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  • 1.
    Carlsson, Håkan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems.
    Skog, Isaac
    Linköping University, The Institute of Technology.
    Hendeby, Gustaf
    Linköping University, The Institute of Technology.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Inertial Navigation Using an Inertial Sensor ArrayManuscript (preprint) (Other academic)
    Abstract [en]

    We present a comprehensive framework for fusing measurements from multiple and generally placed accelerometers and gyroscopes to perform inertial navigation. Using the angular acceleration provided by the accelerometer array, we show that the numerical integration of the orientation can be done with second-order accuracy, which is more accurate compared to the traditional first-order accuracy that can be achieved when only using the gyroscopes. Since orientation errors are the most significant error source in inertial navigation,  improving the orientation estimation reduces the overall navigation error. The practical performance benefit depends on prior knowledge of the inertial sensor array, and therefore we present four different state-space models using different underlying assumptions regarding the orientation modeling. The models are evaluated using a  Lie Group Extended Kalman filter through simulations and real-world experiments.  We also show how individual accelerometer biases are unobservable and can be replaced by a six-dimensional bias term whose dimension is fixed and independent of the number of accelerometers.

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  • 2.
    Carlsson, Håkan
    et al.
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Skog, Isaac
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    On-The-Fly Geometric Calibration of Inertial Sensor Arrays2017In: Proceedings 2017 international conference on indoor positioning and indoor navigation (IPIN), Institute of Electrical and Electronics Engineers (IEEE) , 2017Conference paper (Refereed)
    Abstract [en]

    We present a maximum likelihood estimator for estimating the positions of accelerometers in an inertial sensor array. This method simultaneously estimates the positions of the accelerometers and the motion dynamics of the inertial sensor array and, therefore, does not require a predefined motion sequence nor any external equipment. Using an iterative block coordinate descent optimization strategy, the calibration problem can be solved with a complexity that is linear in the number of time samples. The proposed method is evaluated by Monte-Carlo simulations of an inertial sensor array built out of 32 inertial measurement units. The simulation results show that, if the array experiences sufficient dynamics, the position error is inversely proportional to the number of time samples used in the calibration sequence. Further, results show that for the considered array geometry and motion dynamics in the order of 2000 degrees/s and 2000 degrees/s(2), the positions of the accelerometers can be estimated with an accuracy in the order of 10(-6) m using only 1000 time samples. This enables fast on-the-fly calibration of the geometric errors in an inertial sensor array by simply twisting it by hand for a few seconds.

  • 3.
    Carlsson, Håkan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems.
    Skog, Isaac
    Linköping Univ, Dept Elect Engn, S-58183 Linköping, Sweden..
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Self-Calibration of Inertial Sensor Arrays2021In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 21, no 6, p. 8451-8463Article in journal (Refereed)
    Abstract [en]

    A maximum likelihood estimator is presented for self-calibrating both accelerometers and gyroscopes in an inertial sensor array, including scale factors, misalignments, biases, and sensor positions. By simultaneous estimation of the calibration parameters and the motion dynamics of the array, external equipment is not required for the method. A computational efficient iterative optimization method is proposed where the calibration problem is divided into smaller subproblems. Further, an identifiability analysis of the calibration problem is presented. The analysis shows that it is sufficient to know the magnitude of the local gravity vector and the average scale factor gain of the gyroscopes, and that the array is exposed to two types of motions for the calibration problem to be well defined. The proposed estimator is evaluated by real-world experiments and by Monte Carlo simulations. The results show that the parameters can be consistently estimated and that the calibration significantly improves the accuracy of the motion estimation. This enables on-the-fly calibration of small inertial sensors arrays by simply twisting them by hand.

  • 4.
    Carlsson, Håkan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems.
    Skog, Isaac
    Linköping Univ LIU, Dept Elect Engn, S-58183 Linköping, Sweden..
    Schön, Thomas B.
    Uppsala Univ, Dept Informat Technol, S-75236 Uppsala, Sweden..
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems.
    Quantifying the Uncertainty of the Relative Geometry in Inertial Sensors Arrays2021In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 21, no 17, p. 19362-19373Article in journal (Refereed)
    Abstract [en]

    We present an algorithm to estimate and quantify the uncertainty of the accelerometers' relative geometry in an inertial sensor array. We formulate the calibration problem as a Bayesian estimation problem and propose an algorithm that samples the accelerometer positions' posterior distribution using Markov chain Monte Carlo. By identifying linear substructures of the measurement model, the unknown linear motion parameters are analytically marginalized, and the remaining non-linear motion parameters are numerically marginalized. The numerical marginalization occurs in a low dimensional space where the gyroscopes give information about the motion. This combination of information from gyroscopes and analytical marginalization allows the user to make no assumptions of the motion before the calibration. It thus enables the user to estimate the accelerometer positions' relative geometry by simply exposing the array to arbitrary twisting motion. We show that the calibration algorithm gives good results on both simulated and experimental data, despite sampling a high dimensional space.

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  • 5. Chenouard, Nicolas
    et al.
    Smal, Ihor
    de Chaumont, Fabrice
    Maska, Martin
    Sbalzarini, Ivo F.
    Gong, Yuanhao
    Cardinale, Janick
    Carthel, Craig
    Coraluppi, Stefano
    Winter, Mark
    Cohen, Andrew R.
    Godinez, William J.
    Rohr, Karl
    Kalaidzidis, Yannis
    Liang, Liang
    Duncan, James
    Shen, Hongying
    Xu, Yingke
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Blau, Helen M.
    Paul-Gilloteaux, Perrine
    Roudot, Philippe
    Kervrann, Charles
    Waharte, Francois
    Tinevez, Jean-Yves
    Shorte, Spencer L.
    Willemse, Joost
    Celler, Katherine
    van Wezel, Gilles P.
    Dan, Han-Wei
    Tsai, Yuh-Show
    Ortiz de Solorzano, Carlos
    Olivo-Marin, Jean-Christophe
    Meijering, Erik
    Objective comparison of particle tracking methods2014In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 11, no 3, p. 281-U247Article in journal (Refereed)
    Abstract [en]

    Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

  • 6.
    del Aguila Pla, Pol
    et al.
    CIBM Ctr Biomed Imaging, CH-1015 Lausanne, Switzerland.;Ecole Polytech Fed Lausanne, Biomed Imaging Grp, CH-1015 Lausanne, Switzerland..
    Boquet-Pujadas, Aleix
    Ecole Polytech Fed Lausanne, Biomed Imaging Grp, CH-1015 Lausanne, Switzerland..
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Convex Quantization Preserves Logconcavity2022In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 29, p. 2697-2701Article in journal (Refereed)
    Abstract [en]

    A logconcave likelihood is as important to proper statistical inference as a convex cost function is important to variational optimization. Quantization is often disregarded when writing likelihood models, ignoring the limitations of the physical detectors used to collect the data. These two facts call for the question: would including quantization in likelihood models preclude logconcavity? are the true data likelihoods logconcave? We provide a general proof that the same simple assumption that leads to logconcave continuous-data likelihoods also leads to logconcave quantized-data likelihoods, provided that convex quantization regions are used.

  • 7.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Cell detection by functional inverse diffusion and non-negative group sparsity – Part I: Modeling and Inverse Problems2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 20, p. 5407-5421Article in journal (Refereed)
    Abstract [en]

    In this two-part paper, we present a novel framework and methodology to analyze data from certain image-based biochemical assays, e.g., ELISPOT and Fluorospot assays. In this first part, we start by presenting a physical partial differential equations (PDE) model up to image acquisition for these biochemical assays. Then, we use the PDEs' Green function to derive a novel parametrization of the acquired images. This parametrization allows us to propose a functional optimization problem to address inverse diffusion. In particular, we propose a non-negative group-sparsity regularized optimization problem with the goal of localizing and characterizing the biological cells involved in the said assays. We continue by proposing a suitable discretization scheme that enables both the generation of synthetic data and implementable algorithms to address inverse diffusion. We end Part I by providing a preliminary comparison between the results of our methodology and an expert human labeler on real data. Part II is devoted to providing an accelerated proximal gradient algorithm to solve the proposed problem and to the empirical validation of our methodology.

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  • 8.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Cell detection by functional inverse diffusion and non-negative group sparsity – Part II: Proximal optimization and Performance evaluation2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 20, p. 5422-5437Article in journal (Refereed)
    Abstract [en]

    In this two-part paper, we present a novel framework and methodology to analyze data from certain image-based biochemical assays, e.g., ELISPOT and Fluorospot assays. In this second part, we focus on our algorithmic contributions. We provide an algorithm for functional inverse diffusion that solves the variational problem we posed in Part I. As part of the derivation of this algorithm, we present the proximal operator for the non-negative group-sparsity regularizer, which is a novel result that is of interest in itself, also in comparison to previous results on the proximal operator of a sum of functions. We then present a discretized approximated implementation of our algorithm and evaluate it both in terms of operational cell-detection metrics and in terms of distributional optimal-transport metrics.

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  • 9.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Cell detection on image-based immunoassays2018In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), IEEE, 2018, p. 431-435Conference paper (Refereed)
    Abstract [en]

    Cell detection and counting in the image-based ELISPOT and Fluorospot immunoassays is considered a bottleneck.The task has remained hard to automatize, and biomedical researchers often have to rely on results that are not accurate.Previously proposed solutions are heuristic, and data-based solutions are subject to a lack of objective ground truth data. In this paper, we analyze a partial differential equations model for ELISPOT, Fluorospot, and assays of similar design. This leads us to a mathematical observation model forthe images generated by these assays. We use this model to motivate a methodology for cell detection. Finally, we provide a real-data example that suggests that this cell detection methodology and a human expert perform comparably.

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    delAguilaPla_Jalden_2018
  • 10.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Convolutional group-sparse coding and source localization2018Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a new interpretation of non-negatively constrained convolutional coding problems as blind deconvolution problems with spatially variant point spread function. In this light, we propose an optimization framework that generalizes our previous work on non-negative group sparsity for convolutional models. We then link these concepts to source localization problems that arise in scientific imaging, and provide a visual example on an image derived from data captured by the Hubble telescope.

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    fulltext
  • 11.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Inferences from quantized data - Likelihood logconcavityManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, we present to the signal processing community the most general likelihood logconcavity statement for quantized data to date, together with its proof, which has never been published. In particular, we show how Prékopa’s theorem can be used to show that the likelihood for quantized linear models is jointly logconcave with respect to both its location and scale parameter in a broad range of cases. In order to show this result and explain the limitations of the proof technique, we study sets generated by combinations of points with positive semi-definite matrices whose sum is the identity.

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    delAguilaPla_Jalden_Inference-quantized-data-logconcavity.pdf
  • 12.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Pellaco, Lissy
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Dwivedi, Satyam
    Ericsson Research.
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Clock synchronization over networks - Identifiability of the sawtooth modelManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, we analyze the two-node joint clocksynchronization and ranging problem. We focus on the case of nodes that employ time-to-digital converters to determine the range between them precisely. This specific design leads to a sawtooth model for the captured signal, which has not been studied in detail before from an estimation theory standpoint. In the study of this model, we recover the basic conclusion of a well-known article by Freris, Graham, and Kumar in clock synchronization. Additionally, we discover a surprising identifiability result on the sawtooth signal model: noise improves the theoretical condition of the estimation of the phase and offset parameters. To complete our study, we provide performance references for joint clock synchronization and ranging. In particular, we present the Cramér-Rao lower bounds that correspond to a linearization of our model, as well as a simulation study on the practical performance of basic estimation strategies under realistic parameters. With these performance references, we enable further research in estimation strategies using the sawtooth model and pave the path towards industrial use.

