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  • 1.
    Ahlén, A
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Lindbom, L
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, M
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Analysis of stability and performance of adaptation algorithms with time-invariant gains2004In: IEEE Transactions on Signal Processing, Vol. 52, p. 103-116Article in journal (Refereed)
  • 2.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Solbrand, Göte
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Numerisk lösning av ett optimalstyrproblem med evolutionsmetoden1982Report (Other scientific)
  • 3.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Adaptive deconvolution based on spectral decomposition1991Report (Other scientific)
  • 4.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Derivation and design of Wiener filters using polynomial equations1994In: Control and Dynamic Systems: Digital Signal Processing Techniques and Applications, Adacemic Press, New York , 1994Chapter in book (Refereed)
  • 5.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Optimal filtering problems1992In: Polynomial methods in optimal control and filtering, Peter Peregrinus, London , 1992Chapter in book (Refereed)
  • 6.
    Ahlén, Anders
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Optimal input estimation: A polynomial approach1985Report (Other scientific)
  • 7.
    Alfredsson, S
    et al.
    KAU.
    Brunström, A
    KAU.
    Sternad, M
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    A 4G link level emulator for transport protocol evaluation2004Conference paper (Refereed)
  • 8. Alfredsson, Stefan
    et al.
    Brunström, Anna
    Karlstad universitet.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group. Signals and systems.
    Analysis of a 4G system performance from a link- and transport layer perspective2007Conference paper (Refereed)
  • 9. Alfredsson, Stefan
    et al.
    Brunström, Anna
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Emulation and validation of a 4G system proposal2005In: Radiovetenskap och Kommunikation, 2005Conference paper (Refereed)
  • 10.
    Alfredsson, Stefan
    et al.
    Karlstad universitet.
    Brunström, Anna
    Karlstad universitet.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Impact of 4G wireless link configurations on VoIP network performance2008In: IEEE International Symposium on Wireless Communication Systems 2008, ISWCS2008, Reykjavik, Iceland, 2008Conference paper (Refereed)
  • 11. Alfredsson, Stefan
    et al.
    Brunström, Anna
    Karlstad universitet.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Transport protocol performance over 4G links: Emulator methodology and results2006Conference paper (Refereed)
  • 12.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Design and measurement based evaluation of coherent JT CoMP: A study of precoding, user grouping and resource allocation using predicted CSI2014In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, Vol. 100Article in journal (Refereed)
  • 13.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Design and measurement based evaluations of coherent JT CoMP: a study of precoding, user grouping and resource allocation using predicted CSI2014In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, p. 100-Article in journal (Other academic)
    Abstract [en]

    Coordinated multipoint (CoMP) transmission provides high theoretic gains in spectral efficiency with coherent joint transmission (JT) to multiple users. However, this requires accurate channel state information at the transmitter (CSIT) and also user groups with spatially compatible users. The aim of this paper is to use measured channels to investigate if significant CoMP gains can still be obtained with channel estimation errors. This turns out to be the case, but requires the combination of several techniques. We here focus on coherent downlink JT CoMP to multiple users within a cluster of cooperating base stations. The use of Kalman predictors is investigated to estimate the complex channel gains at the moment of transmission. It is shown that this can provide sufficient CSIT quality for JT CoMP even for long (> 20 ms) system delays at 2.66 GHz at pedestrian velocities or, for lower delays, at 500 MHz, at vehicular velocities. A user grouping and resource allocation scheme that provides appropriate groups for CoMP is also suggested. It provides performance close to that obtained by exhaustive search at very low complexity, low feedback cost and very low backhaul cost. Finally, a robust linear precoder that takes channel uncertainties into account when designing the precoding matrix is considered. We show that, in challenging scenarios, this provides large gains compared with zero-forcing precoding. Evaluations of these design elements are based on measured channels with realistic noise and intercluster interference assumptions. These show that high JT CoMP gains can be expected, on average over large sets of user positions, when the above techniques are combined - especially in severely intracluster interference limited scenarios.

