Fourier Transform-Based Wavenumber Domain 3D Imaging in RIS-Aided Communication Systems

Radio imaging is rapidly gaining prominence in the design of future communication systems, with the potential to utilize reconfigurable intelligent surfaces (RISs) as imaging apertures. Although the sparsity of targets in three-dimensional (3D) space has led most research to adopt compressed sensing (CS)-based imaging algorithms, these often require substantial computational and memory burdens. Drawing inspiration from conventional Fourier transform (FT)-based imaging methods, our research seeks to accelerate radio imaging in RIS-aided communication systems. To begin, we introduce a two-stage wavenumber domain 3D imaging technique: first, we modify RIS phase shifts to recover the equivalent channel response from the user equipment to the RIS array, subsequently employing traditional FT-based wavenumber domain methods to produce target images. We also determine the diffraction resolution limits of the system through k-space analysis, taking into account factors including system bandwidth, transmission direction, operating frequency, and the angle subtended by the RIS. Addressing the challenge of limited pilots in communication systems, we unveil an innovative algorithm that merges the strengths of both FT- and CS-based techniques by substituting the expansive sensing matrix with FT-based operators. Our simulation outcomes confirm that our proposed FT-based methods achieve high-quality images while demanding few time, memory, and communication resources.

I. Introduction

Environment sensing is an emerging function in future wireless communication systems [1], [2], [3]. Among the sensing modalities, radio imaging stands out, illustrating the shapes and scattering properties of the targets in the region of interest (ROI). The radio-based imaging technique is unaffected by light conditions, protects human privacy [4], [5], and supports applications like monitoring, augmented reality, and environmental reconstruction [6], [7], [8]. While synthetic aperture radar (SAR) imaging has been widely studied as a type of radio imaging [9], [10], [11], [12], its techniques are now being adapted to integrated communication and imaging systems [13], [14]. However, communication antenna arrays are typically undersized for high-resolution imaging. Recent literature use the antennas of distributed user equipments (UEs) [13], but anisotropic scattering can introduce system modeling errors [14], [15]. Recently, reconfigurable intelligent surfaces (RISs) have revolutionized future communications by intelligently customizing the radio propagation environments [16], [17]. The RIS arrays typically possess large apertures with numerous uniformly placed tunable elements, which are beneficial for high imaging resolutions and potentially support non-line-of-sight (NLOS) imaging [18]. Moreover, RISs, free of active components, are promising for cost-effective and energy-efficient radio imaging [19].