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| 2. |
- Soltesz, Kristian, et al.
(författare)
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The effect of interventions on COVID-19
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 588:7839, s. 26-28
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Tidskriftsartikel (refereegranskat)
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| 3. |
- Brandt, Rasmus, 1985-
(författare)
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Coordinated Precoding for Multicell MIMO Networks
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Enabling multiple base stations to utilize the spatial dimension in a coordinated manner has been shown to be a fruitful technique for improving the spectral efficiency in wireless interference networks. This thesis considers multicell systems where base stations and mobile stations are equipped with multiple antennas. The base stations coordinate their spatial precoding, but individually serve their mobile stations with data. For such coordinated precoding systems, interference alignment (IA) is a useful theoretical tool, due to its ability to serve the maximum number of interference-free data streams. Three topics related to interference alignment and coordinated precoding are studied.First, the feasibility of IA over a joint space-frequency signal space is studied. A necessary condition for space-frequency IA feasibility is derived, and the possible gain over space-only IA is analyzed. An upper bound on the degree of freedom gain is shown to increase in the number of subcarriers, but decrease in the number of antennas. Numerical studies, using synthetically generated channels and real-world channels obtained from indoors and outdoors channel measurements, are used for sum rate performance evaluation. The results show that although a degree of freedom gain is noticeable due to the space-frequency precoding, the sum rate of the system is mainly improved due to a power gain.Second, distributed channel state information (CSI) acquisition techniques are proposed, which provide estimates of the information necessary to perform distributed coordinated precoding. The methods are based on pilot-assisted channel estimation in the uplink and downlink, and correspond to different tradeoffs between feedback and signaling, backhaul use, and computational complexity. Naively applying the existing WMMSE algorithm for distributed coordinated precoding together with the estimated CSI however results in poor performance. A robustification of the algorithm is therefore proposed, relying on the well known diagonal loading technique. An inherent property of the WMMSE solutions is derived and, when enforced onto solutions with imperfect CSI, results in diagonally loaded receive filters. Numerical simulations show the effectiveness of the proposed robustification. Further, the proposed robustified and distributed WMMSE algorithm performs well compared to existing state-of-the-art robust WMMSE algorithms. In contrast to our approach, the existing methods however rely on centralized CSI acquisition.Third, coordinated precoding systems with hardware impairments are studied. Assuming that impairment compensation techniques have been applied, a model is used to describe the aggregate effect of the residual hardware impairments. An iterative resource allocation method accounting for the residual hardware impairments is derived, based on an existing resource allocation framework. Numerical simulations show that the proposed method outperforms all benchmarks. In particular, the gain over impairments-aware time-division multiple access is substantial.
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| 4. |
- Brandt, Rasmus, 1985-
(författare)
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Distributed Coordination in Multiantenna Cellular Networks
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Wireless communications are important in our highly connected world. The amount of data being transferred in cellular networks is steadily growing, and consequently more capacity is needed. This thesis considers the problem of downlink capacity improvement from the perspective of multicell coordination. By employing multiple antennas at the transmitters and receivers of a multicell network, the inherent spatial selectivity of the users can be exploited in order to increase the capacity through linear precoding and receive filtering. For the coordination between cells, distributed algorithms are often sought due to their low implementation complexity and robustness. In this context, the thesis considers two problem domains: base station clustering and coordinated precoding.Base station clustering corresponds to grouping the cell base stations into disjoint clusters in order to reduce the coordination overhead. This is needed in intermediate-sized to large networks, where the overhead otherwise would be overwhelmingly high. Two solution methods for the clustering problem are proposed: an optimal centralized method, as well as a heuristic distributed method. The optimal method applies to a family of throughput models and exploits the structure of the model to find bounds that can be used to focus the search for the optimal clustering into promising territories. The distributed method instead uses notions from coalitional game theory, where the base stations are modelled as rational and intelligent players in a game. By letting the players make individual deviations that benefit them in the game, i.e.\@ switching clusters, a distributed coalition formation algorithm is obtained.Coordinated precoding is the act of finding the linear precoders and receive filters that maximize the network performance, given a base station clustering. Four specific challenges are studied in this problem domain. First, coordinated precoding under intercluster interference is considered. The channels of the intercluster links are not explicitly estimated due to overhead reasons, and these links thus lead to intercluster interference. By exploiting the known statistics of the intercluster channels, a robust and distributed coordinated precoding algorithm is developed. Second, coordinated precoding under imperfect channel state information is considered. Relying on the channel reciprocity under time-division duplex operation, a distributed estimation framework is proposed. Given the estimated channels, a robust and distributed coordinated precoding algorithm is then derived. Third, coordinated precoding under imperfect radio hardware is considered. By modelling the radio frequency distortion noises, a distributed coordinated precoding method that accounts for the imperfections is proposed. Fourth, joint coordinated precoding and discrete rate selection is considered. By bounding and linearizing an originally intractable optimization problem, a heuristic algorithm is derived which selects the transmit rate from a finite set and simultaneously forms the linear precoders and receive filters.
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| 5. |
- Carlsson, Håkan, et al.
