activity
20132022
most citedA Parallel Stochastic Approximation Method for Nonconvex Multi-Agent Optimization Problems

112 citations · 910 across the 35 of their papers we have counts for

collaborators

40 papers

eess.SP2022★ 99 cited

Three more Decades in Array Signal Processing Research: An Optimization and Structure Exploitation Perspective

Marius Pesavento, Minh Trinh-Hoang, Mats Viberg

The signal processing community currently witnesses the emergence of sensor array processing and Direction-of-Arrival (DoA) estimation in various modern applications, such as autom…

eess.SP2022★ 3 cited

Decentralized Eigendecomposition for Online Learning over Graphs with Applications

Yufan Fan, Minh Trinh-Hoang, Cemil Emre Ardic +1

In this paper, the problem of decentralized eigenvalue decomposition of a general symmetric matrix that is important, e.g., in Principal Component Analysis, is studied, and a decen…

eess.SP2022★ 47 cited

Coordinated Sum-Rate Maximization in Multicell MU-MIMO with Deep Unrolling

Lukas Schynol, Marius Pesavento

Coordinated weighted sum-rate maximization in multicell MIMO networks with intra- and intercell interference and local channel state at the base stations is recognized as an import…

eess.SP2021★ 16 cited

Ambiguities in Direction-of-Arrival Estimation with Linear Arrays

Frederic Matter, Tobias Fischer, Marius Pesavento +1

In this paper, we present a novel approach to compute ambiguities in thinned uniform linear arrays, i.e., sparse non-uniform linear arrays, via a mixed-integer program. Ambiguities…

eess.SP2021★ 7 cited

Extended Successive Convex Approximation for Phase Retrieval with Dictionary Learning

Tianyi Liu, Andreas M. Tillmann, Yang Yang +2

Phase retrieval aims at reconstructing unknown signals from magnitude measurements of linear mixtures. In this paper, we consider the phase retrieval with dictionary learning probl…

cs.IR2021

Recovery under Side Constraints

Khaled Ardah, Martin Haardt, Tianyi Liu +3

This paper addresses sparse signal reconstruction under various types of structural side constraints with applications in multi-antenna systems. Side constraints may result from pr…

eess.SP2021★ 25 cited

Probability of Resolution of MUSIC and g-MUSIC: An Asymptotic Approach

David Schenck, Xavier Mestre, Marius Pesavento

In this article, the outlier production mechanism of the conventional Multiple Signal Classification (MUSIC) and the g-MUSIC Direction-of-Arrival (DoA) estimation technique is inve…

eess.SP2019★ 6 cited

Coordinated Hybrid Precoding for Interference Exploitation in Heterogeneous Networks

Ganapati Hegde, Christos Masouros, Marius Pesavento

We consider a downlink multiuser massive MIMO system comprising multiple heterogeneous base stations with hybrid precoding architectures. To enhance the energy efficiency of the ne…

math.OC2019★ 86 cited

Inexact Block Coordinate Descent Algorithms for Nonsmooth Nonconvex Optimization

Yang Yang, Marius Pesavento, Zhi-Quan Luo +1

In this paper, we propose an inexact block coordinate descent algorithm for large-scale nonsmooth nonconvex optimization problems. At each iteration, a particular block variable is…

eess.SP2018

Iterative Marginal Maximum Likelihood DOD and DOA Estimation for MIMO Radar in the Presence of SIRP Clutter

Bruno Mériaux, Xin Zhang, Mohammed Nabil El Korso +1

The spherically invariant random process (SIRP) clutter model is commonly used in scenarios where the radar clutter cannot be correctly modeled as a Gaussian process. In this short…

eess.SP2018★ 16 cited

Interference Exploitation-based Hybrid Precoding with Robustness Against Phase Errors

Ganapati Hegde, Christos Masouros, Marius Pesavento

Hybrid analog-digital precoding significantly reduces the hardware costs in massive MIMO transceivers when compared to fully-digital precoding at the expense of increased transmit…

eess.SP2018

Energy Consumption Optimization in Mobile Communication Networks

Florian Bahlke, Marius Pesavento

This work addresses the challenge of minimizing the energy consumption of a wireless communication network by joint optimization of the base station transmit power and the cell act…

cs.LG2018★ 36 cited

Successive Convex Approximation Algorithms for Sparse Signal Estimation with Nonconvex Regularizations

