Change search
Refine search result
1 - 15 of 15
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Blau, Helen M.
    et al.
    Gilbert, Penney M.
    Havenstrite, Karen
    Lutolf, Matthias P.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Ramunas, John
    Elastic substrates and methods of use in cell manipulation and culture2010Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    Methods are provided for the ex vivo manipulation of cells, stem cells and other reproductive cells, by manipulating the cells in a container or device comprising an elastic substrate, wherein the substrate has an elasticity that mimics the elasticity of a native microenvironment of the cell.

  • 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. Gilbert, P. M.
    et al.
    Havenstrite, K. L.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Sacco, A.
    Leonardi, N. A.
    Kraft, P.
    Nguyen, N. K.
    Thrun, S.
    Lutolf, M. P.
    Blau, H. M.
    Substrate Elasticity Regulates Skeletal Muscle Stem Cell Self-Renewal in Culture2010In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 329, no 5995, p. 1078-1081Article in journal (Refereed)
    Abstract [en]

    Stem cells that naturally reside in adult tissues, such as muscle stem cells (MuSCs), exhibit robust regenerative capacity in vivo that is rapidly lost in culture. Using a bioengineered substrate to recapitulate key biophysical and biochemical niche features in conjunction with a highly automated single-cell tracking algorithm, we show that substrate elasticity is a potent regulator of MuSC fate in culture. Unlike MuSCs on rigid plastic dishes (similar to 10(6) kilopascals), MuSCs cultured on soft hydrogel substrates that mimic the elasticity of muscle (12 kilopascals) self-renew in vitro and contribute extensively to muscle regeneration when subsequently transplanted into mice and assayed histologically and quantitatively by noninvasive bioluminescence imaging. Our studies provide novel evidence that by recapitulating physiological tissue rigidity, propagation of adult muscle stem cells is possible, enabling future cell-based therapies for muscle-wasting diseases.

  • 4. Gilbert, Penney M.
    et al.
    Corbel, Stephane
    Doyonnas, Regis
    Havenstrite, Karen
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Blau, Helen M.
    A single cell bioengineering approach to elucidate mechanisms of adult stem cell self-renewal2012In: Integrative Biology, ISSN 1757-9694, E-ISSN 1757-9708, Vol. 4, no 4, p. 360-367Article in journal (Refereed)
    Abstract [en]

    The goal of regenerative medicine is to restore form and function to damaged and aging tissues. Adult stem cells, present in tissues such as skeletal muscle, comprise a reservoir of cells with a remarkable capacity to proliferate and repair tissue damage. Muscle stem cells, known as satellite cells, reside in a quiescent state in an anatomically distinct compartment, or niche, ensheathed between the membrane of the myofiber and the basal lamina. Recently, procedures for isolating satellite cells were developed and experiments testing their function upon transplantation into muscles revealed an extraordinary potential to contribute to muscle fibers and access and replenish the satellite cell compartment. However, these properties are rapidly lost once satellite cells are plated in culture. Accordingly, elucidating the role of extrinsic factors in controlling muscle stem cell fate, in particular self-renewal, is critical. Through careful design of bioengineered culture platforms, analysis of specific proteins presented to stem cells is possible. Critical to the success of the approach is single cell analysis, as more rapidly proliferating progenitors may mask the behavior of stem cells that proliferate slowly. Bioengineering approaches provide a potent means of gaining insight into the role of extrinsic factors in the stem cell microenvironment on stem cell function and the mechanisms that control their diverse fates. Ultimately, the multidisciplinary approach presented here will lead to novel therapeutic strategies for degenerative diseases.

  • 5. Ho, Andrew T. V.
    et al.
    Palla, Adelaida R.
    Blake, Matthew R.
    Yucel, Nora D.
    Wang, Yu Xin
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing. Stanford Sch Med, USA.
    Holbrook, Colin A.
    Kraft, Peggy E.
    Delp, Scott L.
    Blau, Helen M.
    Prostaglandin E2 is essential for efficacious skeletal muscle stem-cell function, augmenting regeneration and strength2017In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 114, no 26, p. 6675-6684Article in journal (Refereed)
    Abstract [en]

