, which will enable new applications such as holographic communications, augmented/virtual reality (AR/VR), and high-resolution streaming [1]. At the same time, the research community is already discussing 6G systems, which will further enhance system throughput and diversify the service offerings [2, 3]. The fulfillment of the above-named promises is conditioned on the use of millimeter wave (mmWave) and terahertz (THz) frequency bands, both characterized by extremely short wavelengths. Due to the limitation of the effective antenna apertures, such systems must utilize large-scale phased antenna arrays operating in the beamforming regime to improve the coverage area [4; 5; 6; 7]. Precise knowledge of the propagation conditions at mmWave/THz frequencies is required at many stages of the system's design [8]. At the network planning stage, optimal locations of base stations (BS) maximizing the coverage area need to be determined [9]. Further, utilizing the beamforming regime of antenna arrays, one needs to develop an efficient beam tracking mechanism [10]. However, the use of such arrays as well as complex propagation effects such as reflection, diffraction, and scattering leads requires advanced channel models to predict channel conditions. Ray tracing is conventionally utilized to develop accurate propagation models. By using either image or ray-launching methods, they allow precise information to be obtained about the received signal strength at any given point by taking into account the geometry of the propagation environment and surrounding materials. However, ray tracing is an inherently resource-consuming procedure, even at lower frequencies, and the use of mmWave/THz bands in 5G/6G cellular systems requires much detailed resolution because the channel state parameters may change at distances comparable to the wavelength. Thus, obtaining detailed propagation maps is an extremely time-consuming procedure. In light of the aforementioned limitations, several studies have suggested different speed-up techniques for ray-tracing simulations; see Section 2 for a detailed review. However, all those either explicitly or implicitly assume that a correlation between channel state parameters is preserved across distances larger than the wavelength. While this may indeed be true for some propagation conditions, to the best of the authors' knowledge, there has been no detailed investigation into the effective correlation distances in typical propagation environments. Furthermore, some studies aiming to improve the beam tracking procedures for mmWave/THz systems, also implicitly assume this property. In this paper, we first utilize a ray-tracing tool to quantitatively evaluate the effective correlation distance between channel state parameters for typical outdoor propagation environments, different user mobility patterns, and line-of-sight (LoS) and non-LoS (nLoS) conditions. As metrics of interest, we utilize the angle of arrival/departure (AoA/ AoD) and path loss over the first few strongest paths. Having this information, we then propose a methodology to further enhance the considered distance between ray-tracing points. The methodology relies on representing the channel state parameters as frames similar to video frames and applying state-of-the-art techniques for interpolation and extrapolation.