Power Allocation and Parameter Estimation for Multipath-based 5G Positioning

We consider a single-anchor multiple-input multiple-output orthogonal frequency-division multiplexing system with imperfectly synchronized transmitter (Tx) and receiver (Rx) clocks, where the Rx estimates its position based on the received reference signals. The Tx, having (imperfect) prior knowledge about the Rx location and the surrounding geometry, transmits reference signals based on a set of fixed beams. We develop strategies for the power allocation among the beams aiming to minimize the expected Cram\ue9r-Rao lower bound for Rx positioning. Additional constraints on the design are included to make the optimized power allocation robust to uncertainty on the line-of-sight (LOS) path direction. Furthermore, the effect of clock asynchronism on the proposed allocation strategies is studied. Our evaluation results show that, for non-negligible synchronization error, it is optimal to allocate a large fraction of the available power for the illumination of the non-LOS (NLOS) paths, which help resolve the clock offset. In addition, the complexity reduction achieved by our proposed suboptimal approach incurs only a small performance degradation. We also propose an off-grid compressed sensing-based position estimation algorithm, which exploits the information on the clock offset provided by NLOS paths, and show that it is asymptotically efficient

Cooperative localization with angular measurements and posterior linearization

The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage of the positioning. Conventional distance measurements between vehicles are limited by the need for synchronization and provide no heading information of the vehicle. To address this, we present a cooperative localization algorithm using posterior linearization belief propagation (PLBP) utilizing angle-of-arrival (AoA)-only measurements. Simulation results show that both directional and positional root mean squared error (RMSE) of vehicles can be decreased significantly and converge to a low value in a few iterations. Furthermore, the influence of parameters for the vehicular network, such as vehicle density, communication radius, prior uncertainty, and AoA measurements noise, is analyzed

A generative model of hyperelastic strain energy density functions for multiple tissue brain deformation

PURPOSE: Estimation of brain deformation is crucial during neurosurgery. Whilst mechanical characterisation captures stress-strain relationships of tissue, biomechanical models are limited by experimental conditions. This results in variability reported in the literature. The aim of this work was to demonstrate a generative model of strain energy density functions can estimate the elastic properties of tissue using observed brain deformation. METHODS: For the generative model a Gaussian Process regression learns elastic potentials from 73 manuscripts. We evaluate the use of neo-Hookean, Mooney-Rivlin and 1-term Ogden meta-models to guarantee stability. Single and multiple tissue experiments validate the ability of our generative model to estimate tissue properties on a synthetic brain model and in eight temporal lobe resection cases where deformation is observed between pre- and post-operative images. RESULTS: Estimated parameters on a synthetic model are close to the known reference with a root-mean-square error (RMSE) of 0.1 mm and 0.2 mm between surface nodes for single and multiple tissue experiments. In clinical cases, we were able to recover brain deformation from pre- to post-operative images reducing RMSE of differences from 1.37 to 1.08 mm on the ventricle surface and from 5.89 to 4.84 mm on the resection cavity surface. CONCLUSION: Our generative model can capture uncertainties related to mechanical characterisation of tissue. When fitting samples from elastography and linear studies, all meta-models performed similarly. The Ogden meta-model performed the best on hyperelastic studies. We were able to predict elastic parameters in a reference model on a synthetic phantom. However, deformation observed in clinical cases is only partly explained using our generative model

Cooperative Localization with Angular Measurements and Posterior Linearization

The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage. Conventional distance measurements between vehicles are limited by the need for synchronization and provide no heading information of the vehicle. To address this, we present a cooperative localization algorithm using posterior linearization belief propagation (PLBP) utilizing angle-of-arrival (AoA)-only measurements. Simulation results show that both directional and positional root mean squared error (RMSE) of vehicles can be decreased significantly and converge to a low value in a few iterations. Furthermore, the influence of parameters for the vehicular network, such as vehicle density, communication radius, prior uncertainty and AoA measurements noise, is analyzed.Comment: Submitted for possible publication to an IEEE conferenc

Plasmonic nanodevice with magnetic funcionalities: fabrication and characterization

We have designed and fabricated a nanodevice exhibiting simultaneously ferromagnetic properties of nanostructures with plasmonic properties of continuous films. Our device consists of an array of nanomagnets on top of a continuous plasmonic film. The patterned nanomagnets magnetic state is single domain and well-defined shape anisotropy. Despite the presence of the patterned media on top of the Au film, the system exhibits surface plasmon resonance characteristics of a continuous film, i.e., propagating surface plasmon-polaritons

Manipulating exciton fine-structure in quantum dots with a lateral electric field

The fine structure of the neutral exciton in a single self assembled InGaAs quantum dot is investigated under the effect of a lateral electric field. Stark shifts up to 1.5 meV, an increase in linewidth, and a decrease in photoluminescence intensity were observed due to the electric field. We show that the lateral electric field strongly affects the exciton fine structure splitting due to active manipulation of the single particle wave-functions. Remarkably, the splitting can be tuned over large values and through zero.Comment: 4 pages, 5 figure

Removal of nutrients and pesticides from agricultural runoff using microalgae and cyanobacteria

The use of pesticides in agriculture has ensured the production of different crops. However, pesticides have become an emerging public health problem for Latin American countries due to their excessive use, inadequate application, toxic characteristics, and minimal residue control. The current project evaluates the ability of two strains of algae (Chlorella and Scenedesmus sp.) and one cyanobacteria (Hapalosyphon sp.) to remove excess pesticides and other nutrients present in runoff water from rice production. Different concentrations of wastewater and carbon sources (Na2CO3 and NaHCO3 ) were evaluated. According to the results, all three strains can be grown in wastewater without dilution (100%), with a biomass concentration comparable to a synthetic medium. All three strains significantly reduced the concentration of NO3 and PO4 (95 and 85%, respectively), with no difference between Na2CO3 or NaHCO3 . Finally, Chlorella sp. obtained the highest removal efficiency of the pesticide (Chlorpyrifos), followed by Scenedesmus and Hapalosyphon sp. (100, 75, and 50%, respectively). This work shows that it is possible to use this type of waste as an alternative source of nutrients to obtain biomass and metabolites of interest, such as lipids and carbohydrates, to produce biofuels

Nanometer-scale characterization of laser-driven compression, shocks, and phase transitions, by x-ray scattering using free electron lasers

We study the feasibility of using small angle X-ray scattering (SAXS) as a new experimental diagnostic for intense laser-solid interactions. By using X-ray pulses from a hard X-ray free electron laser, we can simultaneously achieve nanometer and femtosecond resolution of laser-driven samples. This is an important new capability for the Helmholtz international beamline for extreme fields at the high energy density endstation currently built at the European X-ray free electron laser. We review the relevant SAXS theory and its application to transient processes in solid density plasmas and report on first experimental results that confirm the feasibility of the method. We present results of two test experiments where the first experiment employs ultra-short laser pulses for studying relativistic laser plasma interactions, and the second one focuses on shock compression studies with a nanosecond laser system

Growth Interruption Effect on the Fabrication of GaAs Concentric Multiple Rings by Droplet Epitaxy

We present the molecular beam epitaxy fabrication and optical properties of complex GaAs nanostructures by droplet epitaxy: concentric triple quantum rings. A significant difference was found between the volumes of the original droplets and the final GaAs structures. By means of atomic force microscopy and photoluminescence spectroscopy, we found that a thin GaAs quantum well-like layer is developed all over the substrate during the growth interruption times, caused by the migration of Ga in a low As background