  • 14.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Robust linear precoder for coordinated multipoint joint transmission under limited backhaul with imperfect CSI2014In: 2014 11TH INTERNATIONAL SYMPOSIUM ON WIRELESS COMMUNICATIONS SYSTEMS (ISWCS), 2014, p. 138-143Conference paper (Refereed)
    Abstract [en]

    Coordinated Multipoint (COMP) transmission provides high theoretic gains in spectral efficiency, in particular with coherent linear Joint Transmission (JT) to multiple users. However, this requires high backhaul capacity. If the backhaul requirement cannot be met by the system, then CoNIP gains decrease as the linear precoder matrix must be adjusted to include zeros. To minimize the loss of CoMP gains, all elements in the precoder should be adjusted as zeros are added to the precoder. We here propose a low complexity method for adjusting a precoder matrix when some elements are required to be zero, with respect to a robust MSE criterion. This is done by introducing penalties on specific precoder matrix elements. This generalized MSE criterion can then be used as a low complexity tool for optimizing e.g. with respect to sum-rate. Results show that this does indeed provide a better solution than if zeros are added separately. It is especially beneficial for cell edge users, i.e. for the same users that can gain the most from JT CoNIP.

  • 15.
    Apelfröjd, Rikke
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Aronsson, Daniel
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Measurement-based evaluation of robust linear precoding for downlink CoMP2012In: IEEE International Conference on Communications, ICC, Ottawa, Canada, 2012Conference paper (Refereed)
    Abstract [en]

    We study the design and evaluation of joint processing coordinated multipoint (CoMP) downlink transmission. Precoders will then be designed based on outdated channel state information (CSI), so interference cannot be eliminated completely as by an ideal zero-forcing (ZF) solution. We here strive to design and evaluate realistic linear transmit schemes. Kalman predictors are used for orthogonal frequency-division multiplexing (OFDM) channels. They provide optimal linear predictions and also estimates of their uncertainty. Robust linear precoders are designed based on these uncertainty estimates. We introduce and use robust linear quadratic optimal feedforward control, with the criterion averaged (marginalized) over the CSI uncertainty. This flexible solution performs minimum mean square error (MSE) minimization. It can also iteratively optimize other criteria, such as sum-rate. The prediction- and transmission performance is evaluated using measured data on 20 MHz OFDM downlinks from three base stations, for users at fast pedestrian velocities. Downlink CoMP is here also compared to cellular transmission, that uses orthogonal resources within cells but allows uncontrolled interference between cells.

  • 16.
    Aronsson, Daniel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Kalman predictor design for frequency-adaptive scheduling of FDD OFDMA uplinks2007Conference paper (Refereed)
  • 17.
    Aronsson, Daniel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    OFDMA uplink channel prediction to enable frequency-adaptive multiuser scheduling2007Conference paper (Refereed)
  • 18.
    Aronsson, Daniel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Svensson, Tommy
    Chalmers University of Technology, Dept of Signals and Systems.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Performance evaluation of memory-less and Kalman-based channel estimation for OFDMA2009In: IEEE Vehicular Technology Conference, Barcelona, Spanien, April 26-29, 2009, 2009, p. 2314-2318Conference paper (Refereed)
    Abstract [en]

    The next generation wireless systems based on Orthogonal Frequency Division Multiple Access (OFDMA) need to operate in widely different deployment and usage scenarios. Thus, support for flexible resource allocation is important. In this paper we investigate the performance or different memory-less and memory-based channel estimators for different OFDMA subcarrier allocation schemes and different pilot patterns. We evaluate the performance in various fading environments and for different user terminal velocities. The results show that channel estimation can perform well enough for time-frequency localized resources as small as 22 channel symbols with two pilots in many important scenarios. The results provided can be used to identify appropriate subcarrier allocations for the next generation OFDMA based wireless systems.

  • 19.
    Barkefors, Annea
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Berthilsson, Simon
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    An investigation of a theoretical tool for predicting performance of an active noise control system.2012In: 19th International Congress on Sound and Vibration, ICSV19, Vilnius, Lithuania, 2012, p. 1-8Conference paper (Refereed)
  • 20.
    Barkefors, Annea
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Berthilsson, Simon
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Extending the area silenced by active noise control using multiple loudspeakers2012In: Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference, 2012, p. 325-328Conference paper (Refereed)
    Abstract [en]

    Active noise control is of increasing interest in e.g. cars, but the zone of noise damping becomes limited in reverberant environments. We investigate the possibility of extending this spatial zone significantly, by using multiple control loudspeakers. MIMO feedforward controllers designed by linear quadratic control theory are here shown to increase the limiting frequency for uniform damping in a 0.3×0.3 m test area, from 200 Hz to around 600 Hz.

