Showing papers on "Signal-to-noise ratio published in 2002"

A statistical-mechanics approach to large-system analysis of CDMA multiuser detectors

Abstract: We present a theory, based on statistical mechanics, to evaluate analytically the performance of uncoded, fully synchronous, randomly spread code-division multiple-access (CDMA) multiuser detectors with additive white Gaussian noise (AWGN) channel, under perfect power control, and in the large-system limit. Application of the replica method, a tool developed in the literature of statistical mechanics, allows us to derive analytical expressions for the bit-error rate, as well as the multiuser efficiency, of the individually optimum (IO) and jointly optimum (JO) multiuser detectors over the whole range of noise levels. The information-theoretic capacity of the randomly spread CDMA channel and the performance of decorrelating and linear minimum mean-square error (MMSE) detectors are also derived in the same replica formulation, thereby demonstrating validity of the statistical-mechanical approach.

Optimal speech enhancement under signal presence uncertainty using log-spectral amplitude estimator

Abstract: We present an optimally modified log-spectral amplitude estimator, which minimizes the mean-square error of the log-spectra for speech signals under signal presence uncertainty. We propose an estimator for the a priori signal-to-noise ratio (SNR), and introduce an efficient estimator for the a priori speech absence probability. Speech presence probability is estimated for each frequency bin and each frame by a soft-decision approach, which exploits the strong correlation of speech presence in neighboring frequency bins of consecutive frames. Objective and subjective evaluation confirm superiority in noise suppression and quality of the enhanced speech.

Speech enhancement using MMSE short time spectral estimation with gamma distributed speech priors

Abstract: In this paper we consider optimal estimators for speech enhancement in the Discrete Fourier Transform (DFT) domain. We present an analytical solution for estimating complex DFT coefficients in the MMSE sense when the clean speech DFT coefficients are Gamma distributed and the DFT coefficients of the noise are Gaussian or Laplace distributed. Compared to the state-of-the-art Wiener or MMSE short time amplitude estimators the new estimators deliver improved signal-to-noise ratios. When the noise model is a Laplacian density the enhanced speech shows less annoying random fluctuations in the residual noise than for a Gaussian density.

Method for controlling array antenna equipped with a plurality of antenna elements, method for calculating signal to noise ratio of received signal, and method for adaptively controlling radio receiver

Abstract: Based on a received signal y(t) received by a radiating element of an array antenna including the single radiating element and a plurality of parasitic elements, an adaptive controller calculates and sets a reactance value of a variable reactance element for directing a main beam of the array antenna in a direction of a desired wave and directing nulls in directions of interference waves so that a value of an objective function expressed by only the received signal y(t) becomes either one of the maximum and the minimum by using an iterative numerical solution of a nonlinear programming method.

Fast estimation of weak bio-signals using novel algorithms for generating multiple additional data frames

Abstract: A method and apparatus for de-noising weak bio-signals having a relatively low signal to noise ratio utilizes an iterative process of de-noising a data set comprised of a new set of frames. The method separately performs a non-linear de-noising operation on each of the component frames and combines the resultant de-noised frames to form a combined resultant de-noised input signal. The method is preferably carried out in a digital processor.

Optimum scan for fixed-wireless smart antennas

Abstract: Events determine the timing of when to change performance, for example when to scan or when to use a prior stored usually best-performance configuration or just a last configuration, for a smart antenna in a fixed or almost fixed usage like a wireless local area network and a television system. Thereby the system maintains unchanged the parameters, such as those that determine the beam form of the smart antenna until monitoring recognizes one or a combination of more than one of the following conditions or event occurrences; the device communicate with another device for the first time; reboot of the device or the device turns on; the received signal exceeds a predetermined bit error rate (BER); the received signal strength indicator (RSSI) is less than a determined RSSI; the received signal goes below a predetermined signal to noise ratio (SNR); and a user's demand. The performance is changed by changing of the communication parameters, for example: the previous measured configuration data to reduce the scan area and reduces the scan time; control of the transmission power of the communicating device to maintain performance or quality; channel selection to minimize collision in the transmission; switching to the another antenna; change the data rate; and change the modulation scheme. Maintaining the communication with another antenna during the scan of one smart antenna is another key point.

