IRS-Enabled Beam-Space Channel

TL;DR

This paper introduces a new IRS-enabled beam-space channel model that considers the entire channel as a unified entity, enabling improved beamforming strategies and addressing challenges in massive MIMO systems.

Contribution

The paper develops a novel channel model considering the entire IRS-assisted channel as a whole and proposes a segmentation and activation scheme for optimized beamforming.

Findings

Fewer transmitting antennas can outperform more in certain IRS configurations.

The model addresses stationarity and spherical wavefront issues in massive MIMO.

IRS can be effectively modeled as a scattering cluster in beam-space.

Abstract

The intelligent reflecting surface (IRS) is emphasized as a controlled scattering cluster. To this end, scatterers and traveling paths of multipath components are classified to build a new channel model. Unlike the conventional modeling, where the channels between system units are modeled independently, the new model considers the channel as a whole and decomposes it based on the traveling paths. The model shows clearly how IRS, in the beam-space context, converts the channel from a problem into a design element. After investigating IRS as a scattering cluster, based on a proposed segmentation scheme, the beamforming problem is considered with a focus on first-order reflections. Passive beamforming at IRS is shown to have two tiers; at the scatterer and antenna levels. A segment-activation scheme is proposed to maximize the received signal power, where the number of transmitting antenna elements to be used is given as a function of IRS positioning and beamforming at the receiver. The results show that while using more transmitting antenna elements to get narrower beams is possible, using fewer elements can give better performance, especially for larger IRS at close distances. The developed model also proves useful in addressing emerging issues in massive MIMO communication, namely, stationarity and spherical wavefronts.