Three-Dimensional Radio Localization: A Channel Charting-Based Approach

TL;DR

This paper extends channel charting to three-dimensional indoor environments, proposing new methods for multistory and augmented localization using simulated ray tracing data and novel feature extraction techniques.

Contribution

It introduces multistory channel charting and augmented channel charting for 3D environments, along with a new feature engineering method for beamspace channel data.

Findings

Effective 3D localization demonstrated in simulated environments.

Multistory approach improves floor classification accuracy.

Novel feature extraction enhances channel charting performance.

Abstract

Channel charting creates a low-dimensional representation of the radio environment in a self-supervised manner using manifold learning. Preserving relative spatial distances in the latent space, channel charting is well suited to support user localization. While prior work on channel charting has mainly focused on two-dimensional scenarios, real-world environments are inherently three-dimensional. In this work, we investigate two distinct three-dimensional indoor localization scenarios using simulated, but realistic ray tracing-based datasets: a factory hall with a three-dimensional spatial distribution of datapoints, and a multistory building where each floor exhibits a two-dimensional datapoint distribution. For the first scenario, we apply the concept of augmented channel charting, which combines classical localization and channel charting, to a three-dimensional setting. For the second scenario, we introduce multistory channel charting, a two-stage approach consisting of floor classification via clustering followed by the training of a dedicated expert neural network for channel charting on each individual floor, thereby enhancing the channel charting performance. In addition, we propose a novel feature engineering method designed to extract sparse features from the beamspace channel state information that are suitable for localization.