Intelligent Reflecting Surface Assisted Wireless Communication: Modeling and Channel Estimation

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.

References in corpus (3)

• Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems
• Beyond Massive-MIMO: The Potential of Data-Transmission with Large Intelligent Surfaces
• A Tutorial on the Optimization of Amplify-and-Forward MIMO Relay Systems

Cited by in corpus (23)

• A Survey of Intelligent Reflecting Surfaces (IRSs): Towards 6G Wireless Communication Networks
• Intelligent Reflecting Surface Aided Wireless Communications: A Tutorial
• IRS-Aided SWIPT: Joint Waveform, Active and Passive Beamforming Design Under Nonlinear Harvester Model
• Deep-Learning-Aided Detection for Reconfigurable Intelligent Surfaces
• Reconfigurable Intelligent Surface-Aided Wireless Power Transfer Systems: Analysis and Implementation
• Intelligent Reflecting Surface Meets Mobile Edge Computing: Enhancing Wireless Communications for Computation Offloading
• Multiple Antenna Selection and Successive Signal Detection for SM-based IRS-aided Communication
• Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks
• Reconfigurable Intelligent Surface Empowered Downlink Non-Orthogonal Multiple Access
• Millimeter Wave Communications with an Intelligent Reflector: Performance Optimization and Distributional Reinforcement Learning
• Model-Free Optimization for Reconfigurable Intelligent Surface with Statistical CSI
• Physical Layer Security Enhancement With Reconfigurable Intelligent Surface-Aided Networks
• Channel Feedback for Reconfigurable Intelligent Surface Assisted Wireless Communications
• Channel Estimation for Practical IRS-Assisted OFDM Systems
• Multi-User Opportunistic Beamforming using Reconfigurable Surfaces
• Channel Estimation and Power Scaling Law of Large Reflecting Surface with Non-Ideal Hardware
• A Robust Deep Learning-Based Beamforming Design for RIS-assisted Multiuser MISO Communications with Practical Constraints
• Energy Efficiency Analysis of Intelligent Reflecting Surface System with Hardware Impairments
• Joint Beamforming and Reconfigurable Intelligent Surface Design for Two-Way Relay Networks
• Cascaded Channel Estimation for IRS-assisted Mmwave Multi-antenna with Quantized Beamforming
• Performance Analysis under IRS-User Association for Distributed IRSs Assisted MISO Systems
• Angle-Domain Intelligent Reflecting Surface Systems: Design and Analysis
• A 3D Non-Stationary Channel Model for 6G Wireless Systems Employing Intelligent Reflecting Surfaces with Practical Phase Shifts