Spectrum-Aware IRS Configuration Techniques for Ultrawideband Signals

TL;DR

The paper tackles beam-split dispersion in ultrawideband IRS-aided links by proposing spectrum-aware IRS configuration schemes that leverage, rather than erase, the beam-split effect.It develops a flexible wideband model, derives an upper bound on the channel transfer function, and compares baseline (narrowband and ED) with two localized optimization methods (SLO and ALO) across varied geometries and spectra.Simulation results show that SLO and ALO outperform traditional narrowband approaches and are competitive with ED, particularly for small to moderate IRSs and non-flat or multi-band spectra, while ED gains prominence only with larger IRSs.Overall, the work provides a low-to-moderate complexity, practically implementable approach to improve spectrum integrity and received power in wideband IRS-aided near- and far-field THz/UWB communications.

Abstract

Intelligent reflecting surfaces (IRS) have become the subject of many current research efforts, as the ongoing wireless spectrum crunch has made the need to open higher frequency bands a priority. IRS are one of the alternatives proposed to overcome the problem of line-of-sight blocking in very high frequency wireless scenarios. The current state-of-the-art shows the difficulty of implementing practical IRS designs able to redirect large signal bandwidths, prone to the so-called beam split (BS) dispersion effect. In this work, we propose two highly efficient configuration techniques, adapted to ultrawideband downlink scenarios, based on localized optimization over the IRS surface. Such techniques exploit the BS effect while taking into account for the shape of the transmitted signal spectrum. Simulations considering different geometrical setups and different signal spectra show how the proposed techniques are able to guarantee an increased signal power at the receiver with respect to classical narrowband-based solutions or techniques that perform a global optimization over the entire IRS surface.

Figures (14)

• Figure 1: Network geometry.
• Figure 2: Normalized received power spectrum plotted versus the normalized frequency $f/f_0$, for a single-band flat transmitted spectrum, $B = 0.4 f_0$, and $L_x=0.2$ m.
• Figure 3: Normalized received power spectrum plotted versus the normalized frequency $f/f_0$, for a single-band flat transmitted spectrum, $B = 0.4 f_0$, and $L_x=1.0$ m.
• Figure 4: Normalized average received power spectral density plotted versus the relative bandwidth $B/f_0$, for $L_x=0.2$ and a signal characterized by a single-band flat spectrum.
• Figure 5: Normalized average received power spectral density plotted versus the relative bandwidth $B/f_0$, for $L_x=1.0$ and a signal characterized by a single-band flat spectrum.