  • 21.
    Barkefors, Annea
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Adapting an MSE controller for active noise control to nonstationary noise statistics2014Conference paper (Refereed)
  • 22.
    Barkefors, Annea
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Brännmark, Lars-Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Design and Analysis of Linear Quadratic Gaussian Feedforward Controllers for Active Noise Control2014In: IEEE Transactions on Audio, Speech, and Language Processing, ISSN 1558-7916, E-ISSN 1558-7924, Vol. 22, no 12, p. 1777-1791Article in journal (Refereed)
    Abstract [en]

    A method for sound field control applied to active noise control is presented and evaluated. The method uses Linear Quadratic Gaussian (LQG) feedforward control to find a Minimal Mean Square Error (MMSE)-optimal linear sound field controller under a causality constraint. It is obtained by solving a polynomial matrix spectral factorization and a linear (Diophantine) polynomial matrix equation. An important component in the design is the control signal penalty term of the criterion. Its use and influence is here discussed and evaluated using measured room impulse responses. The results indicate that the use of a relatively simple, frequency-weighted penalty on individual control signals provides most of the benefits obtainable by the considered more advanced alternative. We also introduce and illustrate several tools for performance analysis. An analytical expression for the attainable performance clearly reveals the performance loss generated by having to use a causal controller instead of the ideal noncausal controller. This loss is largest at low frequencies. Furthermore, we introduce a measure of the reproducibility of the target noise sound field with given control loudspeaker setups and room transfer functions. It describes how well a controller that uses an input subspace of dimension equal to the effective rank of the system is able to reproduce a target sound field. This performance measure can e.g. be used to support the selection of good combinations of placements of control loudspeakers.

  • 23.
    Berthilsson, Simon
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Barkefors, Annea
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Brännmark, Lars-Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Acoustical zone reproduction for car interiors using a MIMO MSE framework.2012In: AES 48th International Conference, Munich, Germany, 2012Conference paper (Refereed)
  • 24.
    Berthilsson, Simon
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Barkefors, Annea
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    MIMO design of active noise controllers for car interiors: Extending the silenced region at higher frequencies2012In: 2012 American Control Conference, Montréal, Canada, 2012, p. 6140-6147Conference paper (Refereed)
  • 25.
    Berthilsson, Simon
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Acoustic zones for aircraft seat rows2013Conference paper (Refereed)
  • 26.
    Björsell, Joachim
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Grieger, Michael
    AIRRAYS Wireless Solut Dresden, Dresden, Germany.
    Predictor antennas in action2017In: 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), IEEE, 2017Conference paper (Refereed)
    Abstract [en]

    Connected vehicles in large numbers will be expensive in terms of power and bandwidth unless advanced transmit schemes are employed. These would rely on channel state information at transmitter (CSIT), which rapidly becomes outdated for fading vehicular channels. We here evaluate the predictor antenna concept, that solves this problem by using antennas on the outside of vehicles, with one extra antenna in front of the others. Its estimated channel is a scaled prediction for the channels encountered by rearward antennas when they reach that position. We evaluate this concept on a large set of channel sounding measurements from an urban environment. Recent investigations of the correlations of these measurements indicate that the average normalized mean squared errors (NMSEs) of the complex valued channel predictions should be around -10 dB for prediction horizons in space of up to 3 wavelengths. This represents an extension of the attainable prediction horizon by an order of magnitude, as compared to Kalman or Wiener extrapolation of past channel measurements. It represents an accuracy that would enable e.g. accurate massive multiple input multiple output (MIMO) downlink beamforming to vehicles. We here perform predictions on a subset of the measurements with good channel-to-estimation error power ratio (SNR). The approximate true channels are here available and we evaluate the performance on a validation data set. The results confirm that the distribution of the NMSE, over all investigated propagation environments, is close to that obtained by correlation-based models and outperforms the use of outdated channel measurements.

