Intelligent Reflecting Surface Assisted Wireless Communication: Modeling and Channel Estimation

TL;DR

This paper explores the use of Intelligent Reflecting Surfaces (IRS) to enhance wireless communication by reconfiguring propagation environments, proposing a channel estimation protocol, and evaluating its performance at 2.5 GHz.

Contribution

It introduces an IRS-assisted multi-user MISO communication model and a novel MMSE-based channel estimation protocol for such systems.

Findings

Proposed an efficient MMSE-based channel estimation method.

Demonstrated performance improvements at 2.5 GHz.

Highlighted IRS's potential for sustainable wireless networks.

Abstract

The recently completed 5G new radio standard is a result of several cutting-edge technologies, including massive multiple-input multiple-output (MIMO), millimeter (mm)-Wave communication and network densification. However, these technologies face two main practical limitations 1) the lack of control over the wireless channel, and 2) the high power consumption of the wireless interface. To address the need for green and sustainable future cellular networks, the concept of reconfiguring wireless propagation environments using Intelligent Reflecting Surfaces (IRS)s has emerged. An IRS comprises of a large number of low-cost passive antennas that can smartly reflect the impinging electromagnetic waves for performance enhancement. This paper looks at the evolution of the reflective radio concept towards IRSs, outlines the IRS-assisted multi-user multiple-input single-output (MISO) communication model and discusses how it differentiates from the conventional multi-antenna communication models. We propose a minimum mean squared error (MMSE) based channel estimation protocol for the design and analysis of IRS-assisted systems. Performance evaluation results at 2.5 GHz operating frequency are provided to illustrate the efficiency of the proposed system.