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  • 1.
    Agrawal, Piyush
    et al.
    United Technologies Research Center, Cork, Irland.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Olofsson, Tomas
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Gidlund, M
    Characterization of long term channel variations in industrial wireless sensor networks2014Conference paper (Refereed)
  • 2.
    Agrawal, Piyush
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Olofsson, Tomas
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Gidlund, Mikael
    Long Term Channel Characterization for Energy Efficient Transmission in Industrial Environments2014In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 62, no 8, p. 3004-3014Article in journal (Refereed)
    Abstract [en]

    One of the challenges for a successful use of wireless sensor networks in process industries is to design networks with energy efficient transmission, to increase the lifetime of the deployed network while maintaining the required latency and bit-error rate. The design of such transmission schemes depend on the radio channel characteristics of the region. This paper presents an investigation of the statistical properties of the radio channel in a typical process industry, particularly when the network is meant to be deployed for a long time duration, e. g., days, weeks, and even months. Using 17-20-h-long extensive measurement campaigns in a rolling mill and a paper mill, we highlight the non-stationarity in the environment and quantify the ability of various distributions, given in the literature, to describe the variations on the links. Finally, we analyze the design of an optimal received signal-to-noise ratio (SNR) for the deployed nodes and show that improper selection of the distribution for modeling of the variations in the channel can lead to an overuse of energy by a factor of four or even higher.

  • 3.
    Ahlén, A
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Lindbom, L
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, M
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Analysis of stability and performance of adaptation algorithms with time-invariant gains2004In: IEEE Transactions on Signal Processing, Vol. 52, p. 103-116Article in journal (Refereed)
  • 4.
    Ahlén, Anders
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    An input estimation approach to differentiation of noisy data1984Report (Other scientific)
  • 5.
    Ahlén, Anders
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Identifiability of an input estimation problem1986Report (Other scientific)
  • 6.
    Ahlén, Anders
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Reglerteknik / Control theory: Inledande kurs / An introduction1985Report (Other scientific)
  • 7.
    Ahlén, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlgren, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Grönroos, Roland
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Gunningberg, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Hjort, Klas
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Micro Structural Technology.
    Katardjiev, Ilia
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Electronics.
    Rohner, Christian
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Rydberg, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Presentation of the VINN Excellence Center for Wireless Sensor Networks (WISENET)2008In: Conference on Radio Science (RVK08), Växjö, 2008Conference paper (Refereed)
  • 8.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Solbrand, Göte
    Repeated recursive identification for off line estimation1983In: ACI 83, 1983Conference paper (Refereed)
  • 9.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Solbrand, Göte
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Numerisk lösning av ett optimalstyrproblem med evolutionsmetoden1982Report (Other scientific)
  • 10.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Adaptive deconvolution based on spectral decomposition1991Report (Other scientific)
  • 11.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Filter design via inner-outer factorization: Comments on "Optimal deconvolution filter design based on orthogonal principle"1992In: Signal ProcessingArticle in journal (Other scientific)
  • 12.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Optimal filtering problems1992In: Polynomial methods in optimal control and filtering, Peter Peregrinus, London , 1992Chapter in book (Refereed)
  • 13.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Optimal input estimation: A polynomial approach1985Report (Other scientific)
  • 14.
    Bahne, Adrian
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Optimizing the similarity of loudspeaker: Room responses in multiple listening positions2016In: IEEE Transactions on Audio, Speech, and Language Processing, ISSN 1558-7916, E-ISSN 1558-7924, Vol. 24, no 2, p. 340-353Article in journal (Refereed)
    Abstract [en]

    A shortcoming of multichannel sound reproduction standards, such as stereo or 5.1 surround, is their incompatibility with multiple off-axis listening positions. Accurate reproduction of virtual sound sources can only be experienced in the sweet spot, which is located equidistant to the loudspeakers. We here present a novel methodology to compensate audio systems such that the channel similarity is optimized in several listening positions simultaneously. To that end we propose a novel MIMO personal audio filter design framework based on feed-forward control. By proper design choices, filters that successfully compensate for multiple offaxis positions and irregularities in the frequency sum responses are obtained. The design choices include allpass filters with appropriate phase shifts as target for each listening position in addition to a weighted similarity requirement. Evaluations based on measurements of two four-channel car audio systems show that the proposed method significantly improves timbral sound reproduction and phantom center reproduction in several listening positions simultaneously.

