An adaptive neuro-fuzzy propagation model for LoRaWAN

This article proposes an adaptive-network-based fuzzy inference system (ANFIS) model for accurate estimation of signal propagation using LoRaWAN. By using ANFIS, the basic knowledge of propagation is embedded into the proposed model. This reduces the training complexity of artificial neural network (ANN)-based models. Therefore, the size of the training dataset is reduced by 70% compared to an ANN model. The proposed model consists of an efficient clustering method to identify the optimum number of the fuzzy nodes to avoid overfitting, and a hybrid training algorithm to train and optimize the ANFIS parameters. Finally, the proposed model is benchmarked with extensive practical data, where superior accuracy is achieved compared to deterministic models, and better generalization is attained compared to ANN models. The proposed model outperforms the nondeterministic models in terms of accuracy, has the flexibility to account for new modeling parameters, is easier to use as it does not require a model for propagation environment, is resistant to data collection inaccuracies and uncertain environmental information, has excellent generalization capability, and features a knowledge-based implementation that alleviates the training process. This work will facilitate network planning and propagation prediction in complex scenarios

RADAMESH: Cosmological Radiative Transfer for Adaptive Mesh Refinement Simulations

We present a new three-dimensional radiative transfer (RT) code, RADAMESH, based on a ray-tracing, photon-conserving and adaptive (in space and time) scheme. RADAMESH uses a novel Monte Carlo approach to sample the radiation field within the computational domain on a "cell-by-cell" basis. Thanks to this algorithm, the computational efforts are now focused where actually needed, i.e. within the Ionization-fronts (I-fronts). This results in an increased accuracy level and, at the same time, a huge gain in computational speed with respect to a "classical" Monte Carlo RT, especially when combined with an Adaptive Mesh Refinement (AMR) scheme. Among several new features, RADAMESH is able to adaptively refine the computational mesh in correspondence of the I-fronts, allowing to fully resolve them within large, cosmological boxes. We follow the propagation of ionizing radiation from an arbitrary number of sources and from the recombination radiation produced by H and He. The chemical state of six species (HI, HII, HeI, HeII, HeIII, e) and gas temperatures are computed with a time-dependent, non-equilibrium chemistry solver. We present several validating tests of the code, including the standard tests from the RT Code Comparison Project and a new set of tests aimed at substantiating the new characteristics of RADAMESH. Using our AMR scheme, we show that properly resolving the I-front of a bright quasar during Reionization produces a large increase of the predicted gas temperature within the whole HII region. Also, we discuss how H and He recombination radiation is able to substantially change the ionization state of both species (for the classical Stroemgren sphere test) with respect to the widely used "on-the-spot" approximation.Comment: 19 pages, 24 figures; accepted for publication in MNRAS, version with high-resolution figures is avalaible at http://www.ast.cam.ac.uk/~cantal/Papers/CP10.pd

Pathfinder first light: alignment, calibration, and commissioning of the LINC-NIRVANA ground-layer adaptive optics subsystem

We present descriptions of the alignment and calibration tests of the Pathfinder, which achieved first light during our 2013 commissioning campaign at the LBT. The full LINC-NIRVANA instrument is a Fizeau interferometric imager with fringe tracking and 2-layer natural guide star multi-conjugate adaptive optics (MCAO) systems on each eye of the LBT. The MCAO correction for each side is achieved using a ground layer wavefront sensor that drives the LBT adaptive secondary mirror and a mid-high layer wavefront sensor that drives a Xinetics 349 actuator DM conjugated to an altitude of 7.1 km. When the LINC-NIRVANA MCAO system is commissioned, it will be one of only two such systems on an 8-meter telescope and the only such system in the northern hemisphere. In order to mitigate risk, we take a modular approach to commissioning by decoupling and testing the LINC-NIRVANA subsystems individually. The Pathfinder is the ground-layer wavefront sensor for the DX eye of the LBT. It uses 12 pyramid wavefront sensors to optically co-add light from natural guide stars in order to make four pupil images that sense ground layer turbulence. Pathfinder is now the first LINC-NIRVANA subsystem to be fully integrated with the telescope and commissioned on sky. Our 2013 commissioning campaign consisted of 7 runs at the LBT with the tasks of assembly, integration and communication with the LBT telescope control system, alignment to the telescope optical axis, off-sky closed loop AO calibration, and finally closed loop on-sky AO. We present the programmatics of this campaign, along with the novel designs of our alignment scheme and our off-sky calibration test, which lead to the Pathfinder's first on-sky closed loop images

Determining the Phase and Amplitude Distortion of a Wavefront using a Plenoptic Sensor

We have designed a plenoptic sensor to retrieve phase and amplitude changes resulting from a laser beam's propagation through atmospheric turbulence. Compared with the commonly restricted domain of (-pi, pi) in phase reconstruction by interferometers, the reconstructed phase obtained by the plenoptic sensors can be continuous up to a multiple of 2pi. When compared with conventional Shack-Hartmann sensors, ambiguities caused by interference or low intensity, such as branch points and branch cuts, are less likely to happen and can be adaptively avoided by our reconstruction algorithm. In the design of our plenoptic sensor, we modified the fundamental structure of a light field camera into a mini Keplerian telescope array by accurately cascading the back focal plane of its object lens with a microlens array's front focal plane and matching the numerical aperture of both components. Unlike light field cameras designed for incoherent imaging purposes, our plenoptic sensor operates on the complex amplitude of the incident beam and distributes it into a matrix of images that are simpler and less subject to interference than a global image of the beam. Then, with the proposed reconstruction algorithms, the plenoptic sensor is able to reconstruct the wavefront and a phase screen at an appropriate depth in the field that causes the equivalent distortion on the beam. The reconstructed results can be used to guide adaptive optics systems in directing beam propagation through atmospheric turbulence. In this paper we will show the theoretical analysis and experimental results obtained with the plenoptic sensor and its reconstruction algorithms.Comment: This article has been accepted by JOSA