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Found 18 papers, 0 papers with code
Joint Sparse Estimation with Cardinality Constraint via Mixed-Integer Semidefinite Programming
To further reduce the computation time in such scenarios, a relaxation-based approach can be employed to obtain an approximate solution of the MISDP reformulation, at the expense of a reduced estimation performance.
SALSA: A Sequential Alternating Least Squares Approximation Method For MIMO Channel Estimation
A novel channel estimation method called Sequential Alternating Least Squares Approximation (SALSA) is proposed by exploiting a hidden tensor structure in the uplink measurement matrix.
The Perfect Match: RIS-enabled MIMO Channel Estimation Using Tensor Decomposition
To enable the full potential of RISs, we propose to use tensor-decomposition-based CE, which facilitates smart configuration of the RIS by providing the required channel components.
Combining AI/ML and PHY Layer Rule Based Inference -- Some First Results
In 3GPP New Radio (NR) Release 18 we see the first study item starting in May 2022, which will evaluate the potential of AI/ML methods for Radio Access Network (RAN) 1, i. e., for mobile radio PHY and MAC layer applications.
Transfer Learning Capabilities of Untrained Neural Networks for MIMO CSI Recreation
Machine learning (ML) applications for wireless communications have gained momentum on the standardization discussions for 5G advanced and beyond.
Machine Learning for CSI Recreation Based on Prior Knowledge
Based on the prior-CSIs, their locations and the location of the desired channel, the cGAN is trained to output the channel expected at the desired location.
Compressed Sensing Constant Modulus Constrained Projection Matrix Design and High-Resolution DoA Estimation Methods
This paper proposes a compressed sensing-based high-resolution direction-of-arrival estimation method called gradient orthogonal matching pursuit (GOMP).
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.
Machine Learning for Model Order Selection in MIMO OFDM Systems
A variety of wireless channel estimation methods, e. g., MUSIC and ESPRIT, rely on prior knowledge of the model order.
Recovery under Side Constraints
Finally, we address the measurement system design for linear and nonlinear measurements of sparse signals.
Fully Digital and Hybrid Beamforming Design For Millimeter-Wave MIMO-OFDM Two-Way Relaying Systems
In this work, we consider the design of hybrid analog-digital (HAD) multi-carrier MIMO-OFDM two-way relaying systems, where the relay station is equipped with a HAD amplify-and-forward architecture and every mobile station is equipped with a fully-digital beamforming architecture.
Machine Learning Prediction of Time-Varying Rayleigh Channels
Channel state information (CSI) rapidly becomes outdated in high mobility scenarios, degrading the performance of wireless communication systems.
Two-step Machine Learning Approach for Channel Estimation with Mixed Resolution RF Chains
Massive MIMO is one of the main features of 5G mobile radio systems.
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.
The Extended "Sequentially Drilled" Joint Congruence Transformation and its Application in Gaussian Independent Vector Analysis
In this paper we extend our results to the IVA problem, showing how the ML solution for the Gaussian model (with arbitrary covariance and cross-covariance matrices) takes the form of an extended SeDJoCo problem.
Performance Analysis of the Gaussian Quasi-Maximum Likelihood Approach for Independent Vector Analysis
As an immediate consequence of this result, we provide an asymptotically attainable lower bound on the resulting ISRs.
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 $(E_b/N_0)$.
