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Compressed sensing aims to undersample certain high-dimensional signals, yet accurately reconstruct them by exploiting signal characteristics. Accurate reconstruction is possible when the object to be recovered is sufficiently sparse in a…

Information Theory · Computer Science 2015-05-13 David L. Donoho , Arian Maleki , Andrea Montanari

This paper tackles the problem of millimeter-Wave (mmWave) channel estimation in massive MIMO communication systems. A new Bayes-optimal channel estimator is derived using recent advances in the approximate belief propagation (BP) Bayesian…

Information Theory · Computer Science 2019-03-07 Faouzi Bellili , Foad Sohrabi , Wei Yu

This work presents a new variation of the commonly used Least Mean Squares Algorithm (LMS) for the identification of sparse signals with an a-priori known sparsity using a hard threshold operator in every iteration. It examines some useful…

Systems and Control · Computer Science 2016-08-04 Lampros Flokas , Petros Maragos

The problem of network-constrained averaging is to compute the average of a set of values distributed throughout a graph G using an algorithm that can pass messages only along graph edges. We study this problem in the noisy setting, in…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-15 Nima Noorshams , Martin Wainwright

Quantized constant envelope (QCE) precoding, a new transmission scheme that only discrete QCE transmit signals are allowed at each antenna, has gained growing research interests due to its ability of reducing the hardware cost and the…

Information Theory · Computer Science 2023-02-21 Zheyu Wu , Ya-Feng Liu , Bo Jiang , Yu-Hong Dai

We propose an estimator of prediction error using an approximate message passing (AMP) algorithm that can be applied to a broad range of sparse penalties. Following Stein's lemma, the estimator of the generalized degrees of freedom, which…

Machine Learning · Statistics 2018-08-01 Ayaka Sakata

Compressed sensing posits that, within limits, one can undersample a sparse signal and yet reconstruct it accurately. Knowing the precise limits to such undersampling is important both for theory and practice. We present a formula that…

Information Theory · Computer Science 2013-01-09 David Donoho , Iain Johnstone , Andrea Montanari

This paper presents an energy-efficient downlink precoding scheme with the objective of maximizing system energy efficiency in a multi-cell massive MIMO system. The proposed precoding design jointly considers the issues of power control,…

Networking and Internet Architecture · Computer Science 2018-12-27 Shuai Zhang , Lu Liu , Yu Cheng , Xianghui Cao , Sheng Zhou , Zhisheng Niu , Hangguan Shan

In this paper, we extend the bilinear generalized approximate message passing (BiG-AMP) approach, originally proposed for high-dimensional generalized bilinear regression, to the multi-layer case for the handling of cascaded problem such as…

Information Theory · Computer Science 2021-09-08 Qiuyun Zou , Haochuan Zhang , Hongwen Yang

In this paper, we propose a sparse signal estimation algorithm that is suitable for many wireless communication systems, especially for the future millimeter wave and underwater communication systems. This algorithm is not only…

Information Theory · Computer Science 2018-07-20 Chongwen Huang , Lei Liu , Chau Yuen

Approximate message passing (AMP) is a low-cost iterative parameter-estimation technique for certain high-dimensional linear systems with non-Gaussian distributions. However, AMP only applies to independent identically distributed (IID)…

Information Theory · Computer Science 2021-06-07 Lei Liu , Shunqi Huang , Brian M. Kurkoski

We consider the problem of recovering an unknown signal ${\mathbf x}\in {\mathbb R}^n$ from general nonlinear measurements obtained through a generalized linear model (GLM), i.e., ${\mathbf y}= f\left({\mathbf A}{\mathbf x}+{\mathbf…

Information Theory · Computer Science 2022-10-18 Jiang Zhu , Xiangming Meng , Xupeng Lei , Qinghua Guo

Precoding design based on weighted sum-rate (WSR) maximization is a fundamental problem in downlink multi-user multiple-input multiple-output (MU-MIMO) systems. While the weighted minimum mean-square error (WMMSE) algorithm is a standard…

Signal Processing · Electrical Eng. & Systems 2025-10-24 Xi Gao , Akang Wang , Junkai Zhang , Qihong Duan , Jiang Xue

In this paper, an efficient distributed approach for implementing the approximate message passing (AMP) algorithm, named distributed AMP (DAMP), is developed for compressed sensing (CS) recovery in sensor networks with the sparsity K…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-05-26 Puxiao Han , Ruixin Niu , Mengqi Ren

This paper presents joint power allocation and interference mitigation techniques for the downlink of spread spectrum systems which employ multiple relays and the amplify and forward cooperation strategy. We propose a joint constrained…

Information Theory · Computer Science 2013-01-29 Rodrigo C. de Lamare

This paper investigates the linear precoder design for $K$-user interference channels of multiple-input multiple-output (MIMO) transceivers under finite alphabet inputs. We first obtain general explicit expressions of the achievable rate…

Information Theory · Computer Science 2016-11-18 Yongpeng Wu , Chengshan Xiao , Xiqi Gao , John D. Matyjas , Zhi Ding

We propose a low complexity, graph based linear minimum mean square error (LMMSE) filter in which the non-white characteristics of a random process are taken into account. Our method corresponds to block LMMSE filtering, and has the…

Information Theory · Computer Science 2014-05-14 Pinar Sen , Ali Ozgur Yilmaz

In this paper, we propose a symbol-level precoding (SLP) design that aims to minimize the weighted mean square error between the received signal and the constellation point located in the constructive interference region (CIR). Unlike most…

Information Theory · Computer Science 2022-10-04 Yafei Wang , Wenjin Wang , Li You , Christos G. Tsinos , Shi Jin

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

We consider downlink precoding in a frequency-selective multi-user Massive MIMO system with highly efficient but non-linear power amplifiers at the base station (BS). A low-complexity precoding algorithm is proposed, which generates…

Information Theory · Computer Science 2013-05-08 Saif Khan Mohammed , Erik G. Larsson