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    delAguilaPla_Pellaco_Dwivedi_Handel_Jalden_Clock-sync.pdf
  • 13.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Saxena, Vidit
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    SpotNet: Learned iterations for cell detection in image-based immunoassays2019In: Proceedings: International Symposium on Biomedical Imaging, Institute of Electrical and Electronics Engineers (IEEE) , 2019Conference paper (Refereed)
    Abstract [en]

    Accurate cell detection and counting in the image-based ELISpot and FluoroSpot immunoassays is a challenging task. Recently proposed methodology matches human accuracy by leveraging knowledge of the underlying physical process of these assays and using proximal optimization methods to solve an inverse problem. Nonetheless, thousands of computationally expensive iterations are often needed to reach a near-optimal solution. In this paper, we exploit the structure of the iterations to design a parameterized computation graph, SpotNet, that learns the patterns embedded within several training images and their respective cell information. Further, we compare SpotNet to a convolutional neural network layout customized for cell detection. We show empirical evidence that, while both designs obtain a detection performance on synthetic data far beyond that of a human expert, SpotNet is easier to train and obtains better estimates of particle secretion for each cell.

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    ISBI2019_delAguilaPla_Saxena_Jalden
  • 14.
    Dumard, Charlotte
    et al.
    Forschungszentrum Telekommunikation Wien.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zemen, Thomas
    Forschungszentrum Telekommunikation Wien.
    Multi-User MIMO Receiver Processing for Time-Varying Channels2011In: Wireless Communications Over Rapidly Time-Varying Channels / [ed] Franz Hlawatsch and Gerald Matz, Elsevier Academic Press , 2011, p. 337-374Chapter in book (Other academic)
    Abstract [en]

    Wireless broadband communications for mobile users at vehicular speed is the cornerstone of future fourth-generation systems. This chapter deals with joint iterative channel estimation and multiuser detection for the uplink of a multicarrier (MC) code division multiple access (CDMA) system. MCCDMA is based on orthogonal frequency division multiplexing (OFDM) and employs spreading sequences in the frequency domain. Several complexity reduction methods are discussed enabling a real-world low-complexity implementation, such as an iterative approximation of the maximum a posteriori (MAP) detector in combination with a reduced-rank model for the time-varying channel. This reduced-rank channel model projects the time-varying channel onto a subspace spanned by band-limited and time-concentrated prolate spheroidal sequences. Two different multiuser detection methods are investigated: First, the Krylov subspace method is used to reduce the complexity of multiuser detection using LMMSE filtering. Second, sphere decoding is investigated and a sphere decoder is developed that exploits the reduced-rank channel model for complexity reduction.

  • 15.
    Dumard, Charlotte
    et al.
    Forschungszentrum Telekommunikation Wien.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Zemen, Thomas
    Forschungszentrum Telekommunikation Wien.
    Soft Sphere Decoder for an Iterative Receiver in Time-Varying MIMO Channels2008Conference paper (Refereed)
  • 16. Elia, Petros
    et al.
    Jaldén, Joakim
    Construction criteria and existence results for approximately universal linear space-time codes with reduced decoding complexity2008In: 2008 46TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, VOLS 1-3, NEW YORK: IEEE , 2008, p. 1359-1364Conference paper (Refereed)
    Abstract [en]

    This work presents new eigenvalue bounds, necessary conditions and existence results for approximately universal linear (lattice) codes that can be drawn from lattices of reduced dimension, and can thus incur reduced decoding complexity. Currently for the n x n(r) MIMO channel, all known n x T approximately universal codes, except for the Alamouti code for n = 2, n(r) = 1, draw from lattices of dimension equal to or larger than nT, irrespective of n(r). Motivated by the case where n(r) < n, the work describes construction criteria for lattice codes that maintain their approximate universality even when they are drawn from lattices of reduced dimensionality.

  • 17. Elia, Petros
    et al.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fundamental rate-reliability-complexity limits in outage limited MIMO communications2010In: IEEE International Symposium on Information Theory - Proceedings, 2010, p. 2203-2207Conference paper (Refereed)
    Abstract [en]

    The work establishes fundamental limits between rate, reliability and computational complexity, for the general setting of outage-limited MIMO communications. In the high-SNR regime, the limits are optimized over all encoders, all decoders, and all complexity regulating policies. The work then proceeds to explicitly identify encoder-decoder designs and policies, that meet this optimal tradeoff. In practice, the limits aim to meaningfully quantify different pertinent and interrelated measures, such as the optimal rate-reliability capabilities per unit complexity and power, the optimal diversity gains per complexity costs, or the optimal goodput per flop. Finally the tradeoff's simple nature, renders it useful for insightful comparison of the rate-reliability-complexity capabilities for different encoders-decoders.

  • 18. Elia, Petros
    et al.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    General DMT optimality of LR-aided linear MIMO-MAC transceivers with worst-case complexity at most linear in sum-rate2010In: IEEE Information Theory Workshop 2010, 2010, Vol. ITW 2010, p. 5503161-Conference paper (Refereed)
    Abstract [en]

    In the setting of multiple-access MIMO channels, the work establishes the DMT optimality of lattice-reduction (LR)-aided regularized linear decoders. This is achieved irrespective of the lattice design applied by each user. The decoding algorithms employ efficient solutions to the Nearby Vector Problem with Preprocessing in the presence of a regularized non-Euclidean metric, and in the presence of time-outs. The decoders' optimality induces a worst-case computational complexity that is at most linear in the users' sum-rate. This constitutes a substantial improvement over the state of art of DMT optimal decoding, including ML decoders with complexity that is exponential in the sum-rate, or lattice decoders based on solutions to the NP-hard closest vector problem (CVP). The optimality of the efficient decoders is established for all channel statistics, for all channel dimensions, for any number of users, and irrespective of the different rates. The findings directly apply to different computationally intensive multi-user settings such as multi-user MIMO, multi-user cooperative communications, and multi-user MIMO-OFDM.

