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  • 1.
    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: 2017 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 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.

  • 2. 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.

  • 3.
    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.

  • 4.
    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)
  • 5. 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.

  • 6. 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.

  • 7. 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.

  • 8.
    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.

  • 9. 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.

  • 10. 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.

  • 11. 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)
  • 12.
    Jalden, Joakim
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Skoglund, Mikael
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, 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.

  • 13.
    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.

  • 14.
    Jaldén, Joakim
    KTH, Superseded Departments, 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.

  • 15.
    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.

  • 16.
    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.

  • 17.
    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.

  • 18.
    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.

  • 19.
    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.

  • 20.
    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.

  • 21.
    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.

  • 22.
    Jaldén, Joakim
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Martin, Cristoff
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, 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.

  • 23.
    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)
  • 24. 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.

  • 25.
    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.

  • 26.
    Jaldén, Joakim
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, 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.

  • 27.
    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.

  • 28.
    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)
  • 29.
    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.

  • 30.
    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.

  • 31.
    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.

  • 32.
    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

  • 33.
    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.

  • 34.
    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.

  • 35.
    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.

  • 36.
    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)
  • 37. Larsson, Erik G.
    et al.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Fixed-complexity soft MIMO detection via partial marginalization2008In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, no 8, p. 3397-3407Article in journal (Refereed)
  • 38.
    Larsson, Erik G.
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Soft MIMO detection at fixed complexity2007In: GLOBECOM 2007: 2007 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, 2007, p. 1617-1621Conference paper (Refereed)
    Abstract [en]

    This paper presents a new approach to soft demodulation for MIMO channels. The proposed method is an approximation to the exact a posteriori probability-per-bit computer. The main idea is to marginalize the posterior density for the received data exactly over the subset of the transmitted bits that are received with the lowest signal-to-noise-ratio, and then marginalize this density approximately over the remaining bits. Unlike the exact demodulator, whose complexity is huge due to the need for enumerating all possible combinations of transmitted constellation points, the proposed method has very low complexity. Additionally, its complexity is fixed, which makes it suitable for pipelined implementation. Numerical examples illustrate its performance on slow fading 4 x 4 and 6 x 6 complex MIMO channels.

  • 39.
    Li, Zuxing
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Oechtering, Tobias
    KTH, School of Electrical Engineering (EES), Communication Theory. 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.
    Parallel Distributed Neyman-Pearson Detection with Privacy Constraints2014In: Proceedings of the IEEE International Conference on Communications (ICC) 2014 Workshop, 2014, p. 765-770Conference paper (Refereed)
    Abstract [en]

    In this paper, the privacy problem of a parallel distributed detection system vulnerable to an eavesdropper is proposed and studied in the Neyman-Pearson formulation. The privacy leakage is evaluated by a metric related to the Neyman-Pearson criterion. We will show that it is sufficient to consider a deterministic likelihood-ratio test for the optimal detection strategy at the eavesdropped sensor. This fundamental insight helps to simplify the problem to find the optimal privacy-constrained distributed detection system design. The trade-off between the detection performance and privacy leakage is illustrated in a numerical example.

  • 40. Ma, Wing-Kin
    et al.
    Su, Chao-Cheng
    Jalden, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Chi, Chong-Yung
    Some results on 16-QAM MIMO detection using semidefinite relaxation2008In: 2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, 2008, p. 2673-2676Conference paper (Refereed)
    Abstract [en]

    Semidefinite relaxation (SDR) is a high-performance efficient approach to MIMO detection especially for the BPSK or QPSK constellations. Recently, a number of research endeavors have focused on extending SDR to the case of 16-QAM constellations. This paper reports two interesting and useful results on this problem. First, we show that two of the existing 16-QAM SDR receivers, namely the polynomial-inspired SDR (PI-SDR) and bound-constrained SDR (BC-SDR) methods, are equivalent. Second, we develop a specialized interior-point algorithm for the implementation of BC-SDR. The proposed algorithm is computationally efficient exploiting the BC-SDR structures, and enables us to handle larger problem sizes in practice.

  • 41. Ma, Wing-Kin
    et al.
    Su, Chao-Cheng
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Chang, Tsung-Hui
    Chi, Chong-Yung
    The Equivalence of Semidefinite Relaxation MIMO Detectors for Higher-Order QAM2009In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, Vol. 3, no 6, p. 1038-1052Article in journal (Refereed)
    Abstract [en]