Yang Yang, Marius Pesavento, Symeon Chatzinotas +1

In this paper, we propose a successive convex approximation framework for sparse optimization where the nonsmooth regularization function in the objective function is nonconvex and…

math.OC2018★ 7 cited

Joint Antenna Selection and Phase-Only Beamforming Using Mixed-Integer Nonlinear Programming

Tobias Fischer, Ganapati Hegde, Frederic Matter +3

In this paper, we consider the problem of joint antenna selection and analog beamformer design in downlink single-group multicast networks. Our objective is to reduce the hardware…

math.OC2018★ 21 cited

Energy efficiency optimization in MIMO interference channels: A successive pseudoconvex approximation approach

Yang Yang, Marius Pesavento, Symeon Chatzinotas +1

In this paper, we consider the (global and sum) energy efficiency optimization problem in downlink multi-input multi-output multi-cell systems, where all users suffer from multi-us…

eess.SP2018★ 47 cited

Optimized Cell Planning for Network Slicing in Heterogeneous Wireless Communication Networks

Florian Bahlke, Oscar D. Ramos-Cantor, Steffen Henneberger +1

We propose a cell planning scheme to maximize the resource efficiency of a wireless communication network while considering quality-of-service requirements imposed by different mob…

cs.DC2017

A Parallel Best-Response Algorithm with Exact Line Search for Nonconvex Sparsity-Regularized Rank Minimization

Yang Yang, Marius Pesavento

In this paper, we propose a convergent parallel best-response algorithm with the exact line search for the nondifferentiable nonconvex sparsity-regularized rank minimization proble…

eess.SP2017★ 57 cited

Partial Relaxation Approach: An Eigenvalue-Based DOA Estimator Framework

Minh Trinh-Hoang, Mats Viberg, Marius Pesavento

In this paper, the partial relaxation approach is introduced and applied to DOA estimation using spectral search. Unlike existing methods like Capon or MUSIC which can be considere…

stat.AP2017

Non-Coherent Direction-of-Arrival Estimation Using Partly Calibrated Arrays

Wassim Suleiman, Pouyan Parvazi, Marius Pesavento +1

In this paper, direction-of-arrival (DOA) estimation using non-coherent processing for partly calibrated arrays composed of multiple subarrays is considered. The subarrays are assu…

cs.IT2017★ 32 cited

Block- and Rank-Sparse Recovery for Direction Finding in Partly Calibrated Arrays

Christian Steffens, Marius Pesavento

A sparse recovery approach for direction finding in partly calibrated arrays composed of subarrays with unknown displacements is introduced. The proposed method is based on mixed n…

cs.NI2017★ 18 cited

Centralized Coordinated Scheduling in LTE-Advanced Networks

Oscar D. Ramos-Cantor, Jakob Belschner, Ganapati Hegde +1

This work addresses the problem associated with coordinating scheduling decisions among multiple base stations in an LTE-Advanced downlink network in order to manage inter-cell int…

stat.AP2016★ 29 cited

Robust Calibration of Radio Interferometers in Non-Gaussian Environment

Virginie Ollier, Mohammed Nabil El Korso, Rémy Boyer +2

The development of new phased array systems in radio astronomy, as the low frequency array (LOFAR) and the square kilometre array (SKA), formed of a large number of small and flexi…

q-bio.GN2016

Learning Directed-Acyclic-Graphs from Large-Scale Genomics Data

Fabio Nikolay, Marius Pesavento, George Kritikos +1

In this paper we consider the problem of learning the genetic-interaction-map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double knocko…

astro-ph.IM2016★ 4 cited

Parallel Calibration for Sensor Array Radio Interferometers

Martin Brossard, Mohammed Nabil El Korso, Marius Pesavento +3

In order to meet the theoretically achievable imaging performance, calibration of modern radio interferometers is a mandatory challenge, especially at low frequencies. In this pers…