  • 15.
    Bahne, Adrian
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Brännmark, Lars-Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Improved loudspeaker-room equalization for stereo systems regarding channel similarity2012In: Proceedings - International Conference on Audio, Language and Image Processing, 2012, p. 254-259Conference paper (Refereed)
    Abstract [en]

    In this paper, a new approach to robust singlechannel loudspeaker-room equalization for stereo systems based on psychoacoustic insights is presented. Traditionally, in single-channel equalization each channel is equalized individually according to a desired target. In case the target cannot be reached for at least one of the two channels, this approach results in different loudspeaker-room transfer functions of the two channels at the listening position. However, reproducing the intended sound image of stereo recordings requires equal acoustic transfer functions from the input to the two loudspeakers to the listening region. In this paper we aim not only at equalizing the individual channels according to a desired target, but also at explicitly requiring symmetry between the two channels of a stereo system. To this end we propose a two-channel similarity SIMO controller structure, which is an extension to an earlier approach by the authors. The new approach is evaluated based on measurements in a room and is found to reduce differences between the room transfer functions of the two channels in both frequency and time domain.

  • 16.
    Bahne, Adrian
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Brännmark, Lars-Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Symmetric loudspeaker-room equalization utilizing a pairwise channel similarity criterion2013In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, no 24, p. 6276-6290Article in journal (Refereed)
    Abstract [en]

    Similarity of the room transfer functions (RTFs) of symmetric channel pairs is crucial for correct sound reproduction of, for example, stereophonic or 5.1 surround multichannel recordings. This physical and psychoacoustical insight yielded the filter design framework presented in this paper. The filter design framework introduced is based on MIMO feedforward control. It has the aim of pairwise equalization of two audio channels and incorporates two features. In the first place, each channel is individually equalized by minimizing the difference between a desired target response and the original RTF by means of support loudspeakers. The second and novel feature represents the similarity requirement and aims at minimizing the difference between the compensated RTFs of the two channels. In order to asses the proposed method a measure of RTF similarity is proposed. Tests with measurements of two different multichannel audio systems proved the method to be able to significantly improve the similarity of two RTFs.

  • 17.
    Björnemo, Erik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Johansson, Mathias
    Dirac Research AB, Uppsala.
    On the energy-efficiency of cooperative MIMO in nakagami-fading wireless sensor networks2007Conference paper (Refereed)
  • 18.
    Björnemo, Erik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Johansson, Mathias
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Two hops in one too many in an energy-limited wireless sensor network2007Conference paper (Refereed)
  • 19.
    Brännmark, Lars-Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group. Dirac AB, Uppsala.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Multichannel Room Correction with Focus Control2015In: Journal of The Audio Engineering Society, ISSN 0004-7554, ISSN 1549-4950, Vol. 63, no 1-2, p. 21-30Article in journal (Refereed)
    Abstract [en]

    Digital equalization of audio systems is mostly performed on a channel-by-channel basis, i.e., loudspeakers are equalized separately and independently of each other. In reverberant rooms the spatial variability of the loudspeaker room transfer function puts a limit on what can be achieved with such single-channel approaches, and considerably more far-reaching results can be obtained with multichannel methods. In this paper we present a multichannel equalizer design method where the loudspeaker to be equalized is assisted by several support loudspeakers that act in combination to improve the response of the main loudspeaker while suppressing the reverberation of the listening room. However, since a full dereverberation may not always be desirable, we shall here study the proposed method from the perspective of how to control the amount of room correction for a given number of contributing support loudspeakers. The amount of correction is controlled by a scalar parameter that we interpret as a "focus control," enabling the user to slide seamlessly between a single-channel equalizer and a full multichannel inversion of the room.

