Compressed Sensing based Dynamic PSD Map Construction in Cognitive Radio Networks

In the context of spectrum sensing in cognitive radio networks, collaborative spectrum sensing has been proposed as a way to overcome multipath and shadowing, and hence increasing the reliability of the sensing. Due to the high amount of information to be transmitted, a dynamic compressive sensing approach is proposed to map the PSD estimate to a sparse domain which is then transmitted to the fusion center. In this regard, CRs send a compressed version of their estimated PSD to the fusion center, whose job is to reconstruct the PSD estimates of the CRs, fuse them, and make a global decision on the availability of the spectrum in space and frequency domains at a given time. The proposed compressive sensing based method considers the dynamic nature of the PSD map, and uses this dynamicity in order to decrease the amount of data needed to be transmitted between CR sensors’ and the fusion center. By using the proposed method, an acceptable PSD map for cognitive radio purposes can be achieved by only 20 % of full data transmission between sensors and master node. Also, simulation results show the robustness of the proposed method against the channel variations, diverse compression ratios and processing times in comparison with static methods

HVOX: Scalable Interferometric Synthesis and Analysis of Spherical Sky Maps

Analysis and synthesis are key steps of the radio-interferometric imaging process, serving as a bridge between visibility and sky domains. They can be expressed as partial Fourier transforms involving a large number of non-uniform frequencies and spherically-constrained spatial coordinates. Due to the data non-uniformity, these partial Fourier transforms are computationally expensive and represent a serious bottleneck in the image reconstruction process. The W-gridding algorithm achieves log-linear complexity for both steps by applying a series of 2D non-uniform FFTs (NUFFT) to the data sliced along the so-called $w$ frequency coordinate. A major drawback of this method however is its restriction to direction-cosine meshes, which are fundamentally ill-suited for large field of views. This paper introduces the HVOX gridder, a novel algorithm for analysis/synthesis based on a 3D-NUFFT. Unlike W-gridding, the latter is compatible with arbitrary spherical meshes such as the popular HEALPix scheme for spherical data processing. The 3D-NUFFT allows one to optimally select the size of the inner FFTs, in particular the number of W-planes. This results in a better performing and auto-tuned algorithm, with controlled accuracy guarantees backed by strong results from approximation theory. To cope with the challenging scale of next-generation radio telescopes, we propose moreover a chunked evaluation strategy: by partitioning the visibility and sky domains, the 3D-NUFFT is decomposed into sub-problems which execute in parallel, while simultaneously cutting memory requirements. Our benchmarking results demonstrate the scalability of HVOX for both SKA and LOFAR, considering state-of-the-art challenging imaging setups. HVOX is moreover computationally competitive with W-gridder, despite the absence of domain-specific optimizations in our implementation

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

The Standing Wave Phenomenon in Radio Telescopes; Frequency Modulation of the WSRT Primary Beam

Inadequacies in the knowledge of the primary beam response of current interferometric arrays often form a limitation to the image fidelity. We hope to overcome these limitations by constructing a frequency-resolved, full-polarization empirical model for the primary beam of the Westerbork Synthesis Radio Telescope (WSRT). Holographic observations, sampling angular scales between about 5 arcmin and 11 degrees, were obtained of a bright compact source (3C147). These permitted measurement of voltage response patterns for seven of the fourteen telescopes in the array and allowed calculation of the mean cross-correlated power beam. Good sampling of the main-lobe, near-in, and far-side-lobes out to a radius of more than 5 degrees was obtained. A robust empirical beam model was detemined in all polarization products and at frequencies between 1322 and 1457 MHz with 1 MHz resolution. Substantial departures from axi-symmetry are apparent in the main-lobe as well as systematic differences between the polarization properties. Surprisingly, many beam properties are modulated at the 5 to 10% level with changing frequency. These include: (1) the main beam area, (2) the side-lobe to main-lobe power ratio, and (3) the effective telescope aperture. These semi-sinusoidsal modulations have a basic period of about 17 MHz, consistent with the natural 'standing wave' period of a 8.75 m focal distance. The deduced frequency modulations of the beam pattern were verified in an independent long duration observation using compact continuum sources at very large off-axis distances. Application of our frequency-resolved beam model should enable higher dynamic range and improved image fidelity for interferometric observations in complex fields. (abridged)Comment: 12 pages, 11 figures, Accepted for publication in A&A, figures compressed to low resolution; high-resolution version available at: http://www.astro.rug.nl/~popping/wsrtbeam.pd