  • 27.
    Brännmark, Lars-Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Controlling the impulse responses and the spatial variability in digital loudspeaker-room correction2015Conference paper (Refereed)
  • 28. Döttling, M
    et al.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Klang, G
    von Häfen, J
    Olsson, M
    Integration of spatial processing in the WINNER B3G air interface design2006Conference paper (Refereed)
  • 29.
    Döttling, Martin
    et al.
    Nokia-Siemens Networks.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Nyström, Johan
    Ericsson AB.
    Johansson, Niklas
    Ericsson AB.
    von Häfen, Jörn
    Nokia-Siemens Networks.
    Chapter 4: System Concept and Architecture2009In: Radio Technologies and Concepts for IMT-Advanced / [ed] M Döttling, A Osseiran and W Mohr, John Wiley & Sons , 2009Chapter in book (Other academic)
  • 30.
    Falahati, S
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Svensson, A
    Chalmers.
    Sternad, M
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Ekman, T
    Oslo, Norge.
    Adaptive modulation system for predicted wireless channels2004In: IEEE Transactions on Communications, Vol. 52, p. 307-316Article in journal (Refereed)
  • 31.
    Gustafsson, Leif
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    A guide to population modelling for simulation2015In: Open Journal of Modelling and SimulationArticle in journal (Refereed)
  • 32.
    Gustafsson, Leif
    et al.
    SLU.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signal Processing.
    Bringing consistency to simulation of population models - Poisson simulation as a bridge between micro and macro simulation2007In: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 209, no 2, p. 361-385Article in journal (Refereed)
    Abstract [en]

    Population models concern collections of discrete entities such as atoms, cells, humans, animals, etc., where the focus is on the number of entities in a population. Because of the complexity of such models, simulation is usually needed to reproduce their complete dynamic and stochastic behaviour. Two main types of simulation models are used for different purposes, namely micro-simulation models, where each individual is described with its particular attributes and behaviour, and macro-simulation models based on stochastic differential equations, where the population is described in aggregated terms by the number of individuals in different states. Consistency between micro- and macro-models is a crucial but often neglected aspect. This paper demonstrates how the Poisson Simulation technique can be used to produce a population macro-model consistent with the corresponding micro-model. This is accomplished by defining Poisson Simulation in strictly mathematical terms as a series of Poisson processes that generate sequences of Poisson distributions with dynamically varying parameters. The method can be applied to any population model. It provides the unique stochastic and dynamic macro-model consistent with a correct micro-model. The paper also presents a general macro form for stochastic and dynamic population models. In an appendix Poisson Simulation is compared with Markov Simulation showing a number of advantages. Especially aggregation into state variables and aggregation of many events per time-step makes Poisson Simulation orders of magnitude faster than Markov Simulation. Furthermore, you can build and execute much larger and more complicated models with Poisson Simulation than is possible with the Markov approach.

  • 33.
    Gustafsson, Leif
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Consistent micro, macro and state-based population modelling2010In: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 225, no 2, p. 94-107Article in journal (Refereed)
    Abstract [en]

    A population system can be modelled using a micro model focusing on the individual entities, a macro model where the entities are aggregated into compartments, or a state-based model where each possible discrete state in which the system can exist is represented. However, the concepts, building blocks, procedural mechanisms and the time handling for these approaches are very different. For the results and conclusions from studies based on micro, macro and state-based models to be consistent (contradiction-free), a number of modelling issues must be understood and appropriate modelling procedures be applied. This paper presents a uniform approach to micro, macro and state-based population modelling so that these different types of models produce consistent results and conclusions. In particular, we demonstrate the procedures (distribution, attribute and combinatorial expansions) necessary to keep these three types of models consistent. We also show that the different time handling methods usually used in micro, macro and state-based models can be regarded as different integration methods that can be applied to any of these modelling categories. The result is free choice in selecting the modelling approach and the time handling method most appropriate for the study without distorting the results and conclusions.

  • 34.
    Gustafsson, Leif
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    When can a deterministic model of a population system reveal what will happen on average?2013In: Mathematical Biosciences, ISSN 0025-5564, E-ISSN 1879-3134, Vol. 243, no 1, p. 28-45Article in journal (Refereed)
    Abstract [en]

