6D Channel Knowledge Map Construction via Bidirectional Wireless Gaussian Splatting

TL;DR

This paper introduces BiWGS, a 6D channel knowledge map framework that models wireless channels across dynamic 3D transmitter and receiver positions using Gaussian ellipsoids, outperforming traditional methods.

Contribution

The paper presents a novel 6D CKM framework called bidirectional wireless Gaussian splatting (BiWGS) that models wireless channels in dynamic environments, expanding beyond fixed base station assumptions.

Findings

BiWGS outperforms classic MLP in 6D channel power gain mapping.

BiWGS achieves accuracy comparable to state-of-the-art 3D CKM methods.

BiWGS effectively models wireless transmission characteristics in dynamic scenarios.

Abstract

This paper investigates the construction of channel knowledge map (CKM) from sparse channel measurements. Dif ferent from conventional two-/three-dimensional (2D/3D) CKM approaches assuming fixed base station configurations, we present a six-dimensional (6D) CKM framework named bidirectional wireless Gaussian splatting (BiWGS), which is capable of mod eling wireless channels across dynamic transmitter (Tx) and receiver (Rx) positions in 3D space. BiWGS uses Gaussian el lipsoids to represent virtual scatterer clusters and environmental obstacles in the wireless environment. By properly learning the bidirectional scattering patterns and complex attenuation profiles based on channel measurements, these ellipsoids inherently cap ture the electromagnetic transmission characteristics of wireless environments, thereby accurately modeling signal transmission under varying transceiver configurations. Experiment results show that BiWGS significantly outperforms classic multi-layer perception (MLP) for the construction of 6D channel power gain map with varying Tx-Rx positions, and achieves spatial spectrum prediction accuracy comparable to the state-of-the art wireless radiation field Gaussian splatting (WRF-GS) for 3D CKM construction. This validates the capability of the proposed BiWGS in accomplishing dimensional expansion of 6D CKM construction, without compromising fidelity.