Imaging time series for the classification of EMI discharge sources

In this work, we aim to classify a wider range of Electromagnetic Interference (EMI) discharge sources collected from new power plant sites across multiple assets. This engenders a more complex and challenging classification task. The study involves an investigation and development of new and improved feature extraction and data dimension reduction algorithms based on image processing techniques. The approach is to exploit the Gramian Angular Field technique to map the measured EMI time signals to an image, from which the significant information is extracted while removing redundancy. The image of each discharge type contains a unique fingerprint. Two feature reduction methods called the Local Binary Pattern (LBP) and the Local Phase Quantisation (LPQ) are then used within the mapped images. This provides feature vectors that can be implemented into a Random Forest (RF) classifier. The performance of a previous and the two new proposed methods, on the new database set, is compared in terms of classification accuracy, precision, recall, and F-measure. Results show that the new methods have a higher performance than the previous one, where LBP features achieve the best outcome

RME-GAN: A Learning Framework for Radio Map Estimation based on Conditional Generative Adversarial Network

Outdoor radio map estimation is an important tool for network planning and resource management in modern Internet of Things (IoT) and cellular systems. Radio map describes spatial signal strength distribution and provides network coverage information. A practical goal is to estimate fine-resolution radio maps from sparse radio strength measurements. However, non-uniformly positioned measurements and access obstacles can make it difficult for accurate radio map estimation (RME) and spectrum planning in many outdoor environments. In this work, we develop a two-phase learning framework for radio map estimation by integrating radio propagation model and designing a conditional generative adversarial network (cGAN). We first explore global information to extract the radio propagation patterns. We then focus on the local features to estimate the effect of shadowing on radio maps in order to train and optimize the cGAN. Our experimental results demonstrate the efficacy of the proposed framework for radio map estimation based on generative models from sparse observations in outdoor scenarios

Master of Science

thesisConsistency analysis and data collaboration is a relatively new scientific area. It deals with quantifying how well scientific models approximate empirical reality. Consistency analysis is based on methodically comparing model predictions with experimental measurements, but this task is made more difficult by the fact that both models and experiments have their own inherent uncertainties. Computational fluid dynamics (CFD) models are numerical methods able to solve complicated discrete fluid dynamics problems. They are used thoroughly in mechanical, aerospace and energy science. As CFD models are being applied to more and more critical systems, there is a growing need to improve the reliability of CFD model predictions. This work addresses this need by presenting consistency analysis results for a simple CFD model and an experiment in which the concentration field of a buoyant helium plume had been studied by holographic interferometry. A detailed procedure is presented for carrying out data collaboration between simulation and experimental data. This work is novel in a sense that it is the first to present the specific difficulties of collaborating interferometric data. These difficulties arise from the encoded nature of information being present in interferometric fringe images

Radio Astronomy

Contains summary of research and reports on nine research projects.National Science Foundation (Grant AST81-21416)National Science Foundation (Grant AST82-14296)National Aeronautics and Space Administration (Grant S-10781-C)National Aeronautics and Space Administration (Grant NAGW-373)National Science Foundation (Grant AST79-19553)M.I.T. Sloan Fund for Basic ResearchNational Oceanic and Atmospheric Administration (Grant 04-8-M01-1)National Aeronautics and Space Administration (Grant NAG5-10)National Aeronautics and Space Administration (Contract NAS5-22929)Defense Advanced Research Projects Agency (Contract MDA 903-82-K-0521)Center for Advanced Television Studie