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20112020
most citedSparse Estimation using Bayesian Hierarchical Prior Modeling for Real and Complex Linear Models

74 citations · 152 across the 10 of their papers we have counts for

collaborators

12 papers

eess.SP2020★ 9 cited

Distributed Receivers for Extra-Large Scale MIMO Arrays: A Message Passing Approach

Abolfazl Amiri, Sajad Rezaie, Carles Navarro Manchon +1

We study the design of receivers in extra-large scale MIMO (XL-MIMO) systems, i.e. systems in which the base station is equipped with an antenna array of extremely large dimensions…

cs.IT2020

How URLLC can Benefit from NOMA-based Retransmissions

Radosław Kotaba, Carles Navarro Manchón, Tommaso Balercia +1

Among the new types of connectivity unleashed by the emerging 5G wireless systems, Ultra-Reliable Low Latency Communication (URLLC) is perhaps the most innovative, yet challenging…

eess.SP2019

A Message Passing Based Receiver for Extra-Large Scale MIMO

Abolfazl Amiri, Carles Navarro Manch'on, Elisabeth de Carvalho

We consider a massive MIMO system where the array at the access point reaches a dimension that is much larger than the array in current systems. Transitioning to an extremely large…

cs.IT2017★ 9 cited

Hybrid Precoding for Massive MIMO Systems in Cloud RAN Architecture with Capacity-Limited Fronthauls

Jihong Park, Dong Min Kim, Elisabeth De Carvalho +1

Cloud RAN (C-RAN) is a promising enabler for distributed massive MIMO systems, yet is vulnerable to its fronthaul congestion. To cope with the limited fronthaul capacity, this pape…

cs.NI2017

A Traffic Model for Machine-Type Communications Using Spatial Point Processes

Henning Thomsen, Carles Navarro Manchón, Bernard Henri Fleury

A source traffic model for machine-to-machine communications is presented in this paper. We consider a model in which devices operate in a regular mode until they are triggered int…

cs.IT2016★ 2 cited

Turbo-Equalization Using Partial Gaussian Approximation

Chuanzong Zhang, Zhongyong Wang, Carles Navarro Manchón +3

This paper deals with turbo-equalization for coded data transmission over intersymbol interference (ISI) channels. We propose a message-passing algorithm that uses the expectation-…

stat.ML2013★ 2 cited

A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation

Niels Lovmand Pedersen, Carles Navarro Manchón Bernard Henri Fleury

In this paper, we present a Bayesian channel estimation algorithm for multicarrier receivers based on pilot symbol observations. The inherent sparse nature of wireless multipath ch…

cs.IT2012★ 1 cited

Distributed Iterative Processing for Interference Channels with Receiver Cooperation

Mihai-Alin Badiu, Carles Navarro Manchón, Vasile Bota +1

We propose a framework for the derivation and evaluation of distributed iterative algorithms for receiver cooperation in interference-limited wireless systems. Our approach views t…

stat.ML2012★ 3 cited

Application of Bayesian Hierarchical Prior Modeling to Sparse Channel Estimation

Niels Lovmand Pedersen, Carles Navarro Manchón, Dmitriy Shutin +1

Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood func…

cs.IT2012★ 28 cited

Message-Passing Algorithms for Channel Estimation and Decoding Using Approximate Inference

Mihai-Alin Badiu, Gunvor Elisabeth Kirkelund, Carles Navarro Manchón +2

We design iterative receiver schemes for a generic wireless communication system by treating channel estimation and information decoding as an inference problem in graphical models…

stat.ML2011★ 24 cited

Receiver Architectures for MIMO-OFDM Based on a Combined VMP-SP Algorithm

Carles Navarro Manchón, Gunvor E. Kirkelund, Erwin Riegler +2

Iterative information processing, either based on heuristics or analytical frameworks, has been shown to be a very powerful tool for the design of efficient, yet feasible, wireless…

stat.ML2011★ 74 cited

Sparse Estimation using Bayesian Hierarchical Prior Modeling for Real and Complex Linear Models

Niels Lovmand Pedersen, Carles Navarro Manchón, Mihai-Alin Badiu +2

In sparse Bayesian learning (SBL), Gaussian scale mixtures (GSMs) have been used to model sparsity-inducing priors that realize a class of concave penalty functions for the regress…