Showing papers on "Signal-to-noise ratio published in 2001"

Antenna selection for spatial multiplexing systems based on minimum error rate

Abstract: Future cellular systems will employ spatial multiplexing with multiple antennas at both transmitter and receiver to take advantage of large capacity gains. In such systems it will be desirable to select a subset of available transmit antennas for link initialization, link maintenance, or handoff. In this paper we present a criteria for selecting the optimal antenna subset in terms of minimum error rate, when coherent receivers, either linear or maximum likelihood (ML), are used over a slowly varying channel. For the ML receiver we propose to pick the subset whose output constellation has the largest minimum Euclidean distance. For the linear receiver we propose use of the post-processing SNRs (signal to noise ratios) of the multiplexed streams whereby the antenna subset that induces the largest minimum SNR is chosen. Simulations demonstrate that our selection algorithms also provides diversity advantage thus making subset selection useful over fading channels.

Stochastic resonance as a collective property of ion channel assemblies

Abstract: By use of a stochastic generalization of the Hodgkin-Huxley model we investigate both the phenomena of stochastic resonance (SR) and coherence resonance (CR) in variable size patches of an excitable cell membrane. Our focus is on the challenge: how internal noise stemming from individual ion channels does affect collective properties of the whole ensemble. We investigate both an unperturbed situation with no applied stimuli and one in which the membrane is stimulated externally by a periodic signal and additional external noise. For the nondriven case, we demonstrate the existence of an optimal size of the membrane patch for which the internal noise causes a most regular spike activity. This phenomenon shall be termed intrinsic CR. In the presence of an applied periodic stimulus, we demonstrate that the signal-to-noise ratio (SNR) exhibits SR vs. decreasing patch size, or vs. increasing internal noise strength, respectively. Moreover, we demonstrate that conventional SR vs. the external noise intensity occurs only for sufficiently large membrane patches, when the intensity of internal noise is below its optimal level. Thus, biological SR is seemingly rooted in the collective properties of large ion channel ensembles rather than in the individual stochastic dynamics of single ion channels.

Soft digital signal processing

Abstract: In this paper, we propose a framework for low-energy digital signal processing (DSP), where the supply voltage is scaled beyond the critical voltage imposed by the requirement to match the critical path delay to the throughput. This deliberate introduction of input-dependent errors leads to degradation in the algorithmic performance, which is compensated for via algorithmic noise-tolerance (ANT) schemes. The resulting setup that comprises of the DSP architecture operating at subcritical voltage and the error control scheme is referred to as soft DSP. The effectiveness of the proposed scheme is enhanced when arithmetic units with a higher "delay imbalance" are employed. A prediction-based error-control scheme is proposed to enhance the performance of the filtering algorithm in the presence of errors due to soft computations. For a frequency selective filter, it is shown that the proposed scheme provides 60-81% reduction in energy dissipation for filter bandwidths up to 0.5 /spl pi/ (where 2 /spl pi/ corresponds to the sampling frequency f/sub s/) over that achieved via conventional architecture and voltage scaling, with a maximum of 0.5-dB degradation in the output signal-to-noise ratio (SNR/sub o/). It is also shown that the proposed algorithmic noise-tolerance schemes can also be used to improve the performance of DSP algorithms in presence of bit-error rates of up to 10/sup -3/ due to deep submicron (DSM) noise.

Equalization for discrete multitone transceivers to maximize bit rate

Abstract: In a discrete multitone receiver, a time-domain equalizer (TEQ) reduces the intersymbol interference (ISI) by shortening the effective duration of the channel impulse response. Current TEQ design methods such as the minimum mean-squared error (MMSE), maximum shortening SNR (MSSNR), and maximum geometric SNR (MGSNR) do not directly maximize bit rate. We develop two TEQ design methods to maximize the bit rate. First, we partition an equalized multicarrier channel into its equivalent signal, noise, and ISI paths to develop a new subchannel SNR definition. Then, we derive a nonlinear function of TEQ taps that measures the bit rate, which the proposed maximum bit rate (MBR) method optimizes. We also propose a minimum-ISI method that generalizes the MSSNR method by weighting the ISI in the frequency domain to obtain higher performance. The minimum-ISI method is amenable to real-time implementation on a fixed-point digital signal processor. Based on simulations using eight different carrier-serving-area loop channels, (1) the proposed methods yield higher bit rates than MMSE, MGSNR, and MSSNR methods; (2) the proposed methods give three-tap TEQs with higher bit rates than 17-tap MMSE, MGSNR, and MSSNR TEQs; (3) the proposed MBR method achieves the channel capacity (as computed by the matched filter bound using the proposed subchannel SNR model) with a five-tap TEQ; and (4) the proposed minimum-ISI method achieves the bit rate of the optimal MBR method.