  • 20.
    Brännmark, Lars-Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Robust loudspeaker equalization based on position-independent excess phase modeling2008In: 2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, 2008, p. 385-388Conference paper (Refereed)
    Abstract [en]

    A well known problem in loudspeaker equalization is that mixed phase design of the inverse filter causes residual "pre-ringings" in the equalized system, due to the spatial variability of loudspeakerroom transfer functions. A common strategy for robust and perceptually acceptable equalization is therefore to use minimum phase filters only. In this paper, a method for cautious mixed phase equalization is proposed. By analysis of a set of room transfer functions, it is concluded that some non-minimum phase zeros are insensitive to receiver position, and can therefore be robustly inverted. The method improves upon a minimum phase equalization by extending the minimum phase model with a robustly invertible all pass link. Validation measurements show that the time-domain aspect of equalization is improved throughout the spatial region of interest, while preringings are kept at a very low and prespecified level.

  • 21.
    Brännmark, Lars-Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Spatially robust audio compensation based on SIMO feedforward control2009In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 57, no 5, p. 1689-1702Article in journal (Refereed)
    Abstract [en]

    This paper introduces a single-input multiple-output (SIMO) feedforward approach to the single-channel loudspeaker equalization problem. Using a polynomial multivariable control framework, a spatially robust equalizer is derived base on a set of room transfer functions (RTFs) and a multipoint mean-square error (MSE) criterion. In contrast to earlier multipoint methods, the polynomial approach provides analytical expressions for the optimum filter, involving the RTF polynomials and certain spatial averages thereof. However, a direct use of the optimum solution is questionable from a perceptual point of view. Despite its multipoint MSE optimality, the filter exhibits similar, albeit less severe, problems as those encountered in nonrobust single-point designs. First, in the case of mixed phase design it is shown to cause residual "pre-ringings" and undesirable magnitude distortion in the equalized system. Second, due to insufficient spatial averaging when using a limited number of RTFs in the design, the filter is overfitted to the chosen set of measurement points, thus providing insufficient robustness. A remedy to these two problems is proposed, based on a   constrained MSE design and a method for clustering of RTF zeros. The outcome is a mixed phase compensator with a time-domain performance preferable to that of the original unconstrained design.

  • 22.
    Brännmark, Lars-Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Variable control of the pre-response error in mixed phase audio precompensation2009In: 2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA 2009), New York CIty, NY, 2009Conference paper (Refereed)
  • 23.
    Brännmark, Lars-Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Bahne, Adrian
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Compensation of Loudspeaker-Room Responses in a Robust MIMO Control Framework2013In: IEEE Transactions on Audio, Speech, and Language Processing, ISSN 1558-7916, E-ISSN 1558-7924, Vol. 21, no 6, p. 1201-1216Article in journal (Refereed)
    Abstract [en]

    A new multichannel approach to robust broadband loudspeaker-room equalization is presented. Traditionally, the equalization (or room correction) problem has been treated primarily by single-channel methods, where loudspeaker input signals are prefiltered individually by separate scalar filters. Single-channel methods are generally able to improve the average spectral flatness of the acoustic transfer functions in a listening region, but they cannot reduce the variability of the transfer functions within the region. Most modern audio reproduction systems, however, contain two or more loudspeakers, and in this paper we aim at improving the equalization performance by using all available loudspeakers jointly. To this end we propose a polynomial based MIMO formulation of the equalization problem. The new approach, which is a generalization of an earlier single-channel approach by the authors, is found to reduce the average reproduction error and the transfer function variability over a region in space. Moreover, pre-ringing artifacts are avoided, and the reproduction error below 1000 Hz is significantly reduced with an amount that scales with the number of loudspeakers used.

  • 24.
    Brännmark, Lars-Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Bahne, Adrian
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Improved loudspeaker-room equalization using multiple loudspeakers and MIMO feedforward control2012In: Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference, 2012, p. 237-240Conference paper (Refereed)
    Abstract [en]

    In this paper, a new multichannel approach to robust loudspeaker-room equalization is presented. Traditionally, the equalization (or room correction) problem has been treated mostly by single-channel methods, with loudspeaker signals being prefiltered individually by separate scalar filters. Single-channel methods can generally improve the average spectral flatness of the acoustic transfer functions in a listening region, but the variability of the transfer functions within the region cannot be affected. Most modern audio reproduction systems, however, contain two or more loudspeakers, and in this paper we aim at improving the equalization performance by using all available loudspeakers jointly. To this end we propose a general MIMO formulation of the problem, which is a multichannel generalization of an earlier single-channel approach by the authors. The new approach is found to reduce the average reproduction error and the spatial variability of the acoustic transfer functions. Moreover, pre-ringing artifacts are avoided, and the reproduction error below 1000 Hz is significantly reduced with an amount that scales with the number of loudspeakers used.