  • 19.
    Fertl, Peter
    et al.
    Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology.
    Jaldén, Joakim
    Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology.
    Matz, Gerald
    Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology.
    Capacity-Based Performance Comparison of MIMO-BICM Demodulators2008In: 2008 IEEE 9TH WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, 2008, p. 166-170Conference paper (Refereed)
    Abstract [en]

    This paper provides a performance comparison of multiple-input multiple-output (MIMO) demodulators for bit-interleaved coded modulation (BICM) systems with non-iterative demodulation and decoding. We propose to use the capacity of an equivalent "modulation" channel as a performance measure that has the advantage of not depending on the outer error correcting code. Based on this approach, we conclude that a universal ranking of MIMO (soft and hard) demodulation algorithms is not possible. This result is confirmed via bit error rate simulations for a practical system involving low-density parity-check codes. Our approach also allows to derive practical guidelines for MIMO-BICM system design.

  • 20. Fertl, Peter
    et al.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Matz, Gerald
    Performance Assessment of MIMO-BICM Demodulators Based on Mutual Information2012In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, no 3, p. 1366-1382Article in journal (Refereed)
    Abstract [en]

    We provide a comprehensive performance comparison of soft-output and hard-output demodulators in the context of non-iterative multiple-input multiple-output bit-interleaved coded modulation (MIMO-BICM). Coded bit error rate (BER), widely used in literature for demodulator comparison, has the draw-back of depending strongly on the error correcting code being used. This motivates us to propose the mutual information of the equivalent modulation channel (comprising modulator, wireless channel, and demodulator) as a code-independent performance measure. We present extensive numerical results for spatially independent identically distributed (i.i.d.) ergodic and quasi-static fading channels under perfect and imperfect channel state information. These results reveal that the performance ranking of MIMO demodulators is rate-dependent and provide new insights regarding MIMO-BICM system design, i.e., the choice of antenna configuration, symbol constellation, and demodulator for a given target rate.

  • 21. Flåm, John
    et al.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Gaussian mixture modeling for source localization2011In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2011, p. 2604-2607Conference paper (Refereed)
    Abstract [en]

    Exploiting prior knowledge, we use Bayesian estimation to localize a source heard by a fixed sensor network. The method has two main aspects: Firstly, the probability density function (PDF) of a function of the source location is approximated by a Gaussian mixture model (GMM). This approximation can theoretically be made arbitrarily accurate, and allows a closed form minimum mean square error (MMSE) estimator for that function. Secondly, the source location is retrieved by minimizing the Euclidean distance between the function and its MMSE estimate using a gradient method. Our method avoids the issues of a numerical MMSE estimator but shows comparable accuracy.

  • 22.
    Gustafsson, Fredrik
    et al.
    Linköping Univ, Div Automat Control, Linköping, Sweden..
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Bernhardsson, Bo
    Lund Univ, Dept Automat Control, Lund, Sweden..
    Soltesz, Kristian
    Lund Univ, Dept Automat Control, Lund, Sweden..
    Identifiability issues in estimating the impact of interventions on Covid-19 spread2020In: IFAC PAPERSONLINE, ELSEVIER , 2020, Vol. 53, no 5, p. 829-832Conference paper (Refereed)
    Abstract [en]

    The Covid-19 pandemic has spawned numerous dynamic modeling attempts aimed at estimation, prediction, and ultimately control. The predictive power of these attempts has varied, and there remains a lack of consensus regarding the mechanisms of virus spread and the effectiveness of various non-pharmaceutical interventions that have been enforced regionally as well as nationally. Setting out in data available in the spring of 2020, and with a nowfamous model by Imperial College researchers as example, we employ an information-theoretical approach to shed light on why the predictive power of early modeling approaches have remained disappointingly poor. 

  • 23. Isaksson, Markus
    et al.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Murphy, M. J.
    On using an adaptive neural network to predict lung tumor motion during respiration for radiotherapy applications2005In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 32, no 12, p. 3801-3809Article in journal (Refereed)
  • 24.
    Jain, Saumey
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Micro and Nanosystems. KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Protein Engineering. Division of Micro and Nanosystems, KTH Royal Institute of Technology, Stockholm, Sweden; Division of Nanobiotechnology, Department of Protein Science, SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden.
    Birgersson, Madeleine
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Kipen, Javier
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Stemme, Göran
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Micro and Nanosystems.
    Niklaus, Frank
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Micro and Nanosystems.
    Raja, Shyamprasad Natarajan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Micro and Nanosystems.
    Williams, Cecilia
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Cellular and Clinical Proteomics.
    Herland, Anna
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Nano Biotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, Centres, Center for the Advancement of Integrated Medical and Engineering Sciences, AIMES. Department of Neuroscience, Karolinska Institute, Stockholm, Sweden.
    Sensing of protein and DNA complexes using solid-state nanopores2023In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 122, no 3S1Article in journal (Refereed)
  • 25.
    Jalden, Joakim
    et al.
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Skoglund, Mikael
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    On the random coding exponent of multiple antenna systems using space-time block codes2004In: 2004 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, PROCEEDINGS, NEW YORK: IEEE , 2004, p. 189-189Conference paper (Refereed)
    Abstract [en]

    The random coding exponent of multiple antenna systems using space time block codes (STBC) was studied. The effects of different choices of STBC's on the overall performance of a antenna system was analyzed. A narrow band, block fading, multiple antenna channel with Nt antennas at the transmitter and Nr antennas at the receiver were considered for the analysis. The STBC symbols were transmitted across the channel using maximum likelihood, ML, sequence detection. The random coding exponent were found for the cases Nr = 1 and 2. It was concluded that by properly designing the inner STBC the length of the outer code could be reduced while maintaining some target error probability.

