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Simonetto, Andrea (author), Dall'Anese, Emiliano (author), Paternain, Santiago (author), Leus, G.J.T. (author), Giannakis, Georgios B. (author)Optimization underpins many of the challenges that science and technology face on a daily basis. Recent years have witnessed a major shift from traditional optimization paradigms grounded on batch algorithms for medium-scale problems to challenging dynamic, time-varying, and even huge-size settings. This is driven by technological...journal article 2020
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Bushnaq, Osama M. (author), Chaaban, Anas (author), Chepuri, Sundeep Prabhakar (author), Leus, G.J.T. (author), Al-Naffouri, Tareq Y. (author)Optimal sensor selection for source parameter estimation in energy harvesting Internet of Things (IoT) networks is studied in this paper. Specifically, the focus is on the selection of the sensor locations which minimizes the estimation error at a fusion center, and to optimally allocate power and bandwidth for each selected sensor subject to...journal article 2020
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Coutino, Mario (author), Isufi, E. (author), Maehara, Takanori (author), Leus, G.J.T. (author)In this article, we explore the state-space formulation of a network process to recover from partial observations the network topology that drives its dynamics. To do so, we employ subspace techniques borrowed from system identification literature and extend them to the network topology identification problem. This approach provides a unified...journal article 2020
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Gama, F. (author), Isufi, E. (author), Leus, G.J.T. (author), Ribeiro, Alejandro (author)Network data can be conveniently modeled as a graph signal, where data values are assigned to nodes of a graph that describes the underlying network topology. Successful learning from network data is built upon methods that effectively exploit this graph structure. In this article, we leverage graph signal processing (GSP) to characterize the...review 2020
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Ajorloo, Abdollah (author), Amini, Arash (author), Tohidi, Ehsan (author), Bastani, Mohammad Hassan (author), Leus, G.J.T. (author)Compressive sensing (CS) has been widely used in multiple-input-multiple-output (MIMO) radar in recent years. Unlike traditional MIMO radar, detection/estimation of targets in a CS-based MIMO radar is accomplished via sparse recovery. In this article, for a CS-based colocated MIMO radar with linear arrays, we attempt to improve the target...journal article 2020
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Tohidi, Ehsan (author), Hariri, Alireza (author), Behroozi, Hamid (author), Nayebi, Mohammad Mahdi (author), Leus, G.J.T. (author), Petropulu, Athina P. (author)This article proposes a compressed-domain signal processing (CSP) multiple-input multiple-output (MIMO) radar, a MIMO radar approach that achieves substantial sample complexity reduction by exploiting the idea of CSP. CSP MIMO radar involves two levels of data compression followed by target detection at the compressed domain. First,...journal article 2020
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Isufi, E. (author), Banelli, Paolo (author), Di Lorenzo, Paolo (author), Leus, G.J.T. (author)A critical challenge in graph signal processing is the sampling of bandlimited graph signals; signals that are sparse in a well-defined graph Fourier domain. Current works focused on sampling time-invariant graph signals and ignored their temporal evolution. However, time can bring new insights on sampling since sensor, biological, and...journal article 2020
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Han, Jing (author), Wang, Yujie (author), Gong, Zehui (author), Leus, G.J.T. (author)Orthogonal signal-division multiplexing (OSDM) has recently emerged as a promising alternative to orthogonal frequency division multiplexing (OFDM) for high-rate wireless communications. Although providing more flexibility in system design, it suffers from a special interference structure, namely inter-vector interference (IVI), when channel...journal article 2020
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Zhang, Yu (author), Wang, Yue (author), Tian, Zhi (author), Leus, G.J.T. (author), Zhang, Gong (author)This paper aims at developing low-complexity solutions for super-resolution two-dimensional (2D) harmonic retrieval via covariance reconstruction. Given the collected sample covariance, a novel gridless compressed sensing approach is designed based on the atomic norm minimization (ANM) technique. The key is to perform a redundancy reduction (RR)...conference paper 2020
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Hagenaars, E. (author), Pandharipande, A. (author), Frimout, E. (author), Leus, G.J.T. (author)We consider the problem of detecting sensor commissioning in the form of determining the sensor layout. We address this problem for single-pixel thermopile sensors, located at the ceiling, that provide remote temperature measurements for people counting applications and HVAC controls. We employ a random forest classifier to determine the...conference paper 2020
