A Computationally Efficient Reciprocal Effective Roughness Model for Diffuse Scattering

TL;DR

This paper presents a new reciprocal diffuse scattering model that maintains physical accuracy while significantly reducing computational costs for ray-tracing in environments with complex surface roughness.

Contribution

A novel reciprocal diffuse scattering model that preserves the effective roughness structure and reduces computational complexity by an order of magnitude.

Findings

Validated across eight materials with no accuracy loss.

Achieves an order-of-magnitude reduction in computational cost.

Maintains physical consistency in diffuse scattering modeling.

Abstract

Ray-tracing (RT) has become central to site-specific electromagnetic propagation modeling in dynamic complex environments. Yet its computational burden grows sharply as high-fidelity digital twins of these environments scale to millions of facets whose material parameters must be continuously updated as the environment changes. The challenge is amplified at mmWave and sub-THz frequencies, where surface roughness becomes comparable to the wavelength and so diffuse scattering can account for up to 40% of the received power, making accurate yet tractable models essential. The popular Effective Roughness (ER) approach offers physical consistency but become increasingly costly when highly directive lobes are required or when parameters must be iteratively tuned. This communication introduces a directive, reciprocal diffuse scattering model that preserves the structure of the ER while enabling an order-of-magnitude reduction in computational cost. Validation across eight materials shows no loss in accuracy - and a slight improvement - demonstrating a scalable and physically meaningful solution for RT in scenarios where diffuse scattering is non-negligible.