Turbo-equalization for multilevel modulation: an efficient low-complexity scheme

Abstract: This paper addresses the problem of iterative equalization and decoding (turbo-equalization) when bit-interleaved multilevel modulations are considered. The goal is to propose an efficient low-complexity solution in this context, where optimal turbo-equalization is totally untractable. Therefore, we generalize reduced-complexity soft-in/soft-out (SISO) equalizers based on the minimum mean square error (MMSE) criterion (originally proposed in a BPSK context) to this particular scheme. Performances are illustrated through simulations. We show the influence of the mapping on the signal-to-noise ratio (SNR) threshold and on asymptotic performances, and link the obtained results to iterative demodulation and decoding on an additive white Gaussian noise (AWGN) channel.

Estimation of Modal Decay Parameters from Noisy Response Measurements

Abstract: The estimation of modal decay parameters from noisy measurements of reverberant and resonnating systems is a common problem in audio and acoustics, such as in room and concert han measurements or musical instrument modeling. Reliable methods to estimate the initial onse level, decay rate, and noise floor level from noisy measurement data are studied and compared. A new method, based on the nonlinear optimization of a model for exponential decay plus stationary noise floor, is presented. A comparison with traditional decay parameter estimation techniques using simulated measurement data shows that the proposed method outperforms in accuracy and robustness, especially in extreme SNR conditions. Three cases of practical applications of the method are demonstrated.

A dual‐energy subtraction technique for microcalcification imaging in digital mammography—A signal‐to‐noise analysis

Abstract: Breast cancer may manifest as microcalcifications (microCs) in x-ray mammography. However, the detection and visualization of microCs are often obscured by the overlapping tissue structures. The dual-energy subtraction imaging technique offers an alternative approach for imaging and visualizing microCs. With this technique, separate high- and low-energy images are acquired and their differences are used to "cancel" out the background tissue structures. However, the subtraction process could increase the statistical noise level relative to the calcification contrast. Therefore, a key issue with the dual-energy subtraction imaging technique is to weigh the benefit of removing the cluttered background tissue structure over the drawback of reduced signal-to-noise ratio in the subtracted microC images. In this report, a theoretical framework for calculating the (quantum) noise in the subtraction images is developed and the numerical computations are described. We estimate the noise levels in the dual-energy subtraction signals under various imaging conditions, including the x-ray spectra, microC size, tissue composition, and breast thickness. The selection of imaging parameters is optimized to evaluate the feasibility of using a dual-energy subtraction technique for the improved detection and visualization of microCs. We present the results and discuss its dependence on imaging parameters.

Effect of channel estimation error in OFDM-based WLAN

Abstract: We examine the performance degradation due to the channel estimation error in orthogonal frequency division multiplexing (OFDM)-based wireless LAN (WLAN). The average effective SNR and average bit error probabilities (BEPs) are derived in a Rayleigh fading channel.

Non-data-aided signal-to-noise-ratio estimation

Abstract: Non-data-aided (NDA) signal-to-noise-ratio (SNR) estimation is considered for binary phase shift keying systems where the data samples are governed by a normal mixture distribution. Inherent estimation accuracy limitations are examined via a simple, closed-form approximation to the associated Cramer-Rao bound which eliminates the need for numerical integration. The expectation-maximization algorithm is proposed to iteratively maximize the NDA likelihood function. Simulation results show that the resulting estimator offers statistical efficiency over a wider range of scenarios than previously published methods.