The Estimation and Tracking of Frequency

Abstract: Many electronic and acoustic signals can be modelled as sums of sinusoids and noise. However, the amplitudes, phases and frequencies of the sinusoids are often unknown and must be estimated in order to characterise the periodicity or near-periodicity of a signal and consequently to identify its source. This book presents and analyses several practical techniques used for such estimation. The problem of tracking slow frequency changes over time of a very noisy sinusoid is also considered. Rigorous analyses are presented via asymptotic or large sample theory, together with physical insight. The book focuses on achieving extremely accurate estimates when the signal to noise ratio is low but the sample size is large. Each chapter begins with a detailed overview, and many applications are given. Matlab code for the estimation techniques is also included. The book will thus serve as an excellent introduction and reference for researchers analysing such signals.

Analysis of transmit-receive diversity in Rayleigh fading

Abstract: We analyze the error performance of a wireless communication system employing transmit-receive diversity in Rayleigh fading. By focussing on the complex Gaussian statistics of the independent and identically distributed entries of the channel matrix, we derive a formula for the characteristic function (cf) of the maximum output signal-to-noise ratio (SNR). We use this cf to obtain a closed-form expression of the symbol error probability (SEP) for coherent binary keying. An approximate expression for the SEP when the average SNR per branch is large is also obtained. The method can be easily extended to obtain the SEP of M-ary modulation schemes.

Maximum likelihood methods for bearings-only target localization

Abstract: We develop four maximum likelihood (ML) methods to localize a moving target using a network of acoustical sensor arrays. Each array transmits a direction-of-arrival (DOA) estimate to a central processor, which employs one of the localization techniques. The four ML approaches use different target signal models where the time retardation factor for the target position and the degradation of the target signal through the air may or may not be included in the model. We compare these methods along with a linear least squares approach through a number of simulations at various signal to noise levels.

Noise correction for the exact determination of apparent diffusion coefficients at low SNR.

Abstract: Noise in MR image data increases the mean signal intensity of image regions due to the usually performed magnitude reconstruction. Diffusion-weighted MR imaging (DWI) is especially affected by high noise levels for several reasons, and a decreasing SNR at increasing diffusion weighting causes systematic errors when calculating apparent diffusion coefficients (ADCs). Two different methods are presented to correct biased signal intensities due to the presence of complex noise with (a) a Gaussian intensity distribution and (b) an arbitrary intensity distribution. The performance of the correction schemes is demonstrated by numerical simulations and DWI measurements on two different MR systems with different noise characteristics. These experiments show that noise significantly influences the determination of ADCs. Applying the proposed corrections schemes reduced the bias of the determined ADC to less than 10 % of the bias without correction.

Projection-based image registration in the presence of fixed-pattern noise

Abstract: A computationally efficient method for image registration is investigated that can achieve an improved performance over the traditional two-dimensional (2-D) cross-correlation-based techniques in the presence of both fixed-pattern and temporal noise. The method relies on transforming each image in the sequence of frames into two vector projections formed by accumulating pixel values along the rows and columns of the image. The vector projections corresponding to successive frames are in turn used to estimate the individual horizontal and vertical components of the shift by means of a one-dimensional (1-D) cross-correlation-based estimator. While gradient-based shift estimation techniques are computationally efficient, they often exhibit degraded performance under noisy conditions in comparison to cross-correlators due to the fact that the gradient operation amplifies noise. The projection-based estimator, on the other hand, significantly reduces the computational complexity associated with the 2-D operations involved in traditional correlation-based shift estimators while improving the performance in the presence of temporal and spatial noise. To show the noise rejection capability of the projection-based shift estimator relative to the 2-D cross correlator, a figure-of-merit is developed and computed reflecting the signal-to-noise ratio (SNR) associated with each estimator. The two methods are also compared by means of computer simulation and tests using real image sequences.

