Channel Estimation and Low-complexity Beamforming Design for Passive Intelligent Surface Assisted MISO Wireless Energy Transfer

By Deepak Mishra, Håkan Johansson. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019

531 citations recorded by the source corpus.

Usage of passive intelligent surface (PIS) is emerging as a low-cost green alternative to massive antenna systems for realizing high energy beamforming (EB) gains. To maximize its realistic utility, we present a novel channel estimation (CE) protocol for PIS-assisted energy transfer (PET) from a multiantenna power beacon (PB) to a single-antenna energy harvesting (EH) user. Noting the practical limitations of PIS and EH user, all computations are carried out at PB having required active components and radio resources. Using these estimates, near-optimal analytical active and passive EB designs are respectively derived for PB and PIS, that enable efficient PET over a longer duration of coherence block. Nontrivial design insights on relative significance of array size at PIS and PB are also provided. Numerical results validating theoretical claims against the existing benchmarks demonstrate that with sufficient passive elements at PIS, we can achieve desired EB gain with reduced active array size at PB.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/7738d252065fbc5f819e14f5eb170b55d78e7ce7

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Citations in the corpus

Reconfigurable Intelligent Surface Assisted UAV Communication: Joint Trajectory Design and Passive Beamforming (2019, methodology): “In this letter, we assume that the channel state information (CSI) can be obtained based on existing channel estimation techniques for RIS assisted channels, such as in [12], [13].”
An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces Based on a Minimum Variance Unbiased Estimator (2019, methodology): “We consider a model with all elements passive as in [3, 8, 9].”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “In [101], the authors introduce a channel estimation protocol”
Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis (2019, background): “Recently, several works have proposed various strategies to efficiently estimate the channels for IRS-assisted communication [1], [23]–[29].”
An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, unknown): “On-off Scheme [49], [50]: The simplest scheme is the onoff scheme adopted in [49], [50].”
Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface With Discrete Phase Shifts (2019, background): “, physical layer security [17], [20]–[22], simultaneous wireless information and power transfer (SWIPT) [23]–[26], and non-orthogonal multiple access [27], [28].”
Wireless Communications Through Reconfigurable Intelligent Surfaces (2019, methodology): “The authors of [81] proposed a new channel estimation protocol for an RIS-assisted single-user MISO system with energy harvesting.”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, background): “Existing approaches for the IRS’s channel estimation generally assume that only one scattering element is active each time, while all the other elements are inactive, e.g., [30], [180].”
Intelligent Reflecting Surface Meets OFDM: Protocol Design and Rate Maximization (2019, unknown): “4It is worth pointing out that during the preparation of this work, we became aware of a related work [18] on the channel estimation for IRS-enhanced systems, which independently proposed a sequential channel estimation method under the frequency-flat channel that requires M + 1 pilot symbols in the”
Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, methodology): “In the literature, there are some recent works that studied the channel estimation problem for IRS-aided wireless systems [14], [15], [21], [25], [26].”
A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications (2021, methodology): “IRS channel estimation • Near-orthogonal IRS training reflection design subject to the discrete phase-shift constraint in narrowband system [107], [108] • Cascaded channel estimation accounting for discrete phase-shift model in broadband system [113] • ON/OFF training reflection pattern [34], [55]”
Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces (2020, methodology): “Nevertheless, solutions in [7], [8] and [9] mainly consider a frequency-flat communication system by assuming narrow-band channels.”
Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface: Discrete Phase Shift and Progressive Refinement (2019, background): “Instead, only the cascaded user-IRS-AP channels can be estimated at the AP (or user) based on the pilot symbols sent by the user (or AP), by adjusting IRS reflection coefficients over time [28]–[30].”
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”
Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design (2020, methodology): “A close to optimal design for v that maximizes the received signal power at the user is proposed in [23] as v = exp( j ∠ ( ˆ H H 0 ,k ˆ h d,k )) .”
Reconfigurable Intelligent Surfaces for Wireless Communications: Overview of Hardware Designs, Channel Models, and Estimation Techniques (2022, methodology): “Actually, the ON/OFF method [133], [136], [159] generally yields sub-optimal CE results.”
Two-Timescale Channel Estimation for Reconfigurable Intelligent Surface Aided Wireless Communications (2019, methodology): “, dozens to hundreds) of RIS elements and dozens of UEs, while the pilot overhead of typical cascaded channel methods is the product of the number of RIS elements and the number of UEs [4], [5].”
Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization (2019, unknown): “Prior works adopting this method for IRS channel estimation have assumed a simple element-by-element ON/OFF-based reflection pattern [5]–[7], which, however, has two main drawbacks.”
Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT Under QoS Constraints (2019, background): “While the above works focus on exploiting IRS for enhancing the wireless communication or information transmission performance, the high beamforming gain achieved by passive IRS is also appealing for WPT [6], [26].”