Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization

By Beixiong Zheng, Rui Zhang. IEEE Wireless Communications Letters, 2019

697 citations recorded by the source corpus.

In the intelligent reflecting surface (IRS)-enhanced wireless communication system, channel state information (CSI) is of paramount importance for achieving the passive beamforming gain of IRS, which, however, is a practically challenging task due to its massive number of passive elements without transmitting/receiving capabilities. In this letter, we propose a practical transmission protocol to execute channel estimation and reflection optimization successively for an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system. Under the unit-modulus constraint, a novel reflection pattern at the IRS is designed to aid the channel estimation at the access point (AP) based on the received pilot signals from the user, for which the channel estimation error is derived in closed-form. With the estimated CSI, the reflection coefficients are then optimized by a low-complexity algorithm based on the resolved strongest signal path in the time domain. Simulation results corroborate the effectiveness of the proposed channel estimation and reflection optimization methods.

Subfields: Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/58b7eccc4c20e13baecc0b4aa6b57f95f76f5324

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

In Ocean Engineering

Citations in the corpus

Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computing (2019, background): “2) Intelligent Reflecting Surface Aided Wireless Networks: In order to explore the benefits of IRSs in wireless communications, extensive research efforts have been invested into their ergodic capacity analysis [19], channel estimation [20], and practical reflection phase shift modeling [21], as wel”
RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials (2021, methodology): “If a continuous phase-shift optimization is possible, then the optimal phaseshift vector is given as [11], [30]”
Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design (2020, methodology): “The idea was extended in [25] to an OFDM system and in [26] to an IRS-assisted system with discrete phase shifts while focusing on a single-user scenario.”
Radio Localization and Mapping With Reconfigurable Intelligent Surfaces: Challenges, Opportunities, and Research Directions (2019, background): “DECEMBER 2020 | IEEE VEHICULAR TECHNOLOGY MAGAZINE ||| 59 should also account for the presence of the RIS and the availability of the LOS path [5], [14].”
Intelligent Reflecting Surface Assisted Secrecy Communication: Is Artificial Noise Helpful or Not? (2019, methodology): “To characterize the performance limit of the considered IRS-assisted secrecy communication system, we assume that the channel state information (CSI) of all channels involved is perfectly known at Alice and Rose for their joint design of transmit/reflect beamforming and jamming, based on the various”
Intelligent Reflecting Surface: Practical Phase Shift Model and Beamforming Optimization (2019, methodology): “, the channel estimation technique proposed in [9].”
An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces Based on a Minimum Variance Unbiased Estimator (2019, background): “Note that a DFT based training has been independently proposed in [12] but without optimality analysis.”
Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface: Discrete Phase Shift and Progressive Refinement (2019, methodology): “To reduce the channel training overhead, the IRS elements can be divided into groups where only the effective cascaded channel for all elements in each group needs to be estimated [14], [29].”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, background): “The authors in [193] and [194] assume that all reflecting elements are switched on.”
Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT Under QoS Constraints (2019, background): “In contrast, for the second approach without receive RF chains at the IRS, the IRS reflection patterns can be designed together with the uplink pilots to estimate the concatenated AP-IRS-user channels [18], [19].”
Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface With Discrete Phase Shifts (2019, background): “In contrast, for the second approach without receive RF chains at the IRS, the IRS reflection patterns can be designed together with the uplink pilots to estimate the concatenated AP-IRS-user channels [18], [36].”
Capacity Characterization for Intelligent Reflecting Surface Aided MIMO Communication (2019, background): “On the other hand, [10]–[13] proposed to estimate the transmitter-IRS-receiver concatenated channel based on the training signals sent by the transmitter/receiver as well as the channel reciprocity between the forward and reverse links, for both frequency-flat and frequency-selective fading channels”
Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces (2020, methodology): “Therefore, to fully exploit the full reflection of the IRS during the channel estimation phase, the authors in [10] applied the LS to jointly estimate the BS-UE and BS-IRS-UE channels in orthogonal frequency division multiplexing (OFDM) systems, however, they only consider all UEs and access points ”
Physics-Based Modeling and Scalable Optimization of Large Intelligent Reflecting Surfaces (2020, methodology): “[23], [44], [45] for channel estimation schemes for IRS-assisted systems.”
Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial (2020, methodology): “more channel coefficients are induced for both user-BS direct channels as well as user-IRS-BS reflected channels due to the multi-path delay spread and the resultant convolution of timedomain impulse responses of user-IRS and IRS-BS multi-path channels, which makes the channel acquisition problem ev”
Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis (2019, methodology): “On the other hand, [25], [26] proposed a novel discrete Fourier transform (DFT) based channel estimation strategy, in which all the IRS elements are on at each time slot, and their reflection coefficients are determined by the DFT matrix.”
Double-IRS Assisted Multi-User MIMO: Cooperative Passive Beamforming Design (2020, background): “Note that each of these IRS subsurfaces in practice constitutes an arbitrary number of adjacent reflecting elements that induce an identical (common) phase shift to the incident signal, thus enjoying a high aperture gain but with significantly reduced cost for channel estimation and reflection optim”
Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends (2022, background): “may result in imperfect CSIT due to limited channel training resources [194], [195].”
Compressed Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave Systems (2020, background): “Implementing the ON/OFF switching, however, is costly as this requires separate amplitude control of each IRS element [11].”