An experimentalist's approach to accurate localization of phase singularities during reentry.

Abstract: A phase variable that uniquely represents the time course of the action potential has been used to study the mechanisms of cardiac fibrillation. A spatial phase singularity (PS) occurs during reentrant wave propagation and represents the organizing center of the rotating wave. Here, we present an error analysis to investigate how well PSs can be localized. Computer simulations of rotating spiral waves scaled appropriately for cardiac tissue were studied with various levels of noise added. The accuracy in identifying and localizing singularities depended on three factors: (i) the point chosen as the origin in state space used to calculate the phase variable; (ii) signal to noise ratio; and (iii) discretization (number of levels used to represent data). We found that for both simulation as well as experimental data, there existed a wide range for the choice of origin for which PSs could be identified. Discretization coupled with noise affected this range adversely. However, there always existed a range for choice of the origin that was 20% or more of the action potential amplitude within which the accuracy of localizing PSs was better than 2 mm. Thus, a precise determination of origin was not necessary for accurately identifying PSs. © 2001 Biomedical Engineering Society. PAC01: 8719Nn, 8710+e, 8719Hh

Frequency decomposition and compounding of ultrasound medical images with wavelet packets

Abstract: Ultrasound beams propagating in biological tissues undergo distortions due to local inhomogeneities of the acoustic parameters and the nonlinearity of the medium. The spectral analysis of the radio-frequency (RF) backscattered signals may yield important clinical information in the field of tissue characterization, as well as enhancing the detectability of tissue parenchymal diseases. Here, the authors propose a new tissue spectral imaging technique based on the wavelet packets (WP) decomposition. In a conventional ultrasound imaging system, the received echo-signals are generally decimated to generate a medical image, with a loss of information. With the proposed approach, all the RF data are processed to generate a set of frequency subband images. The ultrasound echo signals are simultaneously frequency decomposed and decimated, by using two quadrature mirror filters, followed by a dyadic subsampling. In addition, to enhance the lesion detectability and the image quality, the authors apply a nonlinear filter to reduce noise in each subband image. The proposed method requires simple additional signal processing and it can be implemented on any real-time imaging system. The frequency subband images, which are available simultaneously, can be either used in a multispectral display or summed up together to reduce speckle noise. To localize the different frequency response in the tissues, the authors propose a multifrequency display method where 3 different subband images, chosen among those available, are encoded as red, green, and blue intensities (RGB) to create a false-colored RGB image. According to the clinical application, different choices can evidence different spectral proprieties in the biological tissue under investigation. To enhance the lesion contrast in a grey-level image, one of the possible methods is the summation of the images obtained from narrow frequency subbands, according to the frequency compounding technique. The authors show that by adding the denoised subband images created with the WP decomposition, the contrast-to-noise ratio in 2 phantom images is largely increased.

Optimal coded aperture patterns for improved SNR in nuclear medicine imaging

Abstract: During a Nuclear Medicine project that called for the optimal design of a coded aperture we found that lowthroughput masks do not always provide a Signal-to-Noise Ratio (SNR) advantage. In this paper, we present the simulations of the performance of some coded aperture patterns chosen from different families and compare the results with theoretical predictions. A general expression for the SNR and its particular form for different patterns are provided. The choice of the optimal pattern family is discussed with reference to the characteristics of the object to be imaged and in light of the effect of near-field artifacts. No-Two-Holes-Touching (NTHT) arrays based on Modified Uniformly Redundant Arrays (MURAs) proved to offer the best compromise between SNR performance and practical fabrication constraints. r 2001 Elsevier Science B.V. All rights reserved.