    A dynamic population system is often modelled by a deterministic difference equation model to obtain average estimates. However, there is a risk of the results being distorted because unexplained (random) variations are left out and because entities in the population are described by continuous quantities of an infinitely divisible population so that irregularly occurring events are described by smooth flows. These distortions have many aspects that cannot be understood by only regarding a deterministic approach. However, the reasons why a deterministic model may behave differently and produce biased results become visible when the deterministic model is compared with a stochastic model of the same structure. This paper focuses first on demographic stochasticity, i.e. stochasticity that refers to random variations in the occurrence of events affecting the state of an individual, and investigates the consequences of omitting this by deterministic modelling. These investigations reveal that bias may be strongly influenced by the type of question to be answered and by the stopping criterion ending the analysis or simulation run. Two cases are identified where deterministic models produce unbiased state variables: (1) Dynamic systems with stable local linear dynamics produce unbiased state variables asymptotically, in the limit of large flows; and (2) linear dynamic systems produce unbiased state variables as long as all state variables remain non-negative in both the deterministic and the stochastic models. Both cases also require the question under study to be compatible with a solution over a fixed time interval. Stochastic variability of initial values between simulation runs because of uncertainty or lack of information about the initial situation is denoted initial value stochasticity. Elimination of initial value stochasticity causes bias unless the model is linear. It may also considerably enlarge bias from other sources. Unknown or unexplained variations from the environment (i.e. from outside the borders of the studied system) enter the model in the form of stochastic parameters. The omission of this environmental stochasticity almost always creates biased state variables. Finally, even when a deterministic model produces unbiased state variables, the results will be biased if the output functions are not linear functions of the state variables.

  • 35. Hooli, K
    et al.
    Lara, J
    Pfeltschinger, S
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Thilakawardana, S
    RRM architecture for spectrum sharing in B3G systems2005In: 15th Wireless World Research Forum (WWRF) Meeting, WG1, 2005Conference paper (Refereed)
  • 36.
    Jamaly, Nima
    et al.
    Inst för signaler och system, CTH, Göteborg.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Martinez, Ana Belén
    Tech Univ Dresden, Vodafone Chair Mobile Commun Syst, Dresden, Germany.
    Grieger, Michael
    TU Dresden.
    Svensson, Tommy
    Inst för signaler och system, CTH, Göteborg.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Fettweis, Gerhard
    TU Dresden.
    Analysis and Measurement of Multiple Antenna Systems for Fading Channel Prediction in Moving Relays2014In: 2014 8TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 2014, p. 2015-2019Conference paper (Other academic)
    Abstract [en]

    The performance of wireless data transmission to mobile vehicles is improved if channel state information is available at the transmitter but movement of vehicles causes outdating of channel estimates. The concept of a predictor antenna has recently been proposed, where an antenna is placed in front of other antennas on the roof of the vehicle to sense the radio environment in advance. This can comparatively provide an order-of-magnitude improvement in channel prediction performance. A potential problem with this idea is that closely placed antennas will experience mutual electromagnetic couplings. These may reduce the efficiency of the predictor antenna concept if they are not taken into account. In this paper, we discuss about how to treat the forgoing issue and eventually evaluate a promising candidate on measured channels. We argue that only open-circuit voltage method would be realistic for the present application. The usefulness of the proposed decoupling method is demonstrated on field measurements obtained in downtown Dresden, Germany. We also partly address the sensitivity of the open-circuit decoupling method to the accuracy of the utilized network parameters.

  • 37.
    Javaudin, Jean-Philippe
    et al.
    Orange France Telecom.
    Mange, Geneviève
    Alcatel-Lucent Bell Laboratories.
    Svensson, Tommy
    Chalmers University of Technology, Dept of Signals and Systems.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Chapter 9: Multiple Access Schemes and Inter-Cell Interference Mitigation Techniques2009In: Radio Technologies and Concepts for IMT-Advanced / [ed] M Döttling, A Osseiran and W Mohr, John Wiley & Sons , 2009Chapter in book (Other (popular science, discussion, etc.))
  • 38.
    Johansson, Mathias
    et al.
    Dirac Research AB, Uppsala.
    Brännmark, Lars-Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Bahne, Adrian
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sound field control using a limited number of loudspeakers2009In: 36th Audio Engineering Society International Conference 2009: Automotive Audio - Sound in Motion, Dearborn, Michigan, Red Hook, NY: Audio-Engineering Society , 2009Conference paper (Refereed)
  • 39.
    Johansson, Mathias
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Resource allocation under uncertainty using the maximum entropy principle2005In: IEEE Transaction on Information Theory, Vol. 51, p. 4103-4117Article in journal (Refereed)
  • 40. Jungnickel, Volker
    et al.
    Manolakis, Konstantinos
    Zirwas, Wolfgang
    Panzner, Berthold
    Braun, Volker
    Lossow, Moritz
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Svensson, Tommy
    Inst för signaler och system, CTH, Göteborg.
    The role of small cells, coordinated multi-point and massive MIMO in 5G2014In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 52, no 5, p. 44-51Article in journal (Refereed)
    Abstract [en]

    5G will have to support a multitude of new applications with a wide variety of requirements, including higher peak and user data rates, reduced latency, enhanced indoor coverage, increased number of devices, and so on. The expected traffic growth in 10 or more years from now can be satisfied by the combined use of more spectrum, higher spectral efficiency, and densification of cells. The focus of the present article is on advanced techniques for higher spectral efficiency and improved coverage for cell edge users. We propose a smart combination of small cells, joint transmission coordinated multipoint (JT CoMP), and massive MIMO to enhance the spectral efficiency with affordable complexity. We review recent achievements in the transition from theoretical to practical concepts and note future research directions. We show in measurements with macro-plus-small-cell scenarios that spectral efficiency can be improved by flexible clustering and efficient user selection, and that adaptive feedback compression is beneficial to reduce the overhead significantly. Moreover, we show in measurements that fast feedback reporting combined with advanced channel prediction are able to mitigate the impairment effects of JT CoMP.

  • 41.
    Klockar, Annika
    et al.
    Computer Science, Karlstad University, Karlstad.
    Botella, Carmen
    IRTIC, Universitat de Valencia, Spanien.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Brunström, Anna
    Computer Science, Karlstad University, Karlstad.
    Svensson, Tommy
    Signals and Systems, CTH, Göteborg.
    Utility as a user selection criterion for coordinated multi-point systems2013Conference paper (Refereed)
  • 42.
    Klockar, Annika
    et al.
    Computer Science, Karlstad University, Karlstad.
    Botella, Carmen
    Signals and Systems, Chalmers University of Technology, Gothenburg.
    Svensson, Tommy
    Signals and Systems, Chalmers University of Technology, Gothenburg.
    Brunström, Anna
    Computer Science, Karlstad University, Karlstad.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Utility of joint processing schemes2010In: 7th International Symposium on Wireless Communication Systems, ISWCS, York, UK, 2010Conference paper (Refereed)
  • 43.
    Klockar, Annika
    et al.
    Karlstad Univ, Comp Sci, Karlstad, Sweden.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Brunström, Anna
    Karlstad universitet.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    User-centric pre-selection and scheduling for coordinated multipoint systems2014In: 2014 11TH INTERNATIONAL SYMPOSIUM ON WIRELESS COMMUNICATIONS SYSTEMS (ISWCS), 2014, p. 888-894Conference paper (Refereed)
    Abstract [en]

    The data traffic volumes are constantly increasing in cellular networks. Furthermore, a larger part of the traffic is generated by applications that require high data rates. Techniques including Coordinated Multipoint transmission (CoMP) can increase the data rates, but at the cost of a high overhead. The overhead can be reduced if only a subset of the users is served with CoMP. In this paper, we propose a user selection approach, including pre-selection of CoMP users and short term scheduling, that takes user requirements into account. Users that require a high data rate to reach an acceptable level of service satisfaction are selected to use coherent joint processing CoMP in some of their downlink transmission bandwidth. Simulation results show that both the number of satisfied users and fairness are improved with the proposed user selection as compared to user selection that does not consider individual user requirements.

  • 44.
    Li, Jingya
    et al.
    Dept of Signals and Systems, Chalmers Tekniska Universitet, Göteborg.
    Papadogiannis, Agisilaos
    Dept of Signals and Systems, Chalmers Tekniska Universitet, Göteborg.
    Apelfröjd, Rikke
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Svensson, Tommy
    Dept of Signals and Systems, Chalmers Tekniska Universitet, Göteborg.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Performance evaluation of coordinated multi-point transmission schemes with predicted CSI2012In: IEEE Conference on Personal, Indoor and Mobile Radio Communications, PIMRC, Sydney, Australien, 2012, p. 1055-1060Conference paper (Refereed)
    Abstract [en]

    Coordinated multi-point (CoMP) transmission is considered as an efficient technique to improve cell-edge performance as well as system spectrum efficiency. In CoMP-enabled systems, a cluster of coordinated base stations (BSs) are typically assumed to be connected to a control unit (CU) via backhaul links, and the provided performance gain relies heavily on the quality of the channel state information (CSI) available at the CU side. In this paper, we consider the downlink of a CoMP cluster and compare three different CoMP transmission schemes: zero-forcing coherent joint transmission, non-coherent joint transmission and coordinated scheduling. Moreover, for each of the analyzed schemes, the performance in terms of average sum rate of the CoMP cluster is studied with predicted CSI, considering the effects of the feedback and backhaul latency, as well as the user mobility. Compared to zero-forcing coherent joint transmission, we show that non-coherent joint transmission and coordinated scheduling are more robust to channel uncertainty. In addition, depending on the latency, user mobility and user locations, different schemes would achieve the highest average sum rate performance. Hence, a system could switch between the transmission schemes to improve the sum rate.