    In multi-input multi-output (MIMO) detection, semidefinite relaxation (SDR) has been shown to be an efficient high-performance approach. For BPSK and QPSK, it has been found that SDR can provide near-optimal bit error probability performance. This has stimulated a number of recent research endeavors that aim to apply SDR to the high-order QAM cases. These independently developed SDRs are different in concept, structure and complexity, and presently no serious analysis has been given to compare these methods. This paper analyzes the relationship of three such SDR methods, namely the polynomial-inspired SDR (PI-SDR) by Wiesel et al., the bound-constrained SDR (BC-SDR) by Sidiropoulos and Luo, and the virtually-antipodal SDR (VA-SDR) by Mao et al. Rather unexpectedly, we prove that the three SDRs are equivalent in the following sense: The three SDRs yield the same optimal objective values, and their optimal solutions have strong correspondences. Specifically, we establish this solution equivalence between BC-SDR and VA-SDR for any 4(q)-QAM constellations, and that between BC-SDR and PI-SDR for 16-QAM and 64-QAM. Moreover, the equivalence result holds for any channel, problem size, and signal-to-noise ratio. Our theoretical findings are confirmed by simulations, where the three SDRs offer identical symbol error probabilities. Additional simulation results are also provided to demonstrate the effectiveness of SDR compared to some other MIMO detectors, in terms of complexity and symbol error performance.

  • 42.
    Magnusson, Klas E. G.
    et al.
    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.
    A batch algorithm using iterative application of the Viterbi algorithm to track cells and construct cell lineages2012In: Proceedings - International Symposium on Biomedical Imaging, Institute of Electrical and Electronics Engineers , 2012, p. 382-385Conference paper (Refereed)
    Abstract [en]

    Advances in microscope hardware in the last couple of decades have made it possible to acquire large data sets with image sequences of living cells grown in cell culture. This has led to a demand for automated ways of analyzing the acquired images. This article presents a new algorithm for tracking cells and constructing cell lineages in such image sequences. The algorithm uses information from the entire sequence to make local decisions about cell tracks and can therefore make more robust decisions than algorithms that process the data sequentially. It also incorporates image-based likelihoods of cell division and cell death into the tracking, without having to resort to separate detection algorithms or post processing of tracks. The algorithm consists of a scoring function to rank tracks and an iterative algorithm that searches for the highest scoring tracks, in a computationally efficient way, using the Viterbi algorithm.

  • 43.
    Magnusson, Klas E. G.
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Gilbert, Penney M.
    Blau, Helen M.
    Global linking of cell tracks using the Viterbi algorithm2015In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 34, no 4, p. 911-929Article in journal (Refereed)
    Abstract [en]

    Automated tracking of living cells in microscopy image sequences is an important and challenging problem. With this application in mind, we propose a global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. The algorithm adds tracks to the image sequence one at a time, in a way which uses information from the complete image sequence in every linking decision. This is achieved by finding the tracks which give the largest possible increases to a probabilistically motivated scoring function, using the Viterbi algorithm. We also present a novel way to alter previously created tracks when new tracks are created, thus mitigating the effects of error propagation. The algorithm can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells. The algorithm performance is demonstrated on two challenging datasets acquired using bright-field microscopy, but in principle, the algorithm can be used with any cell type and any imaging technique, presuming there is a suitable segmentation algorithm.

  • 44.
    Magnusson, Klas
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Tracking of non-brownian particles using the Viterbi algorithm2015In: Proceedings - International Symposium on Biomedical Imaging, IEEE conference proceedings, 2015, p. 380-384Conference paper (Refereed)
    Abstract [en]

    We present a global tracking algorithm for tracking particles with dynamic motion models. The tracking algorithm augments a existing global track linking algorithm based on the Viterbi algorithm with a Gaussian Mixture Probability Hypothesis Density filter. This allows the tracking algorithm to use the target velocities to link tracks. The algorithm can handle clutter, missed detections, and random appearance and disappearance of particles in the field of view. The algorithm can also handle targets that switch between different motion models according to a Markov process. The algorithm is evaluated on the synthetic datasets used in the ISBI 2012 Particle Tracking Challenge, which simulate vesicles, receptors, microtubules, and viruses at different particle densities and signal to noise ratios. The evaluation shows that our algorithm performs well across a wide range of particle tracking problems in both 2D and 3D.

  • 45.
    Maros, Marie
    et al.
    KTH, School of Electrical Engineering (EES), Information Science and Engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    ADMM for Distributed Dynamic Beam-forming2017In: IEEE Transactions on Signal and Information Processing over Networks, ISSN 2373-776XArticle in journal (Refereed)
    Abstract [en]

    This paper shows the capability of the alternating direction method of multipliers (ADMM) to track, in a distributed manner, the optimal down-link beam-forming solution in a multiple input single output (MISO) multi-cell network given a dynamic channel. Each time the channel changes, ADMM is allowed to perform one algorithm iteration. In order to implement the proposed scheme, the base stations are not required to exchange channel state information (CSI). They will however be required to exchange interference values once.We show ADMM’s tracking ability in terms of the algorithm’s Lyapunov function. This is shown given that the primal and dual solutions to the convex optimization problem at hand can be understood as a continuous mapping from the problem’s parameters. We show that this holds true even considering that the problem loses strong convexity when it is made distributed. We then show that these requirements hold for the down-link, and consequently the uplink, beam-forming case. Numerical examples corroborating the theoretical findings are also provided.