  • 26.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Detection for multiple input multiple output channels: analysis of sphere decoding and semidefinite relaxation2006Doctoral thesis, monograph (Other scientific)
    Abstract [en]

    The problem of detecting a vector of symbols, drawn from a finite alphabet and transmitted over a multiple-input multiple-output (MIMO) channel with Gaussian noise, is of central importance in digital communications and is encountered in several different applications. Examples include, but are not limited to; detection of symbols spatially multiplexed over a multiple-antenna channel and the multiuser detection problem in a code division multiple access (CDMA) system.

    Two algorithms previously proposed in the literature are considered and analyzed. Both algorithms have their origin in other fields of science but have gained mainstream recognition as efficient algorithms for the detection problem considered herein. Specifically, we consider the sphere decoder and semidefinite relaxation detector. By incorporating assumptions applicable in the communications context the performance of the two algorithms is addressed.

    The first algorithm, the sphere decoder, offers optimal performance in terms of its error probability. Further, the algorithm has proved extremely efficient in terms of computational complexity for moderately sized problems at high signal to noise ratio (SNR). Although it is recognized that the algorithm has an exponential worst case complexity, there has been a widespread belief that the algorithm has a polynomial average complexity at high SNR. A contribution made herein is to show that this is incorrect and that the average complexity, as the worst case complexity, is exponential in the number of symbols detected. Instead, another explanation of the observed efficiency of the algorithm is offered by deriving the exponential rate of growth and showing that this rate, although strictly positive for finite SNR, is small in the high SNR regime.

    The second algorithm, the semidefinite relaxation (SDR) detector, offers polynomial complexity at the expense of suboptimal performance in terms of error probability. Nevertheless, previous numerical observations suggest that error probability of the SDR algorithm is close to that of the optimal detector. Herein, the near optimality is of the SDR algorithm is given a precise meaning by studying the diversity of the SDR algorithm when applied to the (real valued) i.i.d.~Rayleigh fading channel and it is shown that the SDR algorithm achieves the same diversity order as the optimal detector. Further, criteria under which the SDR estimates coincide with the optimal estimates are derived and discussed.

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  • 27.
    Jaldén, Joakim
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Maximum likelihood detection for the linear MIMO channel2004Licentiate thesis, monograph (Other scientific)
    Abstract [en]

    this thesis the problem of maximum likelihood (ML) detection for the linear multiple-input multiple-output (MIMO) channel is considered. The thesis investigates two algorithms previously proposed in the literature for implementing the ML detector, namely semide nite relaxation and sphere decoding.

    The first algorithm, semide nite relaxation, is a suboptimal implementation of the ML detector meaning that it is not guaranteed to solve the maximum likelihood detection problem. Still, numerical evidence suggests that the performance of the semide nite relaxation detector is close to that of the true ML detector. A contribution made in this thesis is to derive conditions under which the semide nite relaxation estimate can be guaranteed to coincide with the ML estimate.

    The second algorithm, the sphere decoder, can be used to solve the ML detection problem exactly. Numerical evidence has previously shown that the complexity of the sphere decoder is remarkably low for problems of moderate size. This has led to the widespread belief that the sphere decoder is of polynomial expected complexity. This is however unfortunately not true. Instead, in most scenarios encountered in digital communications, the expected complexity of the algorithm is exponential in the number of symbols jointly detected. However, for high signal to noise ratio the rate of exponential increase is small. In this thesis it is proved that for a large class of detection problems the expected complexity is lower bounded by an exponential function. Also, for the special case of an i.i.d. Rayleigh fading channel, an asymptotic analysis is presented which enables the computation of the expected complexity up to the linear term in the exponent.

    Download full text (pdf)
    FULLTEXT01
  • 28.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Barbero, Luis G.
    Joint Research Institute for Signal & Image Processing, University of Edinburgh, EH9 3JL Edinburgh, UK.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Thompson, John S.
    Joint Research Institute for Signal & Image Processing, University of Edinburgh, EH9 3JL Edinburgh, UK.
    Full diversity detection in MIMO systems with a fixed-complexity sphere decoder2007In: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE , 2007, p. 49-52Conference paper (Refereed)
    Abstract [en]

    The fixed-complexity sphere decoder (FSD) has been previously proposed for multiple input-multiple output (MIMO) detection to overcome the two main drawbacks of the original sphere decoder (SD), namely its variable complexity and sequential structure. As such, the FSD is highly suitable for hardware implementation and has shown remarkable performance through simulations. Herein, we explore the theoretical aspects of the algorithm and prove that the FSD achieves the same diversity order as the maximum likelihood detector (MLD). Further, we show that the coding loss can be made negligible in the high signal to noise ratio (SNR) regime with a significantly lower complexity than that of the MLD.

  • 29.
    Jaldén, Joakim
    et al.
    Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology.
    Barbero, Luis G.
    Institute for Digital Communications, Joint Research Institute for Signal and Image Processing, The University of Edinburgh, UK.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Thompson, John S.
    Institute for Digital Communications, Joint Research Institute for Signal and Image Processing, The University of Edinburgh, UK.
    The Error Probability of the Fixed-Complexity Sphere Decoder2009In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 57, no 7, p. 2711-2720Article in journal (Refereed)
    Abstract [en]

    The fixed-complexity sphere decoder (FSD) has been previously proposed for multiple-input multiple-output (MIMO) detection in order to overcome the two main drawbacks of the sphere decoder (SD), namely its variable complexity and its sequential structure. Although the FSD has shown remarkable quasi-maximum-likelihood (ML) performance and has resulted in a highly optimized real-time implementation, no analytical study of its performance existed for an arbitrary MIMO system. Herein, the error probability of the FSD is analyzed, proving that it achieves the same diversity as the maximum-likelihood detector (MLD) independent of the constellation used. In addition, it can also asymptotically yield ML performance in the high-signal-to-noise ratio (SNR) regime. Those two results, together with its fixed complexity, make the FSD a very promising algorithm for uncoded MIMO detection.