  • 45.
    Lindbom, Lars
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Sternad, Mikael
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Ahlén, Anders
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Technology, Department of Engineering Sciences, Signal Processing. Signals and systems.
    Adaptation with constant gains: Analysis for slow variations2001In: IEEE International Conference on Acoustics, Speech and Signal Processing, Salt Lake City, UT, 2001Conference paper (Refereed)
  • 46.
    Lindbom, Lars
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Ahlén, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Tracking of time-varying mobile radio channels: Part I: The Wiener LMS algorithm2001In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 49, p. 2207-2217Article in journal (Refereed)
  • 47. Phan-Huy, D. -T
    et al.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Svensson, T.
    Chalmers, Sydney, NSW, Australia.;Nokia Bell Labs, Sydney, NSW, Australia..
    Zirwas, W.
    Villeforceix, B.
    Orange Labs, Sydney, NSW, Australia..
    Karim, F.
    Orange Labs, Sydney, NSW, Australia..
    El-Ayoubi, S. -E
    5G on Board: How Many Antennas Do We Need on Connected Cars?2016In: 2016 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), New York: IEEE, 2016Conference paper (Refereed)
    Abstract [en]

    Mobile networks will support increasing numbers of connected vehicles. Successive generations of mobile networks have reduced the cost of data rate, in terms of spectrum usage and power consumption at the base station, by increasingly exploiting the concept of channel state information at the transmitter. Unfortunately, beyond a limiting velocity (which depends on the carrier frequency), networks are no longer cost efficient, since such information is not usable. Recently, channel prediction techniques requiring several antennas on the car roof have been introduced to solve this problem. In this paper, for the first time, we determine the most cost efficient configurations, in terms of numbers of antennas on the car roof and carrier frequency, in various scenarios (highway and dense urban). Our studies show that with a simple prediction technique based on predictor antennas, the network can use twice less spectrum and around 20 dB less power, for cars with 3 antennas on their tops than for cars with the same number of antennas and not using prediction.

  • 48.
    Phan-Huy, Dinh-Thuy
    et al.
    Orange Labs.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Svensson, Tommy
    Signals and Systems, CTH, Göteborg.
    Adaptive large MISO downlink with predictor antenna array for very fast moving vehicles2013Conference paper (Refereed)
  • 49. Phan-Huy, Dinh-Thuy
    et al.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Svensson, Tommy
    s3, CTH.
    Making 5G Adaptive Antennas Work for Very Fast Moving Vehicles2015In: IEEE Intelligent Transportation Systems Magazine, ISSN 1939-1390, Vol. 7, no 2, p. 71-84Article in journal (Refereed)
    Abstract [en]

    Wireless systems increasingly rely on the accurate knowledge at the transmitter side of the transmitter-to-receiver propagation channel, to optimize the transmission adaptively. Some candidate techniques for 5th generation networks need the channel knowledge for tens of antennas to perform adaptive beamforming from the base station towards the mobile terminal. These techniques reduce the radiated power and the energy consumption of the base station. Unfortunately, they fail to deliver the targeted quality of service to fast moving terminals such as connected vehicles. Indeed, due to the movement of the vehicle during the delay between channel estimation and data transmission, the channel estimate is outdated. In this paper, we propose three new schemes that exploit the "Predictor Antenna" concept. This recent concept is based on the observation that the position occupied by one antenna at the front of the vehicle, will later on be occupied by another antenna at the back. Estimating the channel of the "front" antenna can therefore later help beamforming towards the "back" antenna. Simulations show that our proposed schemes make adaptive beamforming work for vehicles moving at speeds up to 300 km/h.

  • 50. Phan-Huy, D-T
    et al.
    Svensson, Tommy
    Chalmers Tekniska Högskola, Inst för S3, Göteborg.
    Sternad, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
    Zirwas, W
    Villeforceix, B
    Karim, F
    Sayrac, B
    Connected vehicles that use channel prediction will fully take advantage of 5G2015Conference paper (Refereed)
12 1 - 50 of 77
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