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Related papers: Joint User Selection and Precoding in Multiuser MI…

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This paper deals with the problem of precoding in multibeam satellite systems. In contrast to general multiuser multiple-input-multiple-output (MIMO) cellular schemes, multibeam satellite architectures suffer from different challenges.…

Information Theory · Computer Science 2016-12-14 Vahid Joroughi , Miguel Ángel Vázquez , Ana I. Pérez-Neira

This paper addresses joint transceiver and relay design for a wireless multiple-input-multiple-output (MIMO) switching scheme that enables data exchange among multiple users. Here, a multi-antenna relay linearly precodes the received…

Information Theory · Computer Science 2016-11-18 Fanggang Wang , Xiaojun Yuan , Soung Chang Liew , Dongning Guo

This paper tackles the problem of the simultaneous interference among the multiple users in the downlink of a wireless multiantenna system. In order to exploit the multiuser interference and transform it into useful power at the receiver…

Signal Processing · Electrical Eng. & Systems 2020-11-10 Maha Alodeh , Björn Ottersten

We present reconstruction algorithms for smooth signals with block sparsity from their compressed measurements. We tackle the issue of varying group size via group-sparse least absolute shrinkage selection operator (LASSO) as well as via…

Machine Learning · Statistics 2013-09-11 Shahzad Gishkori , Geert Leus

Many practical wireless communications systems select their transmit rate from a finite set of modulation and coding schemes, which correspond to a set of discrete rates. In this paper, we therefore formulate a joint coordinated precoding…

Information Theory · Computer Science 2016-04-20 Rasmus Brandt , Mats Bengtsson

We consider the Multiple Input Single Output (MISO) Gaussian Broadcast channel with $N_t$ antennas at the base station (BS) and $N_u$ single-antenna users in the downlink. We propose a novel user grouping precoder which improves the sum…

Information Theory · Computer Science 2016-11-17 Saif Khan Mohammed , Erik G. Larsson

This study proposes a novel precoding scheme for multiuser multiple-input multiple-output (MIMO) relay systems in the presence of imperfect channel state information (CSI). The base station (BS) and the MIMO relay station (RS) are both…

Information Theory · Computer Science 2014-12-18 Y. Cai , R. C. de Lamare , L. L. Yang , M. Zhao

Precoding design for the downlink of multiuser multiple-input multiple-output (MU-MIMO) systems is a fundamental problem. In this paper, we aim to maximize the weighted sum rate (WSR) while considering both quality-of-service (QoS)…

Signal Processing · Electrical Eng. & Systems 2023-06-06 Kaiyi Chi , Yingzhi Huang , Qianqian Yang , Zhaohui Yang , Zhaoyang Zhang

We introduce a framework for linear precoder design over a massive multiple-input multiple-output downlink system in the presence of nonlinear power amplifiers (PAs). By studying the spatial characteristics of the distortion, we demonstrate…

Information Theory · Computer Science 2021-11-16 Sina Rezaei Aghdam , Sven Jacobsson , Ulf Gustavsson , Giuseppe Durisi , Christoph Studer , Thomas Eriksson

This paper studies the joint design of user grouping, scheduling (or admission control) and precoding to optimize energy efficiency (EE) for multigroup multicast scenarios in single-cell multiuser MISO downlink channels. Noticing that the…

Signal Processing · Electrical Eng. & Systems 2020-05-15 Ashok Bandi , Bhavani Shankar Mysore R , Symeon Chatzinotas , Björn Ottersten

In this paper, we propose to exploit the richly scattered multi-path nature of a frequency selective channel to provide additional degrees of freedom for desigining effective precoding schemes for multi-user communications. We design the…

Information Theory · Computer Science 2008-12-24 Wee Seng Chua , Chau Yuen , Yong Liang Guan , Francois Chin

Massive multi-input multiple-out (MIMO) is a key ingredient in improving the spectral efficiencies for next-generation cellular systems. Thanks to the channel reciprocity, in time-division-duplexing mode, each base station (BS) can acquire…

Signal Processing · Electrical Eng. & Systems 2021-07-30 Deokhwan Han , Namyoon Lee

Joint sparsity offers powerful structural cues for feature selection, especially for variables that are expected to demonstrate a "grouped" behavior. Such behavior is commonly modeled via group-lasso, multitask lasso, and related methods…

Machine Learning · Statistics 2012-04-09 Suvrit Sra

The long-term average performance of the MISO downlink channel, with a large number of users compared to transmit antennas of the BS, depends on the interference management which necessitates the joint design problem of scheduling and…

Signal Processing · Electrical Eng. & Systems 2019-02-14 Ashok Bandi , Bhavani Shankar Mysore R , Symeon Chatzinotas , Björn Ottersten

A structured variable selection problem is considered in which the covariates, divided into predefined groups, activate according to sparse patterns with few nonzero entries per group. Capitalizing on the concept of atomic norm, a composite…

Machine Learning · Computer Science 2023-11-03 David Gregoratti , Xavier Mestre , Carlos Buelga

User-centric (UC) based cell-free (CF) structures can provide the benefits of coverage enhancement for millimeter wave (mmWave) multiple input multiple output (MIMO) systems, which is regarded as the key technology of the reliable and…

Information Theory · Computer Science 2022-05-10 Yingrong Zhong , Yashuai Cao , Tiejun Lv

Cell-free massive multiple-input multiple-output (MIMO) is a promising cellular network. In this network, a large number of distributed and multi-antenna access points (APs) jointly serve many single antenna users using the same…

Signal Processing · Electrical Eng. & Systems 2021-07-30 Deokhwan Han , Jeonghun Park , Namyoon Lee

We consider channel estimation within pulse-shaping multicarrier multiple-input multiple-output (MIMO) systems transmitting over doubly selective MIMO channels. This setup includes MIMO orthogonal frequency-division multiplexing (MIMO-OFDM)…

Information Theory · Computer Science 2016-08-03 Daniel Eiwen , Georg Tauboeck , Franz Hlawatsch , Hans Georg Feichtinger

Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these models is the recovery of "interpretable"…

Machine Learning · Computer Science 2015-03-05 Luca Baldassarre , Nirav Bhan , Volkan Cevher , Anastasios Kyrillidis , Siddhartha Satpathi

We study a norm for structured sparsity which leads to sparse linear predictors whose supports are unions of prede ned overlapping groups of variables. We call the obtained formulation latent group Lasso, since it is based on applying the…

Machine Learning · Statistics 2011-10-05 Guillaume Obozinski , Laurent Jacob , Jean-Philippe Vert