A new joint coding and modulation scheme for channels with clipping

A major limitation in any high-performance digital communication system is the linearity region of the transmitting amplifier. Nonlinearities typically lead to signal clipping. Efficient communication in such conditions requires maintaining a low peak-to-average power ratio (PAR) in the transmitted signal while achieving a high throughput of data. Excessive PAR leads either to frequent clipping or to inadequate resolution in the analog-to-digital or digital-to-analog converters. Currently proposed signaling schemes for future generation wireless communications suffer from a high PAR. This paper presents a new signaling scheme for channels with clipping which achieves a PAR as low as 3. For a given linear range in the transmitter's digital-to-analog converter, this scheme achieves a lower bit-error rate than existing multicarrier schemes, owing to increased separation between constellation points. We present the theoretical basis for this new scheme, approximations for the expected bit-error rate, and simulation results. (C) 2002 Elsevier Science (USA).

Low-complexity low-PAR transmission for MIMO-DSL

This letter considers clip-limited transmission over multiple-input multiple-output digital subscriber lines (MIMO-DSL). We show that a recent low complexity, low peak-to-average-ratio (PAR) single-input modulation technique can be applied to the case of multiple cross-talking channels in a bonded-DSL system. Unfortunately however the direct initialization procedure is computationally infeasible. In this paper, we provide a novel low-complexity initialization procedure. Simulations confirm that the proposed approach has superior performance in clip-limited conditions, compared with both discrete matrix multitone and vectored discrete multitone.

Detecting finite bandwidth periodic signals in stationary noise using the signal coherence spectrum

All signals that appear to be periodic have some sort of variability from period to period regardless of how stable they appear to be in a data plot. A true sinusoidal time series is a deterministic function of time that never changes and thus has zero bandwidth around the sinusoid's frequency. A zero bandwidth is impossible in nature since all signals have some intrinsic variability over time. Deterministic sinusoids are used to model cycles as a mathematical convenience. Hinich [IEEE J. Oceanic Eng. 25 (2) (2000) 256-261] introduced a parametric statistical model, called the randomly modulated periodicity (RMP) that allows one to capture the intrinsic variability of a cycle. As with a deterministic periodic signal the RMP can have a number of harmonics. The likelihood ratio test for this model when the amplitudes and phases are known is given in [M.J. Hinich, Signal Processing 83 (2003) 1349-13521. A method for detecting a RMP whose amplitudes and phases are unknown random process plus a stationary noise process is addressed in this paper. The only assumption on the additive noise is that it has finite dependence and finite moments. Using simulations based on a simple RMP model we show a case where the new method can detect the signal when the signal is not detectable in a standard waterfall spectrograrn display. (c) 2005 Elsevier B.V. All rights reserved.

On the dual structure of the auditory brainstem response in dogs

Objective: To use the over-complete discrete wavelet transform (OCDWT) to further examine the dual structure of auditory brainstem response (ABR) in the dog. Methods: ABR waveforms recorded from 20 adult dogs at supra-threshold (90 and 70 dBnHL) and threshold (0-15 dBSL) levels were decomposed using a six level OCDWT and reconstructed at individual scales (frequency ranges) A6 (0-391 Hz), D6 (391-781 Hz), and D5 (781-1563 Hz). Results: At supra-threshold stimulus levels, the A6 scale (0-391 Hz) showed a large amplitude waveform with its prominent wave corresponding in latency with ABR waves II/III; the D6 scale (391-781 Hz) showed a small amplitude waveform with its first four waves corresponding in latency to ABR waves I, II/III, V, and VI; and the D5 scale (781-1563 Hz) showed a large amplitude, multiple peaked waveform with its first six waves corresponding in latency to ABR waves I, II, III, IV, V, and VI. At threshold stimulus levels (0-15 dBSL), the A6 scale (0-391 Hz) continued to show a relatively large amplitude waveform, but both the D6 and D5 scales (391781 and 781-1563 Hz, respectively) now showed relatively small amplitude waveforms. Conclusions: A dual structure exists within the ABR of the dog, but its relative structure changes with stimulus level. Significance: The ABR in the dog differs from that in the human both in the relative contributions made by its different frequency components, and the way these components change with stimulus level. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Shift, scaling and derivative properties for the discrete cosine transform

A set of DCT domain properties for shifting and scaling by real amounts, and taking linear operations such as differentiation is described. The DCT coefficients of a sampled signal are subjected to a linear transform, which returns the DCT coefficients of the shifted, scaled and/or differentiated signal. The properties are derived by considering the inverse discrete transform as a cosine series expansion of the original continuous signal, assuming sampling in accordance with the Nyquist criterion. This approach can be applied in the signal domain, to give, for example, DCT based interpolation or derivatives. The same approach can be taken in decoding from the DCT to give, for example, derivatives in the signal domain. The techniques may prove useful in compressed domain processing applications, and are interesting because they allow operations from the continuous domain such as differentiation to be implemented in the discrete domain. An image matching algorithm illustrates the use of the properties, with improvements in computation time and matching quality.