    Skeletal muscles harbor quiescent muscle-specific stem cells (MuSCs) capable of tissue regeneration throughout life. Muscle injury precipitates a complex inflammatory response in which a multiplicity of cell types, cytokines, and growth factors participate. Here we show that Prostaglandin E2 (PGE2) is an inflammatory cytokine that directly targets MuSCs via the EP4 receptor, leading to MuSC expansion. An acute treatment with PGE2 suffices to robustly augment muscle regeneration by either endogenous or transplanted MuSCs. Loss of PGE2 signaling by specific genetic ablation of the EP4 receptor in MuSCs impairs regeneration, leading to decreased muscle force. Inhibition of PGE2 production through nonsteroidal anti-inflammatory drug (NSAID) administration just after injury similarly hinders regeneration and compromises muscle strength. Mechanistically, the PGE2 EP4 interaction causes MuSC expansion by triggering a cAMP/phosphoCREB pathway that activates the proliferation-inducing transcription factor, Nurr1. Our findings reveal that loss of PGE2 signaling to MuSCs during recovery from injury impedes muscle repair and strength. Through such gain-or loss-of-function experiments, we found that PGE2 signaling acts as a rheostat for muscle stem-cell function. Decreased PGE2 signaling due to NSAIDs or increased PGE2 due to exogenous delivery dictates MuSC function, which determines the outcome of regeneration. The markedly enhanced and accelerated repair of damaged muscles following intramuscular delivery of PGE2 suggests a previously unrecognized indication for this therapeutic agent.

  • 6.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Segmentation and tracking of cells and particles in time-lapse microscopy2016Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In biology, many different kinds of microscopy are used to study cells. There are many different kinds of transmission microscopy, where light is passed through the cells, that can be used without staining or other treatments that can harm the cells. There is also fluorescence microscopy, where fluorescent proteins or dyes are placed in the cells or in parts of the cells, so that they emit light of a specific wavelength when they are illuminated with light of a different wavelength. Many fluorescence microscopes can take images on many different depths in a sample and thereby build a three-dimensional image of the sample. Fluorescence microscopy can also be used to study particles, for example viruses, inside cells. Modern microscopes often have digital cameras or other equipment to take images or record time-lapse video.

    When biologists perform experiments on cells, they often record image sequences or sequences of three-dimensional volumes to see how the cells behave when they are subjected to different drugs, culture substrates, or other external factors. Previously, the analysis of recorded data has often been done manually, but that is very time-consuming and the results often become subjective and hard to reproduce. Therefore there is a great need for technology for automated analysis of image sequences with cells and particles inside cells. Such technology is needed especially in biological research and drug development. But the technology could also be used clinically, for example to tailor a cancer treatment to an individual patient by evaluating different treatments on cells from a biopsy.

    This thesis presents algorithms to find cells and particles in images, and to calculate tracks that show how they have moved during an experiment. We have developed a complete system that can find and track cells in all commonly used imaging modalities. We selected and extended a number of existing segmentation algorithms, and thereby created a complete tool to find cell outlines. To link the segmented objects into tracks, we developed a new track linking algorithm. The algorithm adds tracks one by one using dynamic programming, and has many advantages over prior algorithms. Among other things, it is fast, it calculates tracks which are optimal for the entire image sequence, and it can handle situations where multiple cells have been segmented incorrectly as one object. To make it possible to use information about the velocities of the objects in the linking, we developed a method where the positions of the objects are preprocessed using a filter before the linking is performed. This is important for tracking of some particles inside cells and for tracking of cell nuclei in some embryos.

     

     

     

    We have developed an open source software which contains all tools that are necessary to analyze image sequences with cells or particles. It has tools for segmentation and tracking of objects, optimization of settings, manual correction, and analysis of outlines and tracks. We developed the software together with biologists who used it in their research. The software has already been used for data analysis in a number of biology publications. Our system has also achieved outstanding performance in three international objective comparisons of systems for tracking of cells.

  • 7.
    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.

  • 8.
    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.

  • 9.
    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.

  • 10. 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.

  • 11.
    Olofsson, Per
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Cellular Biophysics.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Frisk, Thomas
    KTH, School of Engineering Sciences (SCI), Applied Physics, Cellular Biophysics.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Önfelt, Björn
    KTH, School of Engineering Sciences (SCI), Applied Physics, Cellular Biophysics.
    A collagen-based microwell migration assay to study NK—target cell interactionsManuscript (preprint) (Other academic)
    Abstract [en]

    Natural killer (NK) cell cytotoxicity is highly dependent on the ability of NK cells to migrate through the extracellular matrix (ECM) microenvironment. Traditional imaging studies of NK cell migration and cytotoxicity have utilized 2-D surfaces, which do not properly reproduce the structural and mechanical cues that shape the migratory response of NK cells in vivo. In addition, current in vivo imaging does not allow for the accurate long-term single-cell imaging required to dissect the functional heterogeneity of NK cell populations, and importantly, it does not allow studies of human cells. Therefore, it is desirable to implement in vitro migration and killing assays that better mimic in vivo conditions.