Scale-based diffusive image filtering preserving boundary sharpness and fine structures

Abstract: Image acquisition techniques often suffer from low signal-to-noise ratio (SNR) and/or contrast-to-noise ratio (CNR). Although many acquisition techniques are available to minimize these, post acquisition filtering is a major off-line image processing technique commonly used to improve the SNR and CNR. A major drawback of filtering is that it often diffuses/blurs important structures along with noise. Here, the authors introduce two scale-based filtering methods that use local structure size or "object scale" information to arrest smoothing around fine structures and across even low-gradient boundaries. The first of these methods uses a weighted average over a scale-dependent neighborhood while the other employs scale-dependent diffusion conductance to perform filtering. Both methods adaptively modify the degree of filtering at any image location depending on local object scale. Object scale allows the authors to accurately use a restricted homogeneity parameter for filtering in regions with fine details and in the vicinity of boundaries while a generous parameter in the interiors of homogeneous regions. Qualitative experiments based on both phantoms and patient magnetic resonance images show significant improvements using the scale-based methods over the extant anisotropic diffusive filtering method in preserving fine details and sharpness of object boundaries. Quantitative analyses utilizing 25 phantom images generated under a range of conditions of blurring, noise, and background variation confirm the superiority of the new scale-based approaches.

Joint source-channel decoding of correlated sources over noisy channels

Abstract: We consider the case of two correlated binary information sequences. Instead of compressing the information using source coding, both sequences are independently channel encoded, and transmitted over an AWGN channel. The correlation between both sequences is exploited at the receiver, allowing reliable communications at signal to noise ratios very close to the theoretical limits established by the combination of Shannon and Slepian-Wolf theorems.

Space-time autocoding

Abstract: Prior treatments of space-time communications in Rayleigh flat fading generally assume that channel coding covers either one fading interval-in which case there is a nonzero "outage capacity"-or multiple fading intervals-in which case there is a nonzero Shannon capacity. However, we establish conditions under which channel codes span only one fading interval and yet are arbitrarily reliable. In short, space-time signals are their own channel codes. We call this phenomenon space-time autocoding, and the accompanying capacity the space-time autocapacity. Let an M-transmitter antenna, N-receiver antenna Rayleigh flat fading channel be characterized by an M/spl times/N matrix of independent propagation coefficients, distributed as zero-mean, unit-variance complex Gaussian random variables. This propagation matrix is unknown to the transmitter, it remains constant during a T-symbol coherence interval, and there is a fixed total transmit power. Let the coherence interval and number of transmitter antennas be related as T=/spl beta/M for some constant /spl beta/. A T/spl times/M matrix-valued signal, associated with R/spl middot/T bits of information for some rate R is transmitted during the T-symbol coherence interval. Then there is a positive space-time autocapacity C/sub a/ such that for all R

Maximum-likelihood expectation-maximization reconstruction of sinograms with arbitrary noise distribution using NEC-transformations

Abstract: The maximum-likelihood (ML) expectation-maximization (EM) [ML-EM] algorithm is being widely used for image reconstruction in positron emission tomography. The algorithm is strictly valid if the data are Poisson distributed. However, it is also often applied to processed sinograms that do not meet this requirement. This may sometimes lead to suboptimal results: streak artifacts appear and the algorithm converges toward a lower likelihood value. As a remedy, the authors propose two simple pixel-by-pixel methods [noise equivalent counts (NEC)-scaling and NEC-shifting] in order to transform arbitrary sinogram noise into noise which is approximately Poisson distributed (the first and second moments of the distribution match those of the Poisson distribution). The convergence speed associated with both transformation methods is compared, and the NEC-scaling method is validated with both simulations and clinical data. These new methods extend the ML-EM algorithm to a general purpose nonnegative reconstruction algorithm.

Estimation of respiration-induced noise fluctuations from undersampled multislice fMRI data.

Abstract: Functional MRI time series data are known to be contaminated by highly structured noise due to physiological fluctuations. Significant components of this noise are at frequencies greater than those critically sampled in standard multislice imaging protocols and are therefore aliased into the activation spectrum, compromising the estimation of functional activations and the determination of their significance. However, in this work it is demonstrated that unaliased noise information is available in multislice data, and can be used to estimate and reduce noise due to high-frequency respiratory-related fluctuations. Magn Reson Med 45:635-644, 2001. Published 2001 Wiley-Liss, Inc.