  • 25.
    Carlsson, Bengt
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Technology, Department of Engineering Sciences, Signal Processing.
    Söderström, Torsten
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Technology, Department of Engineering Sciences, Signal Processing.
    Ahlén, Anders
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Digital differentiating filters1987Report (Other scientific)
  • 26.
    Eriksson, Oskar
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Björnemo, Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Gidlund, Mikael
    On Hybrid ARQ Adaptive Forward Error Correction in Wireless Sensor Networks2011In: IECON 2011: 37TH ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2011Conference paper (Refereed)
    Abstract [en]

    The use of wireless technology in the process industry is becoming increasingly important to obtain fast deployment at low cost. However, poor channel quality often leads to retransmissions, which are governed by Automatic Repeat Request (ARQ) schemes. While ARQ is a simple and useful tool to alleviate packet errors, it has considerable disadvantages: retransmissions lead to an increase in energy expenditure and latency. The use of Forward Error Correction (FEC) however offers several advantages. We consider a Hybrid-ARQ-Adaptive-FEC scheme (HAF) based on BCH codes and Channel State Information. This scheme is evaluated on AWGN and fading channels. It is shown that HAF offers significantly improved performance both in terms of energy efficiency and latency, as compared to ARQ.

  • 27.
    Gunningberg, Per
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Grönroos, Roland
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
    Katardjiev, Ilia
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electronics.
    Voigt, Thiemo
    SICS.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing.
    Hjort, Klas
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Micro Structural Technology.
    Rydberg, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing.
    WISENET Wireless Sensor Networks VINN Excellence Center2007Other (Other academic)
    Abstract [en]

    This broschure was produced for the inauguration of WISENET December 7, 2007. It decribes the future impact of WISENET, application areas and the 10 partners. The three research areas "Node Integration & Energy", "Networkning & Security" and "Wireless Communication" is briefly described as well as the application projects in "Water Sensing" and "Transport".

  • 28.
    Herman, Ivo
    et al.
    Czech Tech Univ, Dept Control Engn, Prague, Czech Republic..
    Knorn, Steffi
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Disturbance scaling in bidirectional vehicle platoons with different asymmetry in position and velocity coupling2017In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 82, p. 13-20Article in journal (Refereed)
    Abstract [en]

    This paper considers a string of vehicles where the local control law uses the states of the vehicle's immediate predecessor and follower. The coupling towards the preceding vehicle can be chosen different to the coupling with the following vehicle, which is referred to as an asymmetric bidirectional string. Further, the asymmetry for the velocity coupling can be chosen differently to the asymmetry in the position coupling. It is investigated how the effect of the disturbance on the control errors in the string depends on the string length. It is shown, that in case of symmetric position coupling and asymmetric velocity coupling, linear scaling can be achieved. For symmetric interactions, the errors scale quadratically in the number of vehicles. When the coupling in position is asymmetric, exponential scaling may occur or the system might even become unstable. The paper thus gives a comprehensive overview of the achievable performance in linear, asymmetric, bidirectional platoons. The results reveal that symmetry in the position coupling and asymmetry in velocity coupling qualitatively improve the performance of the string. Extensive numerical results illustrate the theoretical findings.

  • 29.
    Johansson, Mathias
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Björnemo, Erik
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Fixed link margins outperforms power control in energy-limited wireless sensor networks2007Conference paper (Refereed)
  • 30.
    Jurado, Isabel
    et al.
    Departamento de Ingenierìa de Sistemas y Automàtica, Escuela Superior de Ingenieros, Universidad de Sevilla, Spanien.
    Quevedo, Daniel E
    School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, Australien.
    Johansson, K H
    ACCESS Linaeus Centre, School of Electrical Engineering, KTH, Stockholm.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Cooperative Dynamic MPC for NCSs2013In: Distributed MPC Made Easy, Berlin, Heidelberg Tyskland: Springer-Verlag , 2013Chapter in book (Refereed)
  • 31.
    Knorn, Steffi
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Deviation bounds in multi agent systems described by undirected graphs2016In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 67, p. 205-210Article in journal (Refereed)
    Abstract [en]

    The theory of port-Hamiltonian systems is used to derive upper bounds for the state deviations in multi agent systems described by undirected graphs pinned to a reference signal. The upper bounds for the deviations in networks of first or second order agents, respectively, depend on the minimal eigenvalue of the extended Laplacian of the system. In networks of first order agents, the deviations decay exponentially with a rate depending on the same minimal eigenvalue. In case networks of second order systems meet specific design properties, it can be shown that the deviations also decay exponentially with half the rate compared to first order systems.

  • 32.
    Knorn, Steffi
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Dey, Subhrakanti
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Quevedo, Daniel E.
    Distortion Minimization in Multi-Sensor Estimation Using Energy Harvesting and Energy Sharing2015In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 63, no 11, p. 2848-2863Article in journal (Refereed)
    Abstract [en]

    This paper investigates an optimal energy allocation problem for multisensor estimation of a random source where sensors communicate their measurements to a remote fusion center (FC) over orthogonal fading wireless channels using uncoded analog transmissions. The FC reconstructs the source using the best linear unbiased estimator (BLUE). The sensors have limited batteries but can harvest energy and also transfer energy to other sensors in the network. A distortion minimization problem over a finite-time horizon with causal and noncausal centralized information is studied and the optimal energy allocation policy for transmission and sharing is derived. Several structural necessary conditions for optimality are presented for the two sensor problem with noncausal information and a horizon of two time steps. A decentralized energy allocation algorithm is also presented where each sensor has causal information of its own channel gain and harvested energy levels and has statistical information about the channel gains and harvested energies of the remaining sensors. Various other suboptimal energy allocation policies are also proposed for reducing the computational complexity of dynamic programming based solutions to the energy allocation problems with causal information patterns. Numerical simulations are included to illustrate the theoretical results. These illustrate that energy sharing can reduce the distortion at the FC when sensors have asymmetric fading channels and asymmetric energy harvesting processes.

  • 33.
    Knorn, Steffi
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Dey, Subhrakanti
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Quevedo, Daniel E
    Univ Newcastle, Sch Elect Engn & Comp Sci, Callaghan, NSW 2308, Australia.
    Multi-sensor estimation using energy harvesting and energy sharing2015Conference paper (Refereed)
    Abstract [en]

    This paper investigates an optimal energy allocation problem for multi sensor estimation of a random source where sensors communicate their measurements to a remote fusion centre (FC) over orthogonal fading wireless channels using uncoded analog transmissions. The FC reconstructs the source using the best linear unbiased estimator (BLUE). The sensors have limited batteries but can harvest energy and also transfer energy to other sensors in the network. A distortion minimization problem over a finite-time horizon with causal and non-causal information is studied and the optimal energy allocation policy for transmission and sharing is derived. Several structural necessary conditions for optimality are presented for the two sensor problem with non-causal information and a horizon of two time steps. Numerical simulations are included to illustrate the theoretical results.

  • 34.
    Leong, Alex S
    et al.
    Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3052, Australien.
    Quevedo, Daniel E
    School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, Australien.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Johansson, KH
    KTH, Stockholm.
    Network topology reconfiguration for state estimation over sensor networks with correlated packet drops2014Conference paper (Refereed)
  • 35. Leong, Alex S
    et al.
    Quevedo, Daniel E
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Johansson, KH
    KTH.
    On network topology reconfiguration for remote state estimation2015In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523Article in journal (Refereed)
  • 36.
    Leong, Alex S
    et al.
    Department of Electical Engineering, Paderborn University, Tyskland.
    Quevedo, Daniel E
    Department of Electrical Engineering, Paderborn University, Tyskland.
    Tanaka, Takashi
    Royal Inst Technol, Sch Elect Engn, Dept Automat Control, Stockholm, Sweden.
    Dey, Subhrakanti
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Event-Based Transmission Scheduling and LQG Control Over a Packet Dropping Link2017In: 20th IFAC World Congress / [ed] Denis Dochain, Didier Henrion, Dimitri Peaucelle, Elsevier, 2017, p. 8945-8950Conference paper (Refereed)
    Abstract [en]

    This paper studies a joint transmission scheduling and controller design problem, which minimizes a linear combination of the control cost and expected energy usage of the sensor. Assuming that the sensor transmission decisions are event-based and determined using the random estimation error covariance information available to the controller, we show a separation in the design of the transmission scheduler and controller. The optimal controller is given as the solution to an LQG-type problem, while the optimal transmission policy is a threshold policy on the estimation error covariance at the controller.

  • 37.
    Limmanee, Athipat
    et al.
    Department of Electrical and Electronic Engineering, The University of Melbourne, VIC 3010, Australien.
    Dey, Subhrakanti
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Distorsion minimization via multiple sensors under energy harvesting constraints2013Conference paper (Refereed)
  • 38.
    Lindbom, Lars
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Falkenström, M
    Tracking of time-varying mobile radio channels: Part II: A case study2002In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 50, p. 156-167Article in journal (Refereed)
  • 39.
    Lindbom, Lars
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Ahlén, Anders
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Adaptation with constant gains: Analysis for slow variations2001In: IEEE International Conference on Acoustics, Speech and Signal Processing, Salt Lake City, UT, 2001Conference paper (Refereed)
  • 40.
    Lindbom, Lars
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Tracking of time-varying mobile radio channels: Part I: The Wiener LMS algorithm2001In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 49, p. 2207-2217Article in journal (Refereed)
  • 41. Nourian, Mojtaba
    et al.
    Dey, Subhrakanti
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Distortion Minimization in Multi-Sensor Estimation With Energy Harvesting2015In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 33, no 3, p. 524-539Article in journal (Refereed)
    Abstract [en]

    This paper presents a design methodology for optimal energy allocation to estimate a random source using multiple wireless sensors equipped with energy harvesting technology. In this framework, multiple sensors observe a random process and then transmit an amplified uncoded analog version of the observed signal through Markovian fading wireless channels to a remote station. The sensors have access to an energy harvesting source, which is an everlasting but unreliable random energy source compared to conventional batteries with fixed energy storage. The remote station or so-called fusion centre estimates the realization of the random process by using a best linear unbiased estimator. The objective is to design optimal energy allocation policies at the sensor transmitters for minimizing total distortion over a finite-time horizon or a long term average distortion over an infinite-time horizon subject to energy harvesting constraints. This problem is formulated as a Markov decision process (MDP) based stochastic control problem and the optimal energy allocation policies are obtained by the use of dynamic programming techniques. Using the concept of submodularity, the structure of the optimal energy allocation policies is studied, which leads to an optimal threshold policy for binary energy allocation levels. Motivated by the excessive communication burden for the optimal control solutions where each sensor needs to know the channel gains and harvested energies of all other sensors, suboptimal decentralized strategies are developed where only statistical information about all other sensors' channel gains and harvested energies is required. Numerical simulation results are presented illustrating the performance of the optimal and suboptimal algorithms.

  • 42.
    Olofsson, Tomas
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Gidlund, M
    Modeling of the fading statistics of wireless sensor network channels in industrial environments2016In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 64, no 12, p. 3021-3034Article in journal (Refereed)
    Abstract [en]

    This paper presents an investigation of how to model the statistical properties of radio channels arising in industrial environments over long time horizons, e.g., hours and days. Based on extensive measurement campaigns, conducted at three different factory buildings, it is shown that for mobile transceivers the fading characteristics are Rayleigh or close to Rayleigh. However, for transceivers mounted at fixed locations, the use of conventional single fading distributions is not sufficient. It is shown that a suitable model structure for describing the fading properties of the radio channels, as measured by power, is a mixture of gamma and compound gamma-lognormal distributions. Furthermore, the complexity of the model generally increases with the observation interval. A model selection approach based on a connection between Kullback's mean discrimination information and the log-likelihood provides a robust choice of model structure. We show that while a (semi)-Markov chain constitute a suitable model for the channel dynamics the time dependence of the data can be neglected in the estimation of the parameters of the mixture distributions. Neglecting the time dependence in the data leads to a more efficient parametrization. Moreover, it is shown that the considered class of mixture distributions is identifiable for both continuous and quantized data under certain conditions and under those conditions a maximum likelihood under independence assumption estimator is shown to give consistent parameters also for data which are not independent. The parameter estimates are obtained by maximizing the log likelihood using a genetic and a local interior point algorithm.

