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We develop a graph neural network (GNN) to compute, within a time budget of 1 to 2 milliseconds required by practical systems, the optimal linear precoder (OLP) maximizing the minimal downlink user data rate for a Cell-Free Massive MIMO…

Signal Processing · Electrical Eng. & Systems 2024-06-10 Benjamin Parlier , Lou Salaün , Hong Yang

Orthogonal/vector approximate message-passing (AMP) is a powerful message-passing (MP) algorithm for signal reconstruction in compressed sensing. This paper proves the convergence of Bayes-optimal orthogonal/vector AMP in the large system…

Information Theory · Computer Science 2022-04-26 Keigo Takeuchi

This paper addresses the reconstruction of sparse signals from spatially coupled, linear, and noisy measurements. A unified framework of rigorous state evolution is established for developing long-memory message-passing (LM-MP) in spatially…

Information Theory · Computer Science 2022-10-14 Keigo Takeuchi

In this paper, linear transceiver design for multi-hop amplify-and-forward (AF) multiple-input multiple-out (MIMO) relaying systems with Gaussian distributed channel estimation errors is investigated. Commonly used transceiver design…

Information Theory · Computer Science 2016-11-18 Chengwen Xing , Shaodan Ma , Zesong Fei , Yik-Chung Wu , H. Vincent Poor

A common goal in many research areas is to reconstruct an unknown signal x from noisy linear measurements. Approximate message passing (AMP) is a class of low-complexity algorithms that can be used for efficiently solving such…

Signal Processing · Electrical Eng. & Systems 2020-03-27 Hangjin Liu , Cynthia Rush , Dror Baron

Training-based transmission over Rayleigh block-fading multiple-input multiple-output (MIMO) channels is investigated. As a training method a combination of a pilot-assisted scheme and a biased signaling scheme is considered. The achievable…

Information Theory · Computer Science 2016-11-18 Keigo Takeuchi , Ralf R. Mueller , Mikko Vehkaperae , Toshiyuki Tanaka

We consider the problem of recovering random graph signals from nonlinear measurements. For this case, closed-form Bayesian estimators are usually intractable and even numerical evaluation of these estimators may be hard to compute for…

Signal Processing · Electrical Eng. & Systems 2022-06-23 Ariel Kroizer , Tirza Routtenberg , Yonina C. Eldar

Purpose: For quantitative susceptibility mapping (QSM), the lack of ground-truth in clinical settings makes it challenging to determine suitable parameters for the dipole inversion. We propose a probabilistic Bayesian approach for QSM with…

Image and Video Processing · Electrical Eng. & Systems 2023-06-01 Shuai Huang , James J. Lah , Jason W. Allen , Deqiang Qiu

We study a two-user state-dependent generalized multiple-access channel (GMAC) with correlated states. It is assumed that each encoder has \emph{noncausal} access to channel state information (CSI). We develop an achievable rate region by…

Information Theory · Computer Science 2014-09-09 Mohammad Javad Emadi , Majid Nasiri Khormuji , Mikael Skoglund , Mohammad Reza Aref

This paper provides comprehensive coding and outer bound for the half-duplex multiple access channel with generalized feedback (MAC-GF). Two users communicate with one destination over a discrete memoryless channel using time division. Each…

Information Theory · Computer Science 2011-08-02 Ahmad Abu Al Haija , Mai Vu

Low-complexity Bayes-optimal memory approximate message passing (MAMP) is an efficient signal estimation algorithm in compressed sensing and multicarrier modulation. However, achieving replica Bayes optimality with MAMP necessitates a…

Information Theory · Computer Science 2024-07-19 Lei Liu , Ming Wang , Shufeng Li , Yuhao Chi , Ning Wei , ZhaoYang Zhang

Sparse superposition codes, or sparse regression codes, constitute a new class of codes which was first introduced for communication over the additive white Gaussian noise (AWGN) channel. It has been shown that such codes are…

Information Theory · Computer Science 2018-11-12 Jean Barbier , Mohamad Dia , Nicolas Macris

In recent studies, neural message passing has proved to be an effective way to design graph neural networks (GNNs), which have achieved state-of-the-art performance in many graph-based tasks. However, current neural-message passing…

Machine Learning · Computer Science 2021-04-21 Wentao Zhang , Yu Shen , Zheyu Lin , Yang Li , Xiaosen Li , Wen Ouyang , Yangyu Tao , Zhi Yang , Bin Cui

In phase retrieval, the goal is to recover a signal $\mathbf{x}\in\mathbb{C}^N$ from the magnitudes of linear measurements $\mathbf{Ax}\in\mathbb{C}^M$. While recent theory has established that $M\approx 4N$ intensity measurements are…

Information Theory · Computer Science 2015-06-19 Philip Schniter , Sundeep Rangan

Approximate message passing (AMP) methods have gained recent traction in sparse signal recovery. Additional information about the signal, or \emph{side information} (SI), is commonly available and can aid in efficient signal recovery. This…

Information Theory · Computer Science 2019-05-06 Anna Ma , You , Zhou , Cynthia Rush , Dror Baron , Deanna Needell

It is shown that a large class of communication systems which admit a sum-product algorithm (SPA) based receiver also admit a corresponding linear-programming (LP) based receiver. The two receivers have a relationship defined by the local…

Information Theory · Computer Science 2016-11-15 Mark F. Flanagan

In orthogonal time sequency multiplexing (OTSM) modulation, the information symbols are conveyed in the delay-sequency domain upon exploiting the inverse Walsh Hadamard transform (IWHT). It has been shown that OTSM is capable of attaining a…

Information Theory · Computer Science 2023-07-07 Zeping Sui , Shefeng Yan , Hongming Zhang , Sumei Sun , Yonghong Zeng , Lie-Liang Yang , Lajos Hanzo

1-bit compressive sensing aims to recover sparse signals from quantized 1-bit measurements. Designing efficient approaches that could handle noisy 1-bit measurements is important in a variety of applications. In this paper we use the…

Information Theory · Computer Science 2022-04-28 Shuai Huang , Trac D. Tran

This paper considers the Gaussian multiple-access channel (MAC) in the asymptotic regime where the number of users grows linearly with the code length. We propose efficient coding schemes based on random linear models with approximate…

Information Theory · Computer Science 2022-05-04 Kuan Hsieh , Cynthia Rush , Ramji Venkataramanan

Multiple-input multiple-output (MIMO) techniques have recently demonstrated significant potentials in visible light communications (VLC), as they can overcome the modulation bandwidth limitation and provide substantial improvement in terms…

Information Theory · Computer Science 2017-02-07 Hanaa Marshoud , Paschalis C. Sofotasios , Sami Muhaidat , Bayan S. Sharif , George K. Karagiannidis