Modal-Based Multi-Scatterer Channel Model for Localized Radiomap Extrapolation

2026-05-04

AI Summary

This work addresses the limited accuracy of conventional radiomap modeling at high frequencies, which stems from neglecting fine-scale scatterers. The authors propose a multi-scatterer channel model based on spherical wave modal expansion that unifies the characterization of source radiation, single scattering, and multiple-scattering coupling effects through modal superposition. By reformulating the forward model as an inverse optimization problem, the approach jointly estimates scatterer responses and transmitter location. Notably, it integrates multi-scattering interactions with low-order modal approximation within a physically interpretable framework—a first in the field—and enables high-fidelity radiomap reconstruction and extrapolation from sparse measurements. Simulations demonstrate that the proposed model significantly outperforms existing methods in both spatial and beam domains, particularly in dense scattering environments.

Abstract

A radiomap, representing the spatial distribution of wireless signal strength within a specific region, is fundamentally determined by the local propagation channel and finds extensive applications in network planning and optimization. The channel model is inherently linked to electromagnetic (EM) wave propagation, and the advent of high-frequency communications presents a new picture - microscopic (and thus negligible) scatterers in lower frequency bands become mesoscopic, rendering non-negligible EM effects. In this paper, we establish a channel model for multiple scatterers based on a spherical wave mode expansion. The source radiation, single scatterer response and multiple scatterer interactions are formed in the superposition of spherical-wave modes, capturing the multi-path effect in wave perspective. Iterative methods are used to handle the massive coupling between scatterers. This forward model is converted to an inverse optimization problem, where the scattering responses and the scatterer locations are jointly learned from sparse field measurements. A simplified approximate model is then introduced, employing fewer and simpler low-order modes while still allowing a larger number of more densely placed scatterers. Simulation results demonstrate that the proposed model accurately reconstructs and extrapolates radiomaps in both the spatial domain and the beam domain. Overall, the proposed framework offers a physically interpretable approach to localized propagation modeling.

Problem

• radiomap extrapolation
• multi-scatterer channel modeling
• spherical wave modes
• high-frequency propagation
• sparse field measurements

Innovation

• spherical-wave mode expansion
• multi-scatterer channel modeling
• radiomap extrapolation
• inverse optimization
• electromagnetic wave propagation