  • 43.
    Ostergaard, Jan
    et al.
    Dept of Electronic System, Aalborg University, Denmark.
    Quevedo, Daniel E
    University of Newcastle, Callaghan, Australia.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Predictive power control and multiple description coding for wireless sensor networks2009In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009), Taipei, Taiwan, 2009Conference paper (Refereed)
  • 44.
    Ostergaard, Jan
    et al.
    Dept of Electronic Systems, Aalborg University, Aalborg, Danmark.
    Quevedo, Daniel E
    School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, Australien.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Predictive power control for dynamic state estimation over wireless sensor networks with relays2010In: : EUSIPCO 2010, Aalborg, Danmark, 2010Conference paper (Refereed)
  • 45.
    Quevedo, Daniel E
    et al.
    University of Newcastle, Callaghan, Australien.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    A predictive power control scheme for energy efficient state estimation via wireless sensor networks2008In: IEEE Conference on Decision and Control, Cancún, Mexico, 2008Conference paper (Refereed)
  • 46.
    Quevedo, Daniel E
    et al.
    University of Newcastle, Callaghan, Australia.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Goodwin, Graham G
    University of Newcastle, Callaghan, Australia.
    Predictive Power Control of Wireless Sensor Networks for Closed Loop Control2009In: Nonlinear Model Predictive Control: Towards New Challenging Applications / [ed] Lalo Magni, Davide Martino Raimondo, Frank Allgöwer, Springer Verlag , 2009, p. 215-224Chapter in book (Other academic)
  • 47.
    Quevedo, Daniel E
    et al.
    School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, Australien.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Johansson, Karl H
    ACCESS Linnaeus Centre, School of Electrical Engineering, Royal Institute of Technology, Stockholm.
    Stability of state estimation over sensor networks with Markovian fading channels2011In: IFAC World Congress 2011, Milano, Italien., 2011Conference paper (Refereed)
  • 48.
    Quevedo, Daniel E
    et al.
    School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, Australien.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Johansson, Karl H.
    KTH, Stockholm.
    State Estimation Over Sensor Networks With Correlated Wireless Channels2013In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 58, no 3, p. 581-593Article in journal (Refereed)
    Abstract [en]

    Stochastic stability for centralized time-varying Kalman filtering over a wireless sensor network with correlated fading channels is studied. On their route to the gateway, sensor packets, possibly aggregated with measurements from several nodes, may be dropped because of fading links. To study this situation, we introduce a network state process, which describes a finite set of configurations of the radio environment. The network state characterizes the channel gain distributions of the links, which are allowed to be correlated between each other. Temporal correlations of channel gains are modeled by allowing the network state process to form a (semi-)Markov chain. We establish sufficient conditions that ensure the Kalman filter to be exponentially bounded. In the one-sensor case, this new stability condition is shown to include previous results obtained in the literature as special cases. The results also hold when using power and bit-rate control policies, where the transmission power and bit-rate of each node are nonlinear mapping of the network state and channel gains.

  • 49.
    Quevedo, Daniel E
    et al.
    School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, Australien.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Leong, Alex S.
    Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC, Australien.
    Dey, Subhrakanti
    Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC, Australien.
    On Kalman filtering over fading wireless channels with controlled transmission powers2012In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 48, no 7, p. 1306-1316Article in journal (Refereed)
    Abstract [en]

    We study stochastic stability of centralized Kalman filtering for linear time-varying systems equipped with wireless sensors. Transmission is over fading channels where variable channel gains are counteracted by power control to alleviate the effects of packet drops. We establish sufficient conditions for the expected value of the Kalman filter covariance matrix to be exponentially bounded in norm. The conditions obtained are then used to formulate stabilizing power control policies which minimize the total sensor power budget. In deriving the optimal power control laws, both statistical channel information and full channel information are considered. The effect of system instability on the power budget is also investigated for both these cases.

  • 50.
    Quevedo, Daniel E
    et al.
    School of Electrical Engineering & Computer Science, The University of Newcastle, Newcastle, Australien.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Leong, Alex S
    Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3052, Australien.
    Dey, Subhrakanti
    Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3052, Australien.
    On Kalman filtering with fading wireless channels governed by power control.2011In: IFAC World Congress 2011, Milano, Italien., 2011Conference paper (Refereed)
12 1 - 50 of 61
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