Challenges and Potential Approaches in Propagation Modeling of High Frequencies for 6G Networks

Future 6G networks, aiming for Tbps data rates and microsecond latency by 2030, rely on millimeter-wave and terahertz bands, introducing significant propagation challenges. This paper examines atmospheric and urban propagation effects that should be considered to avoid limiting 6G performance. Atmospheric phenomena (gaseous absorption, rain, clouds, scintillation, and more) are shown to cause severe signal loss in mmWave and THz bands, with W-band as a benchmark, based on our analysis. Additionally, current models like ITU-R P.618-13 and P.530-18, validated only up to 55 GHz and 40 GHz, respectively, are inadequate for these higher frequencies. Furthermore, these models lack coverage for a three-dimensional architecture, such as air-to-air links, and do not account for terminal dynamics in mobile networks. Beyond this, this contribution investigates urban propagation effects, where blockages, multipath, and penetration losses reduce effective communication range, as shown in our simulations, quantified through 3D ray-tracing at 77 and 94 GHz, to tens of meters in W-band, revealing the need for reliable propagation models. Proposed solutions include high-frequency measurement campaigns tailored to 6 G scenarios, augmented by commercial microwave links, enhanced ray-tracing with diffuse scattering models dominating at high frequencies, and LiDAR-driven digital twins for urban modeling. Machine learning, leveraging graph neural networks, deep learning, and transfer learning, could transform channel modeling despite data scarcity in mmWave and THz bands, enhancing established techniques like adaptive modulation and coding, while enabling new approaches such as massive MIMO with optimized beamforming, and RIS with refined phase shifts, to meet ambitious 6 G targets.