Search Results for author:
Found 14 papers, 1 papers with code
Tensor-based modeling/estimation of static channels in IRS-assisted MIMO systems
This paper proposes a tensor-based parametric modeling and estimation framework in multiple-input multiple-output (MIMO) systems assisted by intelligent reflecting surfaces (IRSs).
Tensor-Based Channel Estimation and Data-Aided Tracking in IRS-Assisted MIMO Systems
This letter proposes a model for symbol detection in the uplink of IRS-assisted networks in the presence of channel aging.
Two-Dimensional Channel Parameter Estimation for IRS-Assisted Networks
The tradeoffs between performance and complexity offered by the proposed methods are discussed and numerically assessed.
Tensor-Based High-Resolution Channel Estimation for RIS-Assisted Communications
This letter proposes a high-resolution channel estimation for reconfigurable intelligent surface (RIS)-assisted communication networks.
Reducing the Control Overhead of Intelligent Reconfigurable Surfaces Via a Tensor-Based Low-Rank Factorization Approach
We show that the proposed low-rank models drastically reduce the required feedback requirements associated with the BS-IRS control links.
Tensor-Based Channel Estimation for RIS-Assisted Networks Operating Under Imperfections
Furthermore, the identifiability and computational complexity of the proposed algorithm are analyzed, and we study the effect of different imperfections on the channel estimation quality.
IRS Phase-Shift Feedback Overhead-Aware Model Based on Rank-One Tensor Approximation
In this paper, we propose a rank-one tensor modeling approach that yields a compact representation of the optimum IRS phase-shift vector for reducing the feedback overhead.
Double-RIS Versus Single-RIS Aided Systems: Tensor-Based MIMO Channel Estimation and Design Perspectives
Reconfigurable intelligent surfaces (RISs) have been proposed recently as new technology to tune the wireless propagation channels in real-time.
Tensor-Based Channel Estimation and Reflection Design for RIS-Aided Millimeter-Wave MIMO Communication Systems
Utilizing such a structure, a tensor-based RIS channel estimation method (termed TenRICE) is proposed, wherein the tensor factor matrices are estimated using an alternating least squares method.
Low-Complexity Massive MIMO Tensor Precoding
We present a novel and low-complexity massive multiple-input multiple-output (MIMO) precoding strategy based on novel findings concerning the subspace separability of Rician fading channels.
Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach
In this paper, we address the receiver design for an IRS-assisted multiple-input multiple-output (MIMO) communication system via a tensor modeling approach aiming at the channel estimation problem using supervised (pilot-assisted) methods.
Channel Parameter Estimation for Millimeter-Wave Cellular Systems with Hybrid Beamforming
We propose a novel two-stage algorithm for channel parameters estimation.
PARAFAC-Based Channel Estimation for Intelligent Reflective Surface Assisted MIMO System
Intelligent reflective surface (IRS) is an emergent technology for future wireless communications.
Signal Processing
Rank-one Detector for Kronecker-Structured Constant Modulus Constellations
To achieve a reliable communication with short data blocks, we propose a novel decoding strategy for Kronecker-structured constant modulus signals that provides low bit error ratios (BERs) especially in the low energy per bit to noise power spectral density ratio $(E_b/N_0)$.