Adaptive link quality management for wireless medium

Abstract: To provide the quality and reliability of a fiber optic link over a wireless link, network nodes in accordance with the present invention include a link quality management unit, which controls multiple transmission parameters of a wireless interface in response variable link conditions. For example, the link quality management unit of one embodiment of the present invention controls transmission power, modulation, and error correction. In general, a receiving network node provides feedback to a transmitting network node. Thus, in many embodiments of the present invention, the link quality management unit includes a signal quality detector, which measures a signal quality value, such as bit error rate, signal to noise ratio, or error vector magnitude. The measured signal quality is transmitted back to the transmitting node so that appropriate changes can be made to the transmission parameters.

Robust speech/non-speech detection using LDA applied to MFCC

Abstract: In speech recognition, speech/non-speech detection must be robust to,noise. In the paper, a method for speech/non-speech detection using a linear discriminant analysis (LDA) applied to mel frequency cepstrum coefficients (MFCC) is presented. The energy is the most discriminant parameter between noise and speech. But with this single parameter, the speech/non-speech detection system detects too many noise segments. The LDA applied to MFCC and the associated test reduces the detection of noise segments. This new algorithm is compared to the one based on signal to noise ratio (Mauuary and Monne, 1993).

Accuracy limits in the determination of absolute optical properties using time-resolved NIR spectroscopy.

Abstract: We assess typical systematic experimental errors involved in a time-resolvedmeasurement as applied to NIR diffuse optical spectroscopy and investigate their effect on the quantification accuracy of the absorption and the reduced scattering coefficient. We demonstrate that common systematic experimental uncertainties may lead to quantification errors of 10% or more, even when excellent signal to noise ratio conditions exist and accurate photon propagation models are employed. We further demonstrate that the accuracy of the calculation depends nonlinearly on the optical properties of the medium measured. High scattering and low absorbing media can be quantified more accurately than media with low scattering or high absorption using measurements of the same signal to noise ratio. We further discuss curve-shape fitting schemes that aid in improving the quantification accuracy in the presence of experimental errors. Finally, we identify uncertainties that set quantification accuracy limits and we find temporal resolution as the ultimate limiting factor in the quantification accuracy achieved. Our findings suggest that temporal resolution of the order of 10 ps is necessary for quantifying the absorption and reduced scattering coefficient of diffuse media with accuracy better than 5% using curve fitting methods. In that sense this analysis can be used in time-resolved system design and in predicting the expected errors given the technology selected for time-resolvedmeasurements.

A comparison of data from airborne, semi-airborne, and ground electromagnetic systems

Abstract: The region around a small conductive massive sulfide body near Sudbury, Ontario, Canada, was used as a test site to compare airborne and ground electromagnetic (EM) systems with a new experimental EM system that uses a ground‐based transmitter and an airborne receiver. In this test survey, the semi‐airborne data were acquired with the transmitter loop used for the ground survey and the receiver normally used for the airborne system. At the time the data were acquired, there was no synchronization between the semi‐airborne receiver and the ground transmitter. However, subsequent digital processing of the full waveform data allowed the zero‐time position to be defined. The data could then be stacked and windowed. The ratio of the peak signal to the late‐time noise level for the airborne data is about 25:1, the semi‐airborne data shows signal‐to‐noise ratios of 500:1, while the signal‐to‐noise ratio for the ground data has a ratio of 50 000:1. This particular conductor is very close to the ground transmitter...

Averaging correlation for C/A code acquisition and tracking in frequency domain

Abstract: This paper describes a new software method called "averaging correlation" to do block level GPS C/A code acquisition and tracking in frequency domain with smaller FFT blocks. The method retains the signal to noise ratio observed in more expensive correlators. Frequency domain software processing will become more feasible and popular if this method is implemented in civil GPS receivers.

An ultra-sensitive pulsed balanced homodyne detector: Application to time-domain quantum measurements

Abstract: A pulsed balanced homodyne detector has been developed for precise measurements of electric field quadratures of pulsed optical quantum states. A high level of common mode suppression (> 85 dB) and low electronic noise (730 electrons per pulse) provide a signal to noise ratio of 14 dB for the measurement of the quantum noise of individual pulses. Measurements at repetition rates up to 1 MHz are possible. As a test, quantum tomography of the coherent state is performed and the Wigner function and the density matrix are reconstructed with a 99.5% fidelity. The detection system can also be used for ultrasensitive balanced detection in cw mode, e.g. for weak absorption measurements.

