Supercomputing-enabled first-principles analysis of wireless channels in real-world environments

Wireless communications are expected to take place in increasingly complicated scenarios, such as dense urban, forest, tunnel and other significant cluttered environments. A key challenge emerging is to understand the physics and characteristics of wireless channels in complex environments, which are critical for the analysis, design, and application of future mobile and wireless communication systems. The objective of this work is to investigate high-resolution, high-performance computational algorithms for extreme-scale channel modehng in real-world environments. The system-level large scene analysis is enabled by the novel, ultra-parallel algorithms on the emerging exascale high-performance computing (HPC) platforms. The results lead to much greater channel model resolution than existing deterministic channel modeling technologies. All relevant propagation mechanisms are accounted for in first-principles. Such a modeling framework will be critical to gaining fundamental physics of wireless propagation channels in real-world scenarios.