  • 30.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Elia, Petros
    DMT Optimality of LR-Aided Linear Decoders for a General Class of Channels, Lattice Designs, and System Models2010In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 56, no 10, p. 4765-4780Article in journal (Refereed)
    Abstract [en]

    This paper identifies the first general, explicit, and nonrandom MIMO encoder-decoder structures that guarantee optimality with respect to the diversity-multiplexing tradeoff (DMT), without employing a computationally expensive maximum-likelihood (ML) receiver. Specifically, the work establishes the DMT optimality of a class of regularized lattice decoders, and more importantly the DMT optimality of their lattice-reduction (LR)-aided linear counterparts. The results hold for all channel statistics, for all channel dimensions, and most interestingly, irrespective of the particular lattice-code applied. As a special case, it is established that the LLL-based LR-aided linear implementation of the MMSE-GDFE lattice decoder facilitates DMT optimal decoding of any lattice code at a worst-case complexity that grows at most linearly in the data rate. This represents a fundamental reduction in the decoding complexity when compared to ML decoding whose complexity is generally exponential in the rate. The results' generality lends them applicable to a plethora of pertinent communication scenarios such as quasi-static MIMO, MIMO-OFDM, ISI, cooperative-relaying, and MIMO-ARQ channels, in all of which the DMT optimality of the LR-aided linear decoder is guaranteed. The adopted approach yields insight, and motivates further study, into joint transceiver designs with an improved SNR gap to ML decoding.

  • 31.
    Jaldén, Joakim
    et al.
    Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology, Austria .
    Elia, Petros
    LR-aided MMSE lattice decoding is DMT optimal for all approximately universal codes2009In: 2009 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, NEW YORK: IEEE , 2009, p. 1263-1267Conference paper (Refereed)
    Abstract [en]

    Currently for the n(T) x n(R) MIMO channel, any explicitly constructed space-time (ST) designs that achieve optimality with respect to the diversity multiplexing tradeoff (DMT) are known to do so only when decoded using maximum likelihood (ML) decoding, which may incur prohibitive decoding complexity. In this paper we prove that MMSE regularized lattice decoding, as well as the computationally efficient lattice reduction (LR) aided MMSE decoder, allows for efficient and DMT optimal decoding of any approximately universal lattice-based code. The result identifies for the first time an explicitly constructed encoder and a computationally efficient decoder that achieve DMT optimality for all multiplexing gains and all channel dimensions. The results hold irrespective of the fading statistics.

  • 32.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Elia, Petros
    Sphere Decoding Complexity Exponent for Decoding Full-Rate Codes Over the Quasi-Static MIMO Channel2012In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 58, no 9, p. 5785-5803Article in journal (Refereed)
    Abstract [en]

    In the setting of quasi-static multiple-input multiple-output channels, we consider the high signal-to-noise ratio (SNR) asymptotic complexity required by the sphere decoding (SD) algorithm for decoding a large class of full-rate linear space-time codes. With SD complexity having random fluctuations induced by the random channel, noise, and codeword realizations, the introduced SD complexity exponent manages to concisely describe the computational reserves required by the SD algorithm to achieve arbitrarily close to optimal decoding performance. Bounds and exact expressions for the SD complexity exponent are obtained for the decoding of large families of codes with arbitrary performance characteristics. For the particular example of decoding the recently introduced threaded cyclic-division-algebra-based codes-the only currently known explicit designs that are uniformly optimal with respect to the diversity multiplexing tradeoff-the SD complexity exponent is shown to take a particularly concise form as a non-monotonic function of the multiplexing gain. To date, the SD complexity exponent also describes the minimum known complexity of any decoder that can provably achieve a gap to maximum likelihood performance that vanishes in the high SNR limit.

  • 33.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Elia, Petros
    EURECOM.
    The complexity of sphere decoding perfect codes under a vanishing gap to ML performance2011In: 2011 IEEE International Symposium on Information Theory Proceedings (ISIT), IEEE , 2011, p. 2836-2840Conference paper (Refereed)
    Abstract [en]

    We consider the complexity of the sphere decoding (SD) algorithm when decoding a class of full rate space-time block codes that are optimal, over the quasi-static MIMO channel, with respect to the diversity-multiplexing tradeoff (DMT). Towards this we introduce the SD complexity exponent which represents the high signal-to-noise ratio (SNR) exponent of the tightest run-time complexity constraints that can be imposed on the SD algorithm while maintaining arbitrarily close to maximum likelihood (ML) performance. Similar to the DMT exposition, our approach naturally captures the dependence of the SD algorithm's computational complexity on the codeword density, code size and channel randomness, and provides simple closed form solutions in terms of the system dimensions and the multiplexing gain.

  • 34.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Fertl, P.
    Matz, G.
    On the generalized mutual information of BICM systems with approximate demodulation2010In: IEEE Information Theory Workshop 2010, Cairo, 2010, Vol. ITW 2010Conference paper (Refereed)
    Abstract [en]

    We consider a generic bit-interleaved coded modulation (BICM) systems with an approximate demodulator or loglike-lihood ratio (LLR) computer. The performance of a BICM system with optimal demodulation has previously been characterized by Caire et al. in terms of the capacity of an independent parallel-channel model with binary inputs and (continuous) LLRs as outputs, and by Martinez et al. in terms of the generalized mutual information (GMI) where the BICM decoder is viewed as a mismatched decoder. Whereas GMI and capacity of the parallelchannel model coincide under optimal demodulation, they differ in general for the case of an approximate demodulator. Herein we show (i) that augmenting approximate BICM demodulators with scalar LLR correction increases the GMI and (ii) that the GMI of the LLR-corrected system coincides with the capacity of the parallel-channel model with binary inputs and outputs given by the approximate LLRs.

  • 35.
    Jaldén, Joakim
    et al.
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Martin, Cristoff
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Semidefinite Programming for Detection in Linear Systems – Optimality Conditions and Space-Time Decoding2003In: IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE , 2003, Vol. 2, p. 9-12Conference paper (Refereed)
    Abstract [en]

    Optimal maximum likelihood detection of finite alphabet symbols in general requires time consuming exhaustive search methods. The computational complexity of such techniques is exponential in the size of the problem and for large problems sub-optimal algorithms are required. In this paper, to find a solution in polynomial time, a semidefinite programming approach is taken to estimate binary symbols in a general linear system. A condition under which the proposed method provides optimal solutions is derived. As an application, the proposed algorithm is used as a decoder for a linear space-time block coding system and the results are illustrated with numerical examples.

  • 36.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. Institute of Communications and Radio-Frequency Engineering (INTHFT), Vienna University of Technology, Austria .
    Matz, Gerald
    MIMO receiver diversity in general fading2008Conference paper (Refereed)
  • 37. Jaldén, Joakim
    et al.
    Maurer, Johannes
    Matz, Gerald
    On the diversity order of vector perturbation precoding with imperfect channel state information2008In: 2008 IEEE 9TH WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, VOLS 1 AND 2, NEW YORK: IEEE , 2008, p. 211-215Conference paper (Refereed)
    Abstract [en]

    We consider vector perturbation precoding over a quasi-static MIMO channel under the assumption of imperfect channel state information (CSI). This is accomplished via a high SNR analysis, specifically targeting the overall system diversity order and the identification of typical errors. The effects of long-term and short-term power constraints, or power allocation policies, are investigated. Our results indicate that under realistic assumptions regarding the channel estimation error the system is mainly interference limited and as such, the particular power constraint does not significantly affect the asymptotic behavior of the error probability. This is in sharp contrast to the case of perfect CSI.

  • 38.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Moreno, Xavier Casas
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Skog, Isaac
    Linkoping Univ, Dept Elect Engn, Linkoping, Sweden..
    USING THE ARDUINO DUE FOR TEACHING DIGITAL SIGNAL PROCESSING2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 6468-6472Conference paper (Refereed)
    Abstract [en]

    This paper describes an Arduino Due based platform for digital signal processing (DSP) education. The platform consists of an in-house developed shield for robust interfacing with analog audio signals and user inputs, and an off-the-shelf Arduino Due that executes the students' DSP code. This combination enables direct use of the Arduino integrated development environment (IDE), with its low barrier to entry for students, its low maintenance need and cross platform interoperability, and its large user base. Relevant hardware and software features of the platform are discussed throughout, as are design choices made in relation to learning objectives, and the planned use of the platform in our own DSP course.

  • 39.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Oechtering, Tobias J.
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Distributed Bayesian detection for the butterfly network2013In: 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE , 2013, p. 61-65Conference paper (Refereed)
    Abstract [en]

    We consider a distributed detection problem where two nodes, or decision makers, observe a common source and aim to decide on one of several hypotheses. Before making their individual decisions, the nodes are allowed to communicate over rate-constrained links, through a bidirectional relay. We show that if the rate of the common relay-to-node link is greater than or equal to the rate of the individual node-to-relay links, and the individual decisions are not coupled by the cost metric, then network coding at the relay allows the overall problem to decouple into two separate two-node distributed detection problems over serial networks; and the two serial networks can be designed independently. However, if the rate of the relay-to-node link is strictly less than the node-to-relay links, no such decoupling can be assumed in general, and the overall detection network needs to be jointly designed.

  • 40.
    Jaldén, Joakim
    et al.
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    An Exponential Lower Bound on the Expected Complexity of Sphere Decoding2004In: Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004, p. 393-396Conference paper (Refereed)
    Abstract [en]

    The sphere decoding algorithm is an efficient algorithm used to solve the maximum likelihood detection problem in several digital communication systems. The sphere decoding algorithm has previously been claimed to have polynomial expected complexity. While it is true that the algorithm has an expected complexity comparable to that of other polynomial time algorithms for problems of moderate size it is a misconception that the expected number of operations asymptotically grow as a polynomial function of the problem size. In order to illustrate this point we derive an exponential lower bound on the expected complexity of the sphere decoder.

  • 41.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Channel dependent termination of the semidefinite relaxation detector2006In: 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing, NEW YORK, NY: IEEE , 2006, p. 185-188Conference paper (Refereed)
    Abstract [en]

    We study the problem of semidefinite relaxation (SDR) for detection of symbols transmitted over a general MIMO channel. In the SDR detector the maximum likelihood detection problem is relaxed into a semidefinite program (SDP) which is solved numerically using an interior-point path-following algorithm. Herein, we provide a criteria which, based on the channel matrix realization, determine the accuracy required by the SDP solver to give a good bit error rate performance of the overall SDR detector. This also reduce the complexity of the SDR detector as it limits the number of interior iterations required in the SDP solver. The performance is demonstrated through simulations.

  • 42.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Detection Based on Relaxation in MIMO Systems2008In: Handbook on Advancements in Smart Antenna Technologies for Wireless Networks / [ed] Chen Sun, Jun Cheng, and Takashi Ohira, Premier Reference Source , 2008, 1, p. 308-327Chapter in book (Other academic)
  • 43.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    High diversity detection using semidefinite relaxation2006In: 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 2006, p. 2082-2086Conference paper (Refereed)
    Abstract [en]

    Receiver diversity is an important measure of a receivers robustness towards fading in wireless communications. For the detection of binary symbols transmitted over a general MIMO channel, the semidefinite relaxation (SDR) detector is a computationally attractive alternative to exact ML detection. In the SDR detector, the hard combinatorial optimization problem arising in the ML detector is relaxed into a simple convex optimization problem followed by component wise threshold decisions. In this work, we argue that the SDR detector win provide an increase in diversity over simpler decoder structures such as the ZF and NMSE detectors. Specifically, for the case of uncoded V-BLAST transmission over a MIMO channel with real valued i.i.d. Gaussian channel coefficients we present an analytic result stating that the SDR detector achieves the maximum possible receiver diversity.

  • 44.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    On the complexity of sphere decoding in digital communications2005In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, ISSN 1053-587X, Vol. 53, no 4, p. 1474-1484Article in journal (Refereed)
    Abstract [en]

    Sphere decoding has been suggested by a number of authors as an efficient algorithm to solve various detection problems in digital communications. In some cases, the algorithm is referred to as an algorithm of polynomial complexity without clearly specifying what assumptions are made about the problem structure. Another claim is that although worst-case complexity is exponential, the expected complexity of the algorithm is polynomial. Herein, we study the expected complexity where the problem size is defined to be the number of symbols jointly detected, and our main result is that the expected complexity is exponential for fixed signal-to-noise ratio (SNR), contrary to previous claims. The sphere radius, which is a parameter of the algorithm, must be chosen to ensure a nonvanishing probability of solving the detection problem. This causes the exponential complexity since the squared radius must grow linearly with problem size. The rate of linear increase is, however, dependent on the noise variance, and thus, the rate of the exponential function is strongly dependent on the SNR. Therefore sphere decoding can be efficient for some SNR and problems of moderate size, even though the number of operations required by the algorithm strictly speaking always grows as an exponential function of the problem size.

  • 45.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    On the limits of sphere decoding2005In: 2005 IEEE International Symposium on Information Theory (ISIT), Vols 1 and 2, NEW YORK: IEEE , 2005, p. 1691-1695Conference paper (Refereed)
    Abstract [en]

    The sphere decoder has emerged as one of the most promising techniques for maximum likelihood detection of symbols transmitted over a general MIMO channel. Although efficient for problems of moderate size it is known that the original sphere decoder is of exponential (expected) complexity which limits its usage for large scale problems. However, at this stage, many alterations and improvements over the original algorithm have appeared in the literature. Herein we study a generic sphere decoder for the i.i.d. Rayleigh fading MIMO channel. The detection ordering and search radius (parameters of the algorithm) are allowed to be arbitrary functions of the decoder input, the only restriction being that the search radius is chosen such that the detection problem is solved. It is shown that the set of problem instances solvable by the sphere decoder in less than exponential time will tend to zero with increasing problem size. This extends previous results by providing a statement which is stronger than exponential expected complexity while relaxing the assumptions regarding the specific decoder implementation.

  • 46.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    On the maximal diversity order of spatial multiplexing with transmit antenna selection2007In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 53, no 11, p. 4273-4276Article in journal (Refereed)
    Abstract [en]

    Zhang et al. recently derived upper and lower bounds on the achievable diversity of an N-R X N-T, i.i.d. Rayleigh fading multiple antenna system using transmit antenna selection, spatial multiplexing and a linear receiver structure. For the case of L = 2 transmitting (out of N-T available) antennas the bounds are tight and therefore specify the maximal diversity order. For the general case with L

  • 47.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Parallel implementation of a soft output sphere decoder2005In: 2005 39th Asilomar Conference on Signals, Systems and Computers, NEW YORK: IEEE , 2005, p. 581-585Conference paper (Refereed)
    Abstract [en]

    Transmission at rates close to capacity over fading multiple antenna channels can be achieved by concatenating inner space-time block codes and powerful outer codes such as turbo or LDPC codes. However, in such systems, computation of the required soft information, or log-likelihood ratios (LLR), for the bits transmitted over the channel is rather complex and some form of approximations are typically used. Herein, we show how the complexity of computing the max-log approximation of the LLR can be reduced by computing all LLR values simultaneously using a parallel sphere decoder implementation.

  • 48.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    The diversity order of the semidefinite relaxation detector2008In: IEEE Transactions on Information Theory, ISSN 0018-9448, E-ISSN 1557-9654, Vol. 54, no 4, p. 1406-1422Article in journal (Refereed)
    Abstract [en]

    In this paper, we consider the detection of binary (antipodal) signals transmitted in a spatially multiplexed fashion over a fading multiple-input-multiple-output (MIMO) channel and where the detection is done by means of semidefinite relaxation (SDR). The SDR detector is an attractive alternative to maximum-likelihood (NIL) detection since the complexity is polynomial rather than exponential. Assuming that the channel matrix is drawn with independent identically distributed (i.i.d.) real-valued Gaussian entries, we study the receiver diversity and prove that the SDR detector achieves the maximum possible diversity. Thus, the error probability of the receiver tends to zero at the same rate as the optimal NIL receiver in the high signal-to-noise ratio (SNR) limit. This significantly strengthens previous performance guarantees available for the semidefinite relaxation detector. Additionally, it proves that full diversity detection is also possible in certain scenarios when using a noncombinatorial receiver structure.

  • 49.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ma, Wing-Kin
    Dept. Electrical & Electronic Engineering, University of Melbourne Parkville, Vic., Australia.
    Reducing the average complexity of ML detection using semidefinite relaxation2005In: 2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2005, p. 1021-1024Conference paper (Refereed)
    Abstract [en]

    Maximum likelihood (ML) detection of symbols transmitted over a MIMO channel is generally a difficult problem due to its NP-hard nature. However, not every instance of the detection problem is equally hard. Thus, the average complexity of an ML detector may be significantly smaller than its worst-case counterpart. This is typically true in the high SNR regime where the received signals are closer to the noise free transmitted signals. Herein, a method which may be used to lower the average complexity of any ML detector is proposed. The method is based on the ability to verify if a symbol estimate is ML, using an optimality condition provided by the near-ML semidefinite relaxation technique. The average complexity reduction advantage of the proposed method is confirmed by numerical results.

  • 50.
    Jaldén, Joakim
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology, Austria .
    Seethaler, Dominik
    Matz, Gerald
    Worst- and average-case complexity of LLL lattice reduction in MIMO wireless systems2008In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2008, p. 2685-2688Conference paper (Refereed)
123 1 - 50 of 137
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