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Found 12 papers, 3 papers with code
Ordinary Differential Equation-based MIMO Signal Detection
The required signal processing rate in future wireless communication systems exceeds the performance of the latest electronics-based processors.
Deep Unfolding-based Weighted Averaging for Federated Learning in Heterogeneous Environments
The proposed approach can be combined with various federated learning algorithms.
Precoder Design for Correlated Data Aggregation via Over-the-Air Computation in Sensor Networks
Over-the-air computation (AirComp) enables efficient wireless data aggregation in sensor networks by simultaneous processing of calculation and communication.
Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent
In the second half of the study, %we apply the theory of Chebyshev steps and Chebyshev-periodical successive over-relaxation (Chebyshev-PSOR) is proposed for accelerating linear/nonlinear fixed-point iterations.
Deep Unfolded Multicast Beamforming
Multicast beamforming is a promising technique for multicast communication.
Theoretical Interpretation of Learned Step Size in Deep-Unfolded Gradient Descent
In this paper, we provide a theoretical interpretation of the learned step size of deep-unfolded gradient descent (DUGD).
Trainable Projected Gradient Detector for Sparsely Spread Code Division Multiple Access
In this paper, we propose a novel trainable multiuser detector called sparse trainable projected gradient (STPG) detector, which is based on the notion of deep unfolding.
Complex Trainable ISTA for Linear and Nonlinear Inverse Problems
Complex-field signal recovery problems from noisy linear/nonlinear measurements appear in many areas of signal processing and wireless communications.
Trainable Projected Gradient Detector for Massive Overloaded MIMO Channels: Data-driven Tuning Approach
This paper presents a deep learning-aided iterative detection algorithm for massive overloaded multiple-input multiple-output (MIMO) systems where the number of transmit antennas $n$ is larger than that of receive antennas $m$.
Deep Learning-Aided Projected Gradient Detector for Massive Overloaded MIMO Channels
The paper presents a deep learning-aided iterative detection algorithm for massive overloaded MIMO systems.
Proceedings of Workshop AEW10: Concepts in Information Theory and Communications
The 10th Asia-Europe workshop in "Concepts in Information Theory and Communications" AEW10 was held in Boppard, Germany on June 21-23, 2017.
Information Theory Information Theory 68P30, 94A05
Sparse Signal Recovery for Binary Compressed Sensing by Majority Voting Neural Networks
We found a loss function suitable for sparse signal recovery, which includes a cross entropy-like term and an $L_1$ regularized term.