Active sonar detection in shallow water using the Page test

Abstract: The use of active sonar in shallow water results in received echoes that may be considerably spread in time compared to the resolution of the transmitted waveform. The duration and structure of the spreading and the time of occurrence of the received echo are unknown without accurate knowledge of the environment and a priori information on the location and reflection properties of the target. A sequential detector based on the Page test is proposed for the detection of time-spread active sonar echoes. The detector also provides estimates of the starting and stopping times of the received echo. This signal segmentation is crucial to allow further processing such as more accurate range and bearing localization, depth localization, or classification. The detector is designed to exploit the time spreading of the received echo and is tuned as a function of range to the expected signal-to-noise ratio (SNR) as determined by the transmitted signal power, transmission loss, approximate target strength, and the estimated noise background level. The theoretical false alarm and detection performance of the proposed detector, the standard Page test, and the conventional thresholded matched filter detector are compared as a function of range, echo duration, SNR, and the mismatch between the actual and assumed SNR. The proposed detector and the standard Page test are seen to perform better than the conventional thresholded matched filter detector as soon as the received echo is minimally spread in time. The use of the proposed detector and the standard Page test in active sonar is illustrated with reverberation data containing target-like echoes from geological features, where it was seen that the proposed detector was able to suppress reverberation generated false alarms that were detected by the standard Page test.

A signal-to-noise analysis of multifocal VEP responses: an objective definition for poor records.

Abstract: Sixty local VEP records, called the multifocal VEP (mfVEP), can be obtained over a wide retinal area. From subject-to-subject, from day-to-day, and from location-to-location, these records can vary in quality presenting a challenge to quantitative analyses. Here three procedures are described for specifying the quality of mfVEP recordings in terms of signal-to-noise ratios. Monocular mfVEPs were recorded in two, 7-min runs. A ‘2-run signal-to-noise ratio’ (2rSNR) was obtained as {[RMS(RunA+RunB)]/[RMS(RunA–RunB)]}–1, where RMS is the root-mean-square amplitude of the response over the period from 45 to 150 ms (signal window). Two ‘noise-window signal-to-noise ratios’ were obtained with the same numerator as the 2rSNR but with the denominators based upon the RMS of a signal-free window from 325 to 430 ms. In one case, inSNR, the denominator was the RMS of the record's noise window and in the other case, mnSNR, the denominator was the mean of the RMS amplitudes of all the signal-free noise windows for the subject. The SNRs were related to false-positive rates (i.e., detecting a signal when none was present) by recording mfVEPs with some of the sectors of the display occluded. In particular, the outer three rings (36 sectors) of the display were occluded so that only noise was recorded; false-positive rates for different values of SNR were calculated. The 2rSNR had the highest false-positive rate largely due to alpha in the records of some subjects. The mnSNR had a lower false-positive rate than did the inSNR because there was little correlation between the RMS of the noise in the signal-free window and the RMS of the noise within the signal window. Use of the mnSNR is recommended over the 2rSNR, especially where alpha contamination can not be eliminated. Ways to improve the SNR of the records are discussed.

A novel adaptive beamforming algorithm for antenna array CDMA systems with strong interferers

Abstract: Blind beamforming based on the maximum signal-to-noise ratio (MSNR) can improve the performance of an array system only when the processing gain of the given code-division multiple-access (CDMA) system is high enough such that the desired signal can become dominant after despreading (see Choi, S. and Shim, D., IEEE Trans. Veh. Technol., vol.49, p.1793-1806, 2000; Choi, S. and Yun, D., IEEE Trans. Antennas Propagat., vol.45, p.1393-1404, 1997). We consider a maximum signal-to-interference-plus-noise ratio (MSINR) beamforming. The MSINR performance criterion is chosen to deal with strong interferers effectively. It is shown that blind MSINR beamforming is possible by directly utilizing the input and output signals of correlators of the CDMA systems. In addition, we propose an adaptive beamforming algorithm at a lower computational complexity - about O(7.5N) - where N is the number of antenna elements of the array system. Simulation results are presented in various signal environments to show the performance of the proposed adaptive algorithm.