Information-theoretic assessment of sampled hyperspectral imagers

Abstract: This work focuses on estimating the information conveyed to a user by hyperspectral image data. The goal is establishing the extent to which an increase in spectral resolution enhances the amount of usable information. Indeed, a tradeoff exists between spatial and spectral resolution due to physical constraints of multi-band sensors imaging with a prefixed SNR. After describing an original method developed for the automatic estimation of variance and correlation of the noise introduced by hyperspectral imagers, lossless interband data compression is exploited to measure the useful information content of hyperspectral data. In fact, the bit rate achieved by the reversible compression process takes into account both the contribution of the "observation" noise (i.e., information regarded as statistical uncertainty, but whose relevance to a user is null) and the intrinsic information of radiance sampled and digitized through an ideally noise-free process. An entropic model of the decorrelated image source is defined and, once the parameters of the noise, assumed to be Gaussian and stationary, have been measured, such a model is inverted to yield an estimate of the information content of the noise-free source from the code rate. Results are reported and discussed on both simulated and AVIRIS data.

Mode controller for signal acquisition and tracking in an ultra wideband communication system

Abstract: A system and method for controlling the mode of operation in a UWB receiver. In one variation, the system and method determines the mode of operation by reading a set number of samples of the signal, estimating mode parameters, calculating a mode probability, and then transitioning in a finite state machine from either a tracking to an acquisition state or vice versa depending on the value of the mode probability. Exemplary versions of the mode controller include a signal to noise ratio calculator, a signal and noise power estimator, and an AGC initialization circuit.

Method for allocating bits and power in multi-carrier communication system

Abstract: A method of transmitting a data bit stream on a multi-carrier transmission system is provided. The steps include estimating a signal to noise ratio for each carrier for a known transmit power for each carrier, allocating a quantity of bits for each carrier within limits imposed by a target bit error rate and the estimated signal to noise ratio, computing a total excess power available for a current allocation of bits, computing additional power that would be required by each carrier to carry additional bits, and allocating the total excess power based on the computation of additional power required by each carrier to carry additional bits. The computation of additional power needed may be performed by computing the additional gain necessary to carry additional bits or by computing the additional excess power necessary to carry additional bits.

Array processing for nonstationary interference suppression in DS/SS communications using subspace projection techniques

Abstract: Combined spatial and time-frequency signatures of signal arrivals at a multisensor array are used for nonstationary interference suppression in direct-sequence spread-spectrum (DS/SS) communications. With random PN spreading code and deterministic nonstationary interferers, the use of antenna arrays offers increased DS/SS signal dimensionality relative to the interferers. Interference mitigation through a spatio-temporal subspace projection technique leads to reduced DS/SS signal distortion and improved performance over the case of a single antenna receiver. The angular separation between the interference and desired signals is shown to play a fundamental role in trading off the contribution of the spatial and time-frequency signatures to the interference mitigation process. The expressions of the receiver signal-to-interference-noise ratio (SINR) implementing subspace projections are derived, and numerical results are provided.

An arrhythmia detector and heart rate estimator for overnight polysomnography studies

Abstract: We present an algorithm for automatic on-line analysis of the ECG channel acquired during overnight polysomnography (PSG) studies. The system is independent of ECG morphology, requires no manual initialization, and operates automatically throughout the night. It highlights likely occurrences of arrhythmias and intervals of bad signal quality while outputting a continual estimate of heart rate. Algorithm performance is validated against standard ECG databases and PSG data. Results demonstrate a minimal false negative rate and a low false positive rate for arrhythmia detection, and robustness over a wide range of noise contamination.

Communication over Doppler spread channels. II. Receiver characterization and practical results

Abstract: For pt. I see ibid., vol. 25, no. 1, p. 62-72 (2000). A receiver for coherent communication through underwater communication channels is analyzed. The receiver performance and stability versus delay spread, Doppler spread, and signal-to-noise ratio is quantified. The stability is governed by the ill-conditioning of a correlation matrix estimate and it sets the limit on how many taps should be used for a channel with a given number of degrees of freedom. The receiver is used extensively on both simulated and real data that are Doppler spread, and good performance in these channels is verified.