Turbulent Time and Length Scale Measurements in High-Velocity Open Channel Flows

In high-velocity open channel flows, the measurements of air-water flow properties are complicated by the strong interactions between the flow turbulence and the entrained air. In the present study, an advanced signal processing of traditional single- and dual-tip conductivity probe signals is developed to provide further details on the air-water turbulent level, time and length scales. The technique is applied to turbulent open channel flows on a stepped chute conducted in a large-size facility with flow Reynolds numbers ranging from 3.8 E+5 to 7.1 E+5. The air water flow properties presented some basic characteristics that were qualitatively and quantitatively similar to previous skimming flow studies. Some self-similar relationships were observed systematically at both macroscopic and microscopic levels. These included the distributions of void fraction, bubble count rate, interfacial velocity and turbulence level at a macroscopic scale, and the auto- and cross-correlation functions at the microscopic level. New correlation analyses yielded a characterisation of the large eddies advecting the bubbles. Basic results included the integral turbulent length and time scales. The turbulent length scales characterised some measure of the size of large vortical structures advecting air bubbles in the skimming flows, and the data were closely related to the characteristic air-water depth Y90. In the spray region, present results highlighted the existence of an upper spray region for C > 0.95 to 0.97 in which the distributions of droplet chord sizes and integral advection scales presented some marked differences with the rest of the flow.

Scalable Visualization of Galaxies, Oceans, and Brains

One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

Self-Similarity of Air-Water Flows in Skimming Flows on Stepped Spillways

Skimming flows on stepped spillways are characterised by a significant rate of turbulent dissipation on the chute. Herein an advanced signal processing of traditional conductivity probe signals is developed to provide further details on the turbulent time and length scales. The technique is applied to a 22° stepped chute operating with flow Reynolds numbers between 3.8 and 7.1 E+5. The new correlation analyses yielded a characterisation of large eddies advecting the bubbles. The turbulent length scales were related to the characteristic depth Y90. Some self-similar relationships were observed systematically at both macroscopic and microscopic levels. These included the distributions of void fraction, bubble count rate, interfacial velocity and turbulence level, and turbulence time and length scales. The self-similarity results were significant because they provided a picture general enough to be used to characterise the air-water flow field in prototype spillways.

Turbulence Characterisation of High-Velocity Free-Surface Flows

In high-velocity free-surface flows, air is continuously being trapped and released through the free-surface. Such high-velocity highly-aerated flows cannot be studied numerically because of the large number of relevant equations and parameters. Herein an advanced signal processing of traditional single- and dual-tip conductivity probes provides some new information on the air-water turbulent time and length scales. The technique is applied to turbulent open channel flows in a large-size facility. The auto- and cross-correlation analyses yield some characterisation of the large eddies advecting the bubbles. The transverse integral turbulent length and time scales are related to the step height: i.e., Lxy/h ~ 0.02 to 0.2, and T.sqrt(g/h) ~ 0.004 to 0.04. The results are irrespective of the Reynolds numbers. The present findings emphasise that turbulent dissipation by large-scale vortices is a significant process in the intermediate zone between the spray and bubbly flow regions (0.3 < C < 0.7). Some self-similar relationships were observed systematically at both macroscopic and microscopic levels. The results are significant because they provide a picture general enough to be used to characterise the air-water flow field in prototype spillways.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

Air target detection via bistatic radar based on LEOS communication signals

The paper discusses the bistatic radar parameters for the case when the transmitter is a satellite emitting communication signals. The model utilises signals from an Iridium-like low earth orbiting satellite system. The maximum detection range, when thermal noise-limited, is discussed at the theoretical level and these results are compared with experimentation. Satellite-radar signal levels and the power of ground reflections are evaluated.

High resolution 3-D imaging via multi-pass SAR

Spaceborne/airborne synthetic aperture radar (SAR) systems provide high resolution two-dimensional terrain imagery. The paper proposes a technique for combining multiple SAR images, acquired on flight paths slightly separated in the elevation direction, to generate high resolution three-dimensional imagery. The technique could be viewed as an extension to interferometric SAR (InSAR) in that it generates topographic imagery with an additional dimension of resolution. The 3-D multi-pass SAR imaging system is typically characterised by a relatively short ambiguity length in the elevation direction. To minimise the associated ambiguities we exploit the relative phase information within the set of images to track the terrain landscape. The SAR images are then coherently combined, via a nonuniform DFT, over a narrow (in elevation) volume centred on the 'dominant' terrain ground plane. The paper includes a detailed description of the technique, background theory, including achievable resolution, and the results of an experimental study.