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  • 1.
    Marinho, Marco
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). University of Brasília (UnB), Department of Electrical Engineering (ENE), Brasília, Brazil.
    Antreich, Felix
    Department of Teleinformatics Engineering Federal University of Ceará (UFC), Fortaleza, Brazil.
    da Costa, João Paulo C.L.
    University of Brasília (UnB), Department of Electrical Engineering (ENE), Brasília, Brazil.
    Caizzone, Steffano
    German Aerospace Center (DLR), Institute for Communications and Navigation, Wessling, Germany.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Pignaton de Freitas, Edison
    Federal University of Rio Grande do Sul (UFRGS), Informatics Institute, Porto Alegre, Brazil.
    Robust Nonlinear Array Interpolation for Direction of Arrival Estimation of Highly Correlated Signals2018In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 144, p. 19-28Article in journal (Refereed)
    Abstract [en]

    Important signal processing techniques need that the response of the different elements of a sensor array has specific characteristics. For physical systems this often is not achievable as the array elements’ responses are affected by mutual coupling or other effects. In such cases, it is necessary to apply array interpolation to allow the application of ESPRIT, Forward Backward Averaging (FBA), and Spatial Smoothing (SPS). Array interpolation provides a model or transformation between the true and a desired array response. If the true response of the array becomes more distorted with respect to the desired one or the considered region of the field of view of the array increases, nonlinear approaches becomes necessary. This work presents two novel methods for sector discretization. An Unscented Transform (UT) based method and a principal component analysis (PCA) based method are discussed. Additionally, two novel nonlinear interpolation methods are developed based on the nonlinear regression schemes Multivariate Adaptive Regression Splines (MARS) and Generalized Regression Neural Networks (GRNNs). These schemes are extended and applied to the array interpolation problem. The performance of the proposed methods is examined using simulated and measured array responses of a physical system used for research on mutual coupling in antenna arrays. © 2017 The Author(s). Published by Elsevier B.V.

  • 2.
    Wolkerstorfer, Martin
    et al.
    FTW Telecommunications Research Center Vienna, Vienna, Austria.
    Jaldén, Joakim
    KTH, Stockholm, Sverige.
    Nordström, Tomas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Low-Complexity Optimal Discrete-Rate Spectrum Balancing in Digital Subscriber Lines2013In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 93, no 1, p. 23-34Article in journal (Refereed)
    Abstract [en]

    Discrete-rate spectrum balancing in interference-limited multi-user and multi-carrier digital subscriber lines (DSL) is a large-scale, non-convex and combinatorial problem. Previously proposed algorithms for its (dual) optimal solution are only applicable for networks with few users, while the suboptimality of less complex bit-loading algorithms has not been adequately studied so far. We deploy constrained optimization techniques as well as problem-specific branch-and-bound and search-space reduction methods, which for the first time give a low-complexity guarantee of optimality in certain multi-user DSL networks of practical size. Simulation results precisely quantify the suboptimality of multi-user bit-loading schemes in a thousand ADSL2 scenarios under measured channel data.

  • 3.
    Wolkerstorfer, Martin
    et al.
    FTW Telecommunications Research Center Vienna, Vienna, Austria.
    Nordström, Tomas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). FTW Telecommunications Research Center Vienna, Vienna, Austria.
    Comparative Simulation Study of Fast Heuristics for Power Control in Copper Broadband Networks2014In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 104, no November 2014, p. 437-449Article in journal (Refereed)
    Abstract [en]

    The data-rate in currently deployed multi-carrier digital subscriber line (DSL) communication systems is limited by the interference among copper lines. This interference can be alleviated by multi-user transmit power allocation. Problem decomposition results in a large number of per-subcarrier problems. Our objective is to solve these nonconvex integer per-subcarrier power control problems at low complexity. For this purpose we develop ten combinatorial heuristics and test them by simulation under a small complexity budget in scenarios with tens of DSL users, where optimal solutions are currently intractable. Simulation results lead us to the conclusion that simple randomized greedy heuristics extended by a specific local search perform well despite the stringent complexity restriction. This has implications on multi-user discrete resource allocation algorithms, as these can be designed to jointly optimize transmit power among users even in large-scale scenarios.

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