An M-QAM Signal Modulation Recognition Algorithm in AWGN Channel

Computing the distinct features from input data, before the classification, is a part of complexity to the methods of Automatic Modulation Classification (AMC) which deals with modulation classification was a pattern recognition problem. Although the algorithms that focus on MultiLevel Quadrature Amplitude Modulation (M-QAM) which underneath different channel scenarios was well detailed. A search of the literature revealed indicates that few studies were done on the classification of high order M-QAM modulation schemes like128-QAM, 256-QAM, 512-QAM and1024-QAM. This work is focusing on the investigation of the powerful capability of the natural logarithmic properties and the possibility of extracting Higher-Order Cumulant's (HOC) features from input data received raw. The HOC signals were extracted under Additive White Gaussian Noise (AWGN) channel with four effective parameters which were defined to distinguished the types of modulation from the set; 4-QAM~1024-QAM. This approach makes the recognizer more intelligent and improves the success rate of classification. From simulation results, which was achieved under statistical models for noisy channels, manifest that recognized algorithm executes was recognizing in M-QAM, furthermore, most results were promising and showed that the logarithmic classifier works well over both AWGN and different fading channels, as well as it can achieve a reliable recognition rate even at a lower signal-to-noise ratio (less than zero), it can be considered as an Integrated Automatic Modulation Classification (AMC) system in order to identify high order of M-QAM signals that applied a unique logarithmic classifier, to represents higher versatility, hence it has a superior performance via all previous works in automatic modulation identification systemComment: 18 page

Superconducting Quantum Interference in Fractal Percolation Films. Problem of 1/f Noise

An oscillatory magnetic field dependence of the DC voltage is observed when a low-frequency current flows through superconducting Sn-Ge thin-film composites near the percolation threshold. The paper also studies the experimental realisations of temporal voltage fluctuations in these films. Both the structure of the voltage oscillations against the magnetic field and the time series of the electric "noise" possess a fractal pattern. With the help of the fractal analysis procedure, the fluctuations observed have been shown to be neither a noise with a large number of degrees of freedom, nor the realisations of a well defined dynamic system. On the contrary the model of voltage oscillations induced by the weak fluctuations of a magnetic field of arbitrary nature gives the most appropriate description of the phenomenon observed. The imaging function of such a transformation possesses a fractal nature, thus leading to power-law spectra of voltage fluctuations even for the simplest types of magnetic fluctuations including the monochromatic ones. Thus, the paper suggests a new universal mechanism of a "1/f noise" origin. It consists in a passive transformation of any natural fluctuations with a fractal-type transformation function.Comment: 17 pages, 13 eps-figures, Latex; title page and figures include

Space Shuttle Proximity Operation Sensor Study

The performance of the Kuband radar was analyzed in detail, and the performance was updated and summarized. In so doing, two different radar design philosophies were described, and the corresponding differences in losses were enumerated. The resulting design margins were determined for both design philosophies and for both the designated and nondesignated range modes of operation. In some cases, the design margin was about zero, and in other cases it was significantly less than zero. With the point of view described above, the recommended solution is to allow more scan time but at the present scan rate. With no other changes in the present configuration, the radar met design detection specifications for all design philosophies at a range of 11.3 nautical miles

Astrometry and Photometry with Coronagraphs

We propose a solution to the problem of astrometric and photometric calibration of coronagraphic images with a simple optical device which, in theory, is easy to use. Our design uses the Fraunhofer approximation of Fourier optics. Placing a periodic grid of wires (we use a square grid) with known width and spacing in a pupil plane in front of the occulting coronagraphic focal plane mask produces fiducial images of the obscured star at known locations relative to the star. We also derive the intensity of these fiducial images in the coronagraphic image. These calibrator images can be used for precise relative astrometry, to establish companionship of other objects in the field of view through measurement of common proper motion or common parallax, to determine orbits, and to observe disk structure around the star quantitatively. The calibrator spots also have known brightness, selectable by the coronagraph designer, permitting accurate relative photometry in the coronagraphic image. This technique, which enables precision exoplanetary science, is relevant to future coronagraphic instruments, and is particularly useful for `extreme' adaptive optics and space-based coronagraphy.Comment: To appear in ApJ August 2006, 27 preprint style pages 4 figure

Subtraction of Bright Point Sources from Synthesis Images of the Epoch of Reionization

Bright point sources associated with extragalactic AGN and radio galaxies are an important foreground for low frequency radio experiments aimed at detecting the redshifted 21cm emission from neutral hydrogen during the epoch of reionization. The frequency dependence of the synthesized beam implies that the sidelobes of these sources will move across the field of view as a function of observing frequency, hence frustrating line-of-sight foreground subtraction techniques. We describe a method for subtracting these point sources from dirty maps produced by an instrument such as the MWA. This technique combines matched filters with an iterative centroiding scheme to locate and characterize point sources in the presence of a diffuse background. Simulations show that this technique can improve the dynamic range of EOR maps by 2-3 orders of magnitude.Comment: 11 pages, 8 figures, 1 table, submitted to PAS

Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design

Massive multiple-input multiple-output (MIMO) systems are cellular networks where the base stations (BSs) are equipped with unconventionally many antennas, deployed on co-located or distributed arrays. Huge spatial degrees-of-freedom are achieved by coherent processing over these massive arrays, which provide strong signal gains, resilience to imperfect channel knowledge, and low interference. This comes at the price of more infrastructure; the hardware cost and circuit power consumption scale linearly/affinely with the number of BS antennas $N$. Hence, the key to cost-efficient deployment of large arrays is low-cost antenna branches with low circuit power, in contrast to today's conventional expensive and power-hungry BS antenna branches. Such low-cost transceivers are prone to hardware imperfections, but it has been conjectured that the huge degrees-of-freedom would bring robustness to such imperfections. We prove this claim for a generalized uplink system with multiplicative phase-drifts, additive distortion noise, and noise amplification. Specifically, we derive closed-form expressions for the user rates and a scaling law that shows how fast the hardware imperfections can increase with $N$ while maintaining high rates. The connection between this scaling law and the power consumption of different transceiver circuits is rigorously exemplified. This reveals that one can make the circuit power increase as $\sqrt{N}$, instead of linearly, by careful circuit-aware system design.Comment: Accepted for publication in IEEE Transactions on Wireless Communications, 16 pages, 8 figures. The results can be reproduced using the following Matlab code: https://github.com/emilbjornson/hardware-scaling-law

Frequency response modeling and control of flexible structures: Computational methods

The dynamics of vibrations in flexible structures can be conventiently modeled in terms of frequency response models. For structural control such models capture the distributed parameter dynamics of the elastic structural response as an irrational transfer function. For most flexible structures arising in aerospace applications the irrational transfer functions which arise are of a special class of pseudo-meromorphic functions which have only a finite number of right half place poles. Computational algorithms are demonstrated for design of multiloop control laws for such models based on optimal Wiener-Hopf control of the frequency responses. The algorithms employ a sampled-data representation of irrational transfer functions which is particularly attractive for numerical computation. One key algorithm for the solution of the optimal control problem is the spectral factorization of an irrational transfer function. The basis for the spectral factorization algorithm is highlighted together with associated computational issues arising in optimal regulator design. Options for implementation of wide band vibration control for flexible structures based on the sampled-data frequency response models is also highlighted. A simple flexible structure control example is considered to demonstrate the combined frequency response modeling and control algorithms

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

In this paper, we propose a model-based machine-learning approach for dual-polarization systems by parameterizing the split-step Fourier method for the Manakov-PMD equation. The resulting method combines hardware-friendly time-domain nonlinearity mitigation via the recently proposed learned digital backpropagation (LDBP) with distributed compensation of polarization-mode dispersion (PMD). We refer to the resulting approach as LDBP-PMD. We train LDBP-PMD on multiple PMD realizations and show that it converges within 1% of its peak dB performance after 428 training iterations on average, yielding a peak effective signal-to-noise ratio of only 0.30 dB below the PMD-free case. Similar to state-of-the-art lumped PMD compensation algorithms in practical systems, our approach does not assume any knowledge about the particular PMD realization along the link, nor any knowledge about the total accumulated PMD. This is a significant improvement compared to prior work on distributed PMD compensation, where knowledge about the accumulated PMD is typically assumed. We also compare different parameterization choices in terms of performance, complexity, and convergence behavior. Lastly, we demonstrate that the learned models can be successfully retrained after an abrupt change of the PMD realization along the fiber.Comment: 10 pages, 11 figures, to appear in the IEEE/OSA Journal of Lightwave Technolog

Single-input Multiple-output Tunable Log-domain Current-mode Universal Filter

This paper describes the design of a current-mode single-input multiple-output (SIMO) universal filter based on the log-domain filtering concept. The circuit is a direct realization of a first-order differential equation for obtaining the lossy integrator circuit. Lossless integrators are realized by log-domain lossy integrators. The proposed filter comprises only two grounded capacitors and twenty-four transistors. This filter suits to operate in very high frequency (VHF) applications. The pole-frequency of the proposed filter can be controlled over five decade frequency range through bias currents. The pole-Q can be independently controlled with the pole-frequency. Non-ideal effects on the filter are studied in detail. A validated BJT model is used in the simulations operated by a single power supply, as low as 2.5 V. The simulation results using PSpice are included to confirm the good performances and are in agreement with the theory