  • 46. Maska, Martin
    et al.
    Ulman, Vladimir
    Svoboda, David
    Matula, Pavel
    Matula, Petr
    Ederra, Cristina
    Urbiola, Ainhoa
    Espana, Tomas
    Venkatesan, Subramanian
    Balak, Deepak M. W.
    Karas, Pavel
    Bolckova, Tereza
    Streitova, Marketa
    Carthel, Craig
    Coraluppi, Stefano
    Harder, Nathalie
    Rohr, Karl
    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.
    Dzyubachyk, Oleh
    Krizek, Pavel
    Hagen, Guy M.
    Pastor-Escuredo, David
    Jimenez-Carretero, Daniel
    Ledesma-Carbayo, Maria J.
    Munoz-Barrutia, Arrate
    Meijering, Erik
    Kozubek, Michal
    Ortiz-de-Solorzano, Carlos
    A benchmark for comparison of cell tracking algorithms2014In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 30, no 11, p. 1609-1617Article in journal (Refereed)
    Abstract [en]

    Motivation: Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. Results: The main contributions of the challenge include the creation of a comprehensive video dataset repository and the definition of objective measures for comparison and ranking of the algorithms. With this benchmark, six algorithms covering a variety of segmentation and tracking paradigms have been compared and ranked based on their performance on both synthetic and real datasets. Given the diversity of the datasets, we do not declare a single winner of the challenge. Instead, we present and discuss the results for each individual dataset separately.

  • 47. Maurer, Johannes
    et al.
    Jaldén, Joakim
    Matz, Gerald
    Multi-threshold top - Full-diversity vector perturbation precodingwith finite-rate feedforward2008In: 2008 42ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, 2008, p. 428-432Conference paper (Refereed)
    Abstract [en]

    We consider vector perturbation (VP) precoding for a multiple antenna broadcast scenario with Multiple noncooperative users. Under an instantaneous transmit power constraint, VP precoding requires the feedforward of a power normalization factor to the users. Simple quantization of the power normalization factor is shown to result in an error floor. To overcome this problem, we propose a new precoding scheme that uses a finite set of power normalization factors and avoids transmission at all when the available power is not sufficient to perform channel equalization at the transmit side. With this scheme, full diversity can be achieved (even with imperfect channel state information) while simultaneously significant amounts of transmit power can be saved.

  • 48. Maurer, Johannes
    et al.
    Jaldén, Joakim
    Matz, Gerald
    Transmit outage precoding with imperfect channel state information under an instantaneous power constraint2008In: 2008 IEEE 9TH WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, VOLS 1 AND 2, NEW YORK: IEEE , 2008, p. 66-70Conference paper (Refereed)
    Abstract [en]

    In this paper, we consider a multiple antenna broadcast scenario with multiple non-cooperative users under the assumption of imperfect channel state information. Under an instantaneous transmit power constraint, vector perturbation precoding requires that the users be continuously informed about the adaptive power scaling factor used at the transmit side. To overcome this limitation, we propose a new precoding scheme that uses a fixed power scaling and avoids transmitting when the available power is not sufficient to perform channel equalization at the transmit side, an event referred to as outage. We present a performance analysis and optimization of this scheme and provide numerical comparisons with classical vector perturbation.

  • 49.
    Maurer, Johannes
    et al.
    Technical University of Vienna.
    Jaldén, Joakim
    Technical University of Vienna.
    Seethaler, Dominik
    Communication Technology Lab, Zurich.
    Matz, Gerald
    Technical University of Vienna.
    Achieving a Continuous Diversity-Complexity Tradeoff in Wireless MIMO Systems via Pre-Equalized Sphere-Decoding2009In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 3, no 6, p. 986-999Article in journal (Refereed)
  • 50. Maurer, Johannes
    et al.
    Jaldén, Joakim
    nstitute of Communications and Radio-Frequency Engineering, Vienna University of Technology, Austria .
    Seethaler, Dominik
    Matz, Gerald
    Vector perturbation precoding for receivers with limited dynamic range2009In: 2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2009, p. 2709-2712Conference paper (Refereed)
    Abstract [en]

    In this paper we consider the vector perturbation (VP) precoding scheme for the multiuser MISO broadcast channel proposed by Hochwald et al. under the practical assumption that the receivers have limited dynamic range. In this case, VP precoding is shown to suffer from an error floor at high signal-to-noise ratio (SNR). As an alternative, we propose precoding with restricted VP (RVP), which takes the limited dynamic range of the receivers explicitly into account by restricting to a finite set of possible perturbation vectors at the transmitter side. We derive the diversity order of this RVP scheme and show that no error floor occurs and that the performance is superior to VP for the entire range of SNRs.

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