(författare)
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Inertial Navigation Using an Inertial Sensor Array
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We present a comprehensive framework for fusing measurements from multiple and generally placed accelerometers and gyroscopes to perform inertial navigation. Using the angular acceleration provided by the accelerometer array, we show that the numerical integration of the orientation can be done with second-order accuracy, which is more accurate compared to the traditional first-order accuracy that can be achieved when only using the gyroscopes. Since orientation errors are the most significant error source in inertial navigation, improving the orientation estimation reduces the overall navigation error. The practical performance benefit depends on prior knowledge of the inertial sensor array, and therefore we present four different state-space models using different underlying assumptions regarding the orientation modeling. The models are evaluated using a Lie Group Extended Kalman filter through simulations and real-world experiments. We also show how individual accelerometer biases are unobservable and can be replaced by a six-dimensional bias term whose dimension is fixed and independent of the number of accelerometers.
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| 6. |
- Carlsson, Håkan
(författare)
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Inertial Sensor Arrays : Sensor Fusion and Calibration
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Motion estimation using inertial sensors is today used in a wide range of applications, from aircraft navigation to inflatable bicycle helmets. The accuracy with which the motion can be estimated using inertial sensors depends on how large the measurement errors are. One approach to reducing the inertial sensors' measurement errors is to use more sensors than what is necessary for motion estimation. By averaging the measurements from a redundant amount of sensors, the impact of independent errors can be reduced. But by placing multiple inertial sensors on a rigid body, more information about the motion is available than what can be obtained from simple averaging. For instance, point-wise accelerations of a rigid body contain information on the rotation of the rigid body. This thesis examines and proposes methods for how to fuse the measurements from an inertial sensor array and how systematic measurement errors present in the sensors can be estimated and calibrated.The inertial sensor array contains multiple accelerometers and multiple gyroscopes. In motion estimation applications, it is common to estimate the angular velocity from the gyroscopes measurements and then integrate the angular velocity into an orientation. The angular velocity can also be estimated from multiple accelerometers. This thesis proposes different models for fusing the accelerometer and gyroscope measurements for more accurate orientation estimation. By increasing the accuracy with which the orientation can be estimated, the integrated error in the position and velocity estimates can be decreased.The performance of the fusion algorithms for multiple inertial sensors depends on how large the systematic measurement errors are. The amount of rotational information from multiple accelerometers depends on how well the locations of the accelerometers are known. Other calibration parameters in the inertial sensor array are sensor biases. These calibration parameters are estimated in conventional calibration by exposing the inertial sensors to a known reference motion. However, creating such reference motion requires external equipment that may not be available to the user. Therefore, this thesis proposes methods to jointly estimate the motion and the sensor parameters, thereby omitting the need for external calibration equipment.
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| 7. |
- Carlsson, Håkan, et al.
(författare)
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On-The-Fly Geometric Calibration of Inertial Sensor Arrays
- 2017
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Ingår i: Proceedings 2017 international conference on indoor positioning and indoor navigation (IPIN). - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 8. |
- Carlsson, Håkan, et al.
(författare)
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Quantifying the Uncertainty of the Relative Geometry in Inertial Sensors Arrays
- 2021
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Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 21:17, s. 19362-19373
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Tidskriftsartikel (refereegranskat)abstract
- We present an algorithm to estimate and quantify the uncertainty of the accelerometers' relative geometry in an inertial sensor array. We formulate the calibration problem as a Bayesian estimation problem and propose an algorithm that samples the accelerometer positions' posterior distribution using Markov chain Monte Carlo. By identifying linear substructures of the measurement model, the unknown linear motion parameters are analytically marginalized, and the remaining non-linear motion parameters are numerically marginalized. The numerical marginalization occurs in a low dimensional space where the gyroscopes give information about the motion. This combination of information from gyroscopes and analytical marginalization allows the user to make no assumptions of the motion before the calibration. It thus enables the user to estimate the accelerometer positions' relative geometry by simply exposing the array to arbitrary twisting motion. We show that the calibration algorithm gives good results on both simulated and experimental data, despite sampling a high dimensional space.
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| 9. |
- Carlsson, Håkan, et al.
(författare)
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Self-Calibration of Inertial Sensor Arrays
- 2021
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Ingår i: IEEE Sensors Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 1530-437X .- 1558-1748. ; 21:6, s. 8451-8463
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Tidskriftsartikel (refereegranskat)abstract
- A maximum likelihood estimator is presented for self-calibrating both accelerometers and gyroscopes in an inertial sensor array, including scale factors, misalignments, biases, and sensor positions. By simultaneous estimation of the calibration parameters and the motion dynamics of the array, external equipment is not required for the method. A computational efficient iterative optimization method is proposed where the calibration problem is divided into smaller subproblems. Further, an identifiability analysis of the calibration problem is presented. The analysis shows that it is sufficient to know the magnitude of the local gravity vector and the average scale factor gain of the gyroscopes, and that the array is exposed to two types of motions for the calibration problem to be well defined. The proposed estimator is evaluated by real-world experiments and by Monte Carlo simulations. The results show that the parameters can be consistently estimated and that the calibration significantly improves the accuracy of the motion estimation. This enables on-the-fly calibration of small inertial sensors arrays by simply twisting them by hand.
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| 10. |
- Chenouard, Nicolas, et al.
(författare)
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Objective comparison of particle tracking methods
- 2014
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Ingår i: Nature Methods. - : Springer Science and Business Media LLC. - 1548-7091 .- 1548-7105. ; 11:3, s. 281-U247
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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