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Coutino, Mario (author), Chepuri, Sundeep Prabhakar (author), Maehara, Takanori (author), Leus, G.J.T. (author)To analyze and synthesize signals on networks or graphs, Fourier theory has been extended to irregular domains, leading to a so-called graph Fourier transform. Unfortunately, different from the traditional Fourier transform, each graph exhibits a different graph Fourier transform. Therefore to analyze the graph-frequency domain properties of...journal article 2020
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Fernandez-Menduina, S. (author), Krahmer, F. (author), Leus, G.J.T. (author), Bhandari, A. (author)Direction-of-arrival (DoA) estimation is a mature topic with decades of history. Despite the progress in the field, very few papers have looked at the problem of DoA estimation with unknown dynamic range. Consider the case of space exploration or near-field and far-field emitters. In such settings, the amplitude of the impinging wavefront can be...conference paper 2020
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Yang, M. (author), Coutino, Mario (author), Isufi, E. (author), Leus, G.J.T. (author)While regularization on graphs has been successful for signal reconstruction, strategies for controlling the bias-variance trade-off of such methods have not been completely explored. In this work, we put forth a node varying regularizer for graph signal reconstruction and develop a minmax approach to design the vector of regularization...conference paper 2020
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van der Meulen, P.Q. (author), Coutino, Mario (author), Kruizinga, P. (author), Bosch, J.G. (author), Leus, G.J.T. (author)We consider the scenario of finding the transfer function of an aberrating layer in front of an ultrasound array. We are interested in blindly estimating this transfer function without prior knowledge of the unknown ultrasound sources or ultrasound contrast image. The algorithm gives an exact solution if the matrix representing the aberration...conference paper 2020
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Ebihara, Tadashi (author), Ogasawara, Hanako (author), Leus, G.J.T. (author)In this paper, we propose a novel underwater acoustic (UWA) communication scheme that achieves energy and spectrum efficiency simultaneously by combining Doppler-resilient orthogonal signal division multiplexing (D-OSDM) and multiple-input-multiple-output (MIMO) signaling. We present both the transmitter processing and the receiver processing...review 2020
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Tohidi, E. (author), Amiri, Rouhollah (author), Coutino, Mario (author), Gesbert, David (author), Leus, G.J.T. (author), Karbasi, Amin (author)Submodularity is a discrete domain functional property that can be interpreted as mimicking the role of well-known convexity/concavity properties in the continuous domain. Submodular functions exhibit strong structure that lead to efficient optimization algorithms with provable near-optimality guarantees. These characteristics, namely,...journal article 2020
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Manss, C. (author), Shutin, Dmitriy (author), Leus, G.J.T. (author)For swarm systems, distributed processing is of paramount importance, and Bayesian methods are preferred for their robustness. Existing distributed sparse Bayesian learn- ing (SBL) methods rely on the automatic relevance deter- mination (ARD), which involves a computationally complex reweighted l1-norm optimization, or they use loopy belief...journal article 2020
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Nambur Ramamohan, K. (author), Chepuri, S.P. (author), Comesana, Daniel Fernandez (author), Leus, G.J.T. (author)In this paper, the focus is on the gain and phase calibration of sparse sensor arrays to localize more sources than the number of physical sensors. The proposed technique is a blind calibration method as it does not require any calibrator sources. Joint estimation of the gain errors, phase errors, and source directions is a complicated non...conference paper 2019
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Han, J. (author), Chepuri, S.P. (author), Zhang, Qunfei (author), Leus, G.J.T. (author)Orthogonal signal-division multiplexing (OSDM) is a promising modulation scheme that provides a generalized framework to unify orthogonal frequency-division multiplexing (OFDM) and single-carrier frequency-domain equalization. By partitioning each data block into vectors, it allows for a flexible configuration to trade off resource management...journal article 2019
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Gama, F. (author), Marques, Antonio G. (author), Leus, G.J.T. (author), Ribeiro, Alejandro (author)Two architectures that generalize convolutional neural networks (CNNs) for the processing of signals supported on graphs are introduced. We start with the selection graph neural network (GNN), which replaces linear time invariant filters with linear shift invariant graph filters to generate convolutional features and reinterprets pooling as a...journal article 2019