Realizing RF Wavefront Copying with RIS for Future Extended Reality Applications

TL;DR

This paper proposes a novel XR-RF system that combines RF imaging and programmable wireless environments using RIS to replicate RF wavefronts for extended reality applications, introducing a new configuration algorithm and modeling replication imprecision.

Contribution

It introduces a new RIS-based PWE configuration algorithm for wavefront copying in XR-RF and models the inherent imprecision using gamma distribution based on simulations.

Findings

Wavefront copying enables spatially flexible XR experiences.

Imprecision in waveform replication can be effectively modeled statistically.

Simulation results validate the proposed gamma distribution model.

Abstract

Lately a new approach to Extended Reality (XR), denoted as XR-RF, has been proposed which is realized by combining Radio Frequency (RF) Imaging and programmable wireless environments (PWEs). RF Imaging is a technique that aims to detect geometric and material features of an object through RF waves. On the other hand, the PWE focuses on the the conversion of the wireless RF propagation in a controllable, by software, entity through the utilization of Reconfigurable Intelligent Surfaces (RISs), which can have a controllable interaction with impinging RF waves. In that sense, this dynamic synergy leverages the potential of RF Imaging to detect the structure of an object through RF wavefronts and the PWE's ability to selectively replicate those RF wavefronts from one spatial location to wherever an XR-RF mobile user is presently located. Then the captured wavefront, through appropriate hardware, is mapped to the visual representation of the object through machine learning models. As a key aspect of the XR-RF's system workflow is the wavefront copying mechanism, this work introduces a new PWE configuration algorithm for XR-RF. Moreover, it is shown that the waveform replication process inevitably yields imprecision in the replication process. After statistical analysis, based on simulation results, it is shown that this imprecision can be effectively modeled by the gamma distribution.