Non-linear transformations of the feature space for robust Speech Recognition

Abstract: The noise usually produces a non-linear distortion of the feature space considered for Automatic Speech Recognition. This distortion causes a mismatch between the training and recognition conditions which significantly degrades the performance of speech recognizers. In this contribution we analyze the effect of the additive noise over cepstral based representations and we compare several approaches to compensate this effect. We discuss the importance of the non-linearities introduced by the noise and we propose a method (based on the histogram equalization technique) specifically oriented to the compensation of the non-linear transformation caused by the additive noise. The proposed method has been evaluated using the AURORA-2 database and task. The recognition results show significant improvements with respect to other compensation methods reported in the bibliography and reveals the importance of the non-linear effects of the noise and the utility of the proposed method.

On the outage probability of optimum combining and maximal ratio combining schemes in an interference-limited Rice fading channel

Abstract: In this letter, we study the performance of optimum combining (OC) and maximal ratio combining (MRC) diversity schemes in wireless digital communication systems with Rice fading and cochannel interference. New simplified closed-form expressions are derived for the probability density function (pdf) as well as the outage probability for OC and MRC when the desired signal has a line of sight and the interferers are assumed to be scattered and further away from the receiver. It is assumed that the interferers have equal powers and their number (L) is larger than the diversity order (M), i.e., L>M.

Adaptive filtering of evoked potentials with radial-basis-function neural network prefilter

Abstract: Evoked potentials (EPs) are time-varying signals typically buried in relatively large background noise. To extract the EP more effectively from noise, we had previously developed an approach using an adaptive signal enhancer (ASE) (Chen et al., 1995). ASE requires a proper reference input signal for its optimal performance. Ensemble- and moving window-averages were formerly used with good results. In this paper, we present a new method to provide even more effective reference inputs for the ASE. Specifically, a Gaussian radial basis function neural network (RBFNN) was used to preprocess raw EP signals before serving as the reference input. Since the RBFNN has built-in nonlinear activation functions that enable it to closely fit any function mapping, the output of RBFNN can effectively track the signal variations of EP. Results confirmed the superior performance of ASE with RBFNN over the previous method.

Use of modified line encoding and low signal-to-noise ratio based signal processing to extend range of digital data transmission over repeaterless two-wire telephone link

Abstract: The range of digital data communication services, such as a basic rate 2B1Q ISDN channel, to customer premises located beyond the industry standard achievable range of a two-wire loop can be extended by increasing the capacity of the ISDN line code from two information bits per symbol to three information bits per symbol, so as to reduce the effective symbol rate, which is error correction encoded to an effective 4B1H line code for defining a sixteen level PAM signal waveform, and employing enhanced low signal-to-noise ratio signal processing techniques in both the transmitter and receiver to accommodate the increased insertion loss of the two-wire line resulting from its extended length. Such enhanced low signal-to-noise ratio signal processing techniques include a Tomlinson precoder in the transmitter, and an adaptive linear equalizer and a module unit in the receiver.

Asymmetric adaptive modulation in a wireless communication system

Abstract: On embodiment of the system and method provides asymmetric adaptive modulation which allows uplink and downlink subframes (304, 302, respectively) of data to be transmitted between a base station (102) and a CPE (104) with different modulation schemes, thus increasing the efficiency of downlink transmissions while maintaining the stability of uplink transmissions. In systems with multiple CPEs, each CPE (104) and base station (102) pair can independently select their uplink and downlink modulation techniques. The system and method are also adaptive in that they adjust the modulation schemes based on, for example, signal to noise ratio measurements or bit error rate measurements.

Directional signal and noise sensors for borehole electromagnetic telemetry system

Abstract: An electromagnetic borehole telemetry system providing improved signal to noise ratio. Adaptive filters use noise channels as references to remove noise from the signal channel. Directional detectors provide a signal channel with reduced noise content and improved noise channels with reduced signal content. Directional detectors may be magnetometers aligned with the magnetic field, or antennas aligned with the electric field, of signal or noise sources. Alignment may be performed by beam steering of the outputs of a three-channel detector, which may detect both signal and noise.