    We have combined a microwell assay that allows long-term imaging and tracking of small, well-defined populations of NK cells with an interstitial ECM-like matrix to more closely approximate in vivo conditions. The microwells, which are loaded with a gel mixture containing NK and target cells, allows for long-term imaging of NK–target cell interactions within a confined 3-D volume. The microwells were optically sectioned by confocal fluorescence microscopy once every 2 min for 12 h. NK cells were tracked by the Baxter Algorithms to assess motility parameters and interactions with target cells were manually scored for duration and outcome.

    We found marked differences in motility between individual cells with a significant fraction of the cells moving slowly and being confined to a small area within the matrix, while other cells moved more freely, probably reflecting local variations in the matrix structure and inherent difference in motility between individual cells. A majority of NK cells also exhibited transient variation in their mobility alternating between periods of migration arrest and random movement. NK cells that alternated between different modes of migration switched on average once every 3 h.

    NK cells made fewer and shorter contacts with target cells than in comparable 2-D assays. The difference was particularly pronounced for the process of post-conjugation attachment when NK and target cells separate. The timing of this process is likely influenced by a biomechanical component only present in 3-D environments where the cells are offered multiple anchor points with the matrix that can be used to generate the forces needed to pull apart.

    The developed microwell-based assay is suitable for 3-D time-lapse imaging of NK cells migration and cytotoxicity. As it allows for experiments with human cells, it could be used as a complement to in vivo imaging to study the influence of e.g. education and cytokine activation on NK cell heterogeneity in migration and cytotoxicity.

  • 12. Sadanandan, Sajith Kecheril
    et al.
    Baltekin, Ozden
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Boucharin, Alexis
    Ranefall, Petter
    Jalden, Joakim
    Elf, Johan
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Wahlby, Carolina
    Segmentation and Track-Analysis in Time-Lapse Imaging of Bacteria2016In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 10, no 1, p. 174-184Article in journal (Refereed)
    Abstract [en]

    In this paper, we have developed tools to analyze prokaryotic cells growing in monolayers in a microfluidic device. Individual bacterial cells are identified using a novel curvature based approach and tracked over time for several generations. The resulting tracks are thereafter assessed and filtered based on track quality for subsequent analysis of bacterial growth rates. The proposed method performs comparable to the state-of-the-art methods for segmenting phase contrast and fluorescent images, and we show a 10-fold increase in analysis speed.

  • 13. Ulman, V
    et al.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Information Science and Engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ortiz-de-Solorzano, Carlos
    et al.,
    An objective comparison of cell-tracking algorithms2017In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 14, no 12, p. 1141-+Article in journal (Refereed)
    Abstract [en]

    We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

  • 14.
    Yajnanarayana, Vijaya
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Brandt, Rasmus
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dwivedi, Satyam
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal Scheduling for Interference Mitigation by Range Information2017In: IEEE Transactions on Mobile Computing, ISSN 1536-1233, E-ISSN 1558-0660, Vol. 16, no 11, p. 3167-3181Article in journal (Refereed)
  • 15.
    Yajnanarayana, Vijaya
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Brandt, Rasmus
    Dwivedi,, Satyam
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Optimal Scheduling for Interference Mitigation by Range InformationManuscript (preprint) (Other academic)
    Abstract [en]

    This paper describes several algorithms for generating an optimal schedule for multiple access on a shared channel by utilizing range information in a fully connected network. We also provide detailed analysis for the proposed algorithms in terms of their complexity, convergence, and effect of non-idealities in the network. The performance of the proposed schemes are compared with non-aided methods to quantify the benefits of using the range information in the communication. We argue that the proposed techniques yield significant benefits as the number of nodes in the network increases. We provide simulation results in support of the claim. The proposed methods indicate that the throughput can be increased on average by 3-10 times for typical network configurations.

1 - 15 of 15
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf