Applications of nonuniform sampling in wideband multichannel communication systems

This research is an investigation into utilising randomised sampling in communication systems to ease the sampling rate requirements of digitally processing narrowband signals residing within a wide range of overseen frequencies. By harnessing the aliasing suppression capabilities of such sampling schemes, it is shown that certain processing tasks, namely spectrum sensing, can be performed at significantly low sampling rates compared to those demanded by uniform-sampling-based digital signal processing. The latter imposes sampling frequencies of at least twice the monitored bandwidth regardless of the spectral activity within. Aliasing can otherwise result in irresolvable processing problems, as the spectral support of the present signal is a priori unknown. Lower sampling rates exploit the processing module(s) resources (such as power) more efficiently and avoid the possible need for premium specialised high-cost DSP, especially if the handled bandwidth is considerably wide. A number of randomised sampling schemes are examined and appropriate spectral analysis tools are used to furnish their salient features. The adopted periodogram-type estimators are tailored to each of the schemes and their statistical characteristics are assessed for stationary, and cyclostationary signals. Their ability to alleviate the bandwidth limitation of uniform sampling is demonstrated and the smeared-aliasing defect that accompanies randomised sampling is also quantified. In employing the aforementioned analysis tools a novel wideband spectrum sensing approach is introduced. It permits the simultaneous sensing of a number of nonoverlapping spectral subbands constituting a wide range of monitored frequencies. The operational sampling rates of the sensing procedure are not limited or dictated by the overseen bandwidth antithetical to uniform-sampling-based techniques. Prescriptive guidelines are developed to ensure that the proposed technique satisfies certain detection probabilities predefined by the user. These recommendations address the trade-off between the required sampling rate and the length of the signal observation window (sensing time) in a given scenario. Various aspects of the introduced multiband spectrum sensing approach are investigated and its applicability highlighted

Estimation of Fourier Transform Using Alias-free Hybrid-Stratified Sampling

This paper proposes a novel method of estimating the Fourier Transform (FT) of deterministic, continuous-time signals, from a finite number \u1d441 of their samples taken from a fixed-length observation window. It uses alias-free hybrid-stratified sampling to probe the processed signal at a mixture of deterministic and random time instants. The FT estimator, specifically designed to work with this sampling scheme, is unbiased, consistent and fast converging. It is shown that if the processed signal has continuous third derivative, then the estimator's rate of uniform convergence in mean square is \u1d441^−5. Therefore, in terms of frequency-independent upper bounds on the FT estimation error, the proposed approach significantly outperforms existing estimators that utilize alias-free sampling, such as total random, stratified sampling, and antithetical stratified whose rate of uniform convergence is \u1d441^−1. It is proven here that \u1d441^−1 is a guaranteed minimum rate for all stratified-sampling-based estimators satisfying four weak conditions formulated in this paper. Owing to the alias-free nature of the sampling scheme, no constraints are imposed on the spectral support of the processed signal or the frequency ranges for which the Fourier Transform is estimated

Evaluation of several reconstruction methods of bandlimited signals

In this paper we evaluate several methods of reconstructing signals from finite sets of their samples. A class of band-limited signals is considered. Both, noise-free and noisy cases are studied. The evaluation is performed by extensive simulations where different shapes and bandwidths of the reconstructing filters are examined. We demonstrate that if a fixed number of signal samples are used in the reconstruction, then the signal to noise ratio becomes the main factor limiting the quality of the reconstruction

A Novel Sub-Nyquist Fourier Transform Estimator Based on Alias-free Hybrid Stratified Sampling

This paper introduces a novel method of estimating theFourier transform of deterministic continuous-time signals from a finite number N of their nonuniformly spaced measurements. These samples, located at a mixture of deterministic and random time instants, are collected at sub-Nyquist rates since no constraints are imposed on either the bandwidth or the spectral support of the processed signal. It is shown that the proposed estimation approach converges uniformly for all frequencies at the rate N^−5 or faster. This implies that it significantly outperforms its alias-free-sampling-based predecessors, namely stratified and antithetical stratified estimates, which are shown to uniformly convergence at a rate of N^−1. Simulations are presented to demonstrate the superior performance and low complexity of the introduced technique

High-Order Hybrid Stratified Sampling: Fast Uniform-Convergence Fourier Transform Estimation

This paper considers the problem of estimating the Fourier transform of continuous-time signals from N nonuniformly collected observations. Here, we introduce a new class of Hybrid Stratified sampling scheme in conjunction with a suitable estimator, which can provide the rate of convergence of order \u1d7cf/\u1d475(\u1d7d0\u1d472+\u1d7d1) in the mean-square sense, for signals with \u1d472+\u1d7cf continuous derivatives. Most importantly, it is shown that this rate is not only faster, but also uniform and independent of the analysed frequency (unlike) compared with other existing random-sampling-based techniques. In this paper, we establish the statistical properties of the proposed approach and illustrate its performance analytically as well as numerically

Sum rules and dualities for generalized parton distributions: is there a holographic principle?

To leading order approximation, the physical content of generalized parton distributions (GPDs) that is accessible in deep virtual electroproduction of photons or mesons is contained in their value on the cross-over trajectory. This trajectory separates the t-channel and s-channel dominated GPD regions. The underlying Lorentz covariance implies correspondence between these two regions through their relation to GPDs on the cross-over trajectory. This point of view leads to a family of GPD sum rules which are a quark analogue of finite energy sum rules and it guides us to a new phenomenological GPD concept. As an example, we discuss the constraints from the JLab/Hall A data on the dominant u-quark GPD H. The question arises whether GPDs are governed by some kind of holographic principle.Comment: 45 pages, 4 figures, Sect. 2 reorganized for clarity. Typos in Eq. (20) corrected. 4 new refs. Matches published versio

The Cholecystectomy As A Day Case (CAAD) Score: A Validated Score of Preoperative Predictors of Successful Day-Case Cholecystectomy Using the CholeS Data Set

Background Day-case surgery is associated with significant patient and cost benefits. However, only 43% of cholecystectomy patients are discharged home the same day. One hypothesis is day-case cholecystectomy rates, defined as patients discharged the same day as their operation, may be improved by better assessment of patients using standard preoperative variables. Methods Data were extracted from a prospectively collected data set of cholecystectomy patients from 166 UK and Irish hospitals (CholeS). Cholecystectomies performed as elective procedures were divided into main (75%) and validation (25%) data sets. Preoperative predictors were identified, and a risk score of failed day case was devised using multivariate logistic regression. Receiver operating curve analysis was used to validate the score in the validation data set. Results Of the 7426 elective cholecystectomies performed, 49% of these were discharged home the same day. Same-day discharge following cholecystectomy was less likely with older patients (OR 0.18, 95% CI 0.15–0.23), higher ASA scores (OR 0.19, 95% CI 0.15–0.23), complicated cholelithiasis (OR 0.38, 95% CI 0.31 to 0.48), male gender (OR 0.66, 95% CI 0.58–0.74), previous acute gallstone-related admissions (OR 0.54, 95% CI 0.48–0.60) and preoperative endoscopic intervention (OR 0.40, 95% CI 0.34–0.47). The CAAD score was developed using these variables. When applied to the validation subgroup, a CAAD score of ≤5 was associated with 80.8% successful day-case cholecystectomy compared with 19.2% associated with a CAAD score >5 (p < 0.001). Conclusions The CAAD score which utilises data readily available from clinic letters and electronic sources can predict same-day discharges following cholecystectomy

The effect of cyclostationarity on a DASP-based spectrum sensing method

In this paper we analyse and quantify the damage to the quality of spectrum estimation of discrete-time signals when a finite number of the signal samples are lost. We assume that the positions of the lost samples, of otherwise uniformly sampled signal, are random. We modify a DTFT-based spectral estimator to remove bias from the spectral analysis. Then we derive the standard deviation of the estimator and use it as the measure of accuracy. Simulation results confirm validity of the results presented in this paper