Averaged Q-factor method using amplitude histogram evaluation for transparent monitoring of optical signal-to-noise ratio degradation in optical transmission system

Abstract: Presents the averaged Q-factor method based on an amplitude histogram evaluation to monitor the optical signal quality of an optical transmission system. We examine several parameters of this method and provide direction to design a novel optical signal quality monitoring circuit.

Effect of atmospheric turbulence on bit-error rate in an on-off-keyed optical wireless system

Abstract: Atmospheric turbulence produces scintillation at an optical receiver, which leads to fading of the received signal. This fading affects the bit-error-rate (BER) of a digital signal in a way that depends on the depth of the fade, the decision threshold at the receiver, and the average signal-to-noise ratio. The degree of fading can be dramatically reduced by the use of a time-delayed diversity technique, which involves retransmission of the data stream after a short delay, and resynchronization of the received data streams.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Method of measuring position and orientation with improved signal to noise ratio

Abstract: A method of measuring position and orientation of an object in a space in six degrees of freedom includes a three axis transmitter transmitting a magnetic field to be received by a three axis receiver. The transmitter transmits a pulsed DC transmit waveform. The waveform is preferably a symmetrical square wave with distinct non-overlapping axes and signal processing is accomplished such that the integrator is reset at the start of the rising edge transient period, the coil output signal is integrated throughout the rising edge transient and steady state periods, and the integration result is measured at the end of the steady state period, for each axis. The result is dramatically enhanced signal to noise ratio. The timing of measurements is chosen to reduce eddy current distortion while providing improved compensation for drift of the sensor with respect to the Earth's stationary magnetic field.

Maximum-SNR spatial-temporal formatting designs for MIMO channels

Abstract: We consider a communication scenario involving an m /spl times/ n multiple input multiple output (MIMO) flat fading channel whose input is a symbol stream multiplied prior to transmission by an n /spl times/ n spatial-temporal formatting matrix X and whose output is fed into an m /spl times/ n linear combiner Z. We show how to choose the matrices X and Z to maximize the signal-to-noise ratio (SNR) of the linear combiner output data that are used for detection, under the total power constraint (TPC), the elemental power constraint (EPC), or the total and elemental power constraint (TEPC). The TEPC design (considered here for the first time) is shown to include the TPC and EPC designs (previously considered by the authors) as special cases and, hence, to provide a theoretically and practically interesting unifying framework. We make use of this framework to discuss various tradeoffs of the three space-time formatting designs considered, such as transmission rate and requirements for channel state information at the transmission side. Additionally, we show that the EPC design, which is the only one of the aforementioned designs that does not require channel information at the transmission side, is also the maximum SNR design in the worst channel case under a TPC.

The capacity of an UWB multiple-access communications system

Abstract: In this paper we compute the channel capacity of M-ary pulse position modulation ultra-wideband (UWB) communications over multiple-access channels. Under certain assumptions, the multiple-access noise component at the receiver can be modeled as Gaussian. An expression for the signal-to-noise ratio is developed for UWB utilizing rectangular pulses. The information theoretic capacity of the UWB system is expressed as a function of number of users. Utilizing the expressions developed, other trade-offs can be determined between the system parameters and capacity.

Microphone array post-filter for diffuse noise field

Abstract: This paper proposes a novel technique for estimating the signal power spectral density to be used in the transfer function of a microphone array post-filter. The technique is a modification of the existing Zelinski post-filter, which uses the auto- and cross-spectral densities of the array inputs to estimate the signal and noise spectral densities. The Zelinski technique, however, assumes zero cross-correlation between noise on different sensors. This assumption is inaccurate in real conditions, particularly at low frequencies and for arrays with closely spaced sensors. In this paper we replace this with an assumption of a theoretically diffuse noise field, which is more appropriate in a variety of realistic noise environments. In experiments using noise recordings from an office of computer workstations, the modified post-filter results in significant improvement in terms of objective speech quality measures and speech recognition performance.