Distribution Of Signal-to-noise Ratio Research Articles

Steady-Sensitivity Distributed Acoustic Sensors

Distributed acoustic sensors (DAS) based on phase-sensitive optical time-domain reflectometry (ϕOTDR) have demonstrated interesting performance for many applications ranging from seismology to pipeline protection. However, the sensitivity of traditional DAS relying on coherent detection is strongly dependent on the system noise and trace fading points, offering poor reliability of the results in the spatial dimension. In this manuscript, we evaluate the statistical performance of a recently proposed DAS technique, namely, chirped-pulse ϕOTDR, in terms of sensitivity and signal-to-noise ratio (SNR). Our results show behavioral trends that significantly differ from those of traditional DAS. In particular, the acoustic SNR distribution in chirped-pulse DAS is notably narrower than that in the traditional case, allowing to ensure a large system dynamic range across all the points of the optical trace. Hence, chirped-pulse ϕOTDR offers localized perturbation detection with very high reliability, almost independent of trace fading points, along the complete reachable range of the sensor.

Improving Data Quality for the Australian High Frequency Ocean Radar Network through Real-Time and Delayed-Mode Quality-Control Procedures

Quality-control procedures and their impact on data quality are described for the High-Frequency Ocean Radar (HFR) network in Australia, in particular for the commercial phased-array (WERA) HFR type. Threshold-based quality-control procedures were used to obtain radial velocity and signal-to-noise ratio (SNR), however, values were set through quantitative analyses with independent measurements available within the HFR coverage, when available, or from long-term data statistics. An artifact removal procedure was also applied to the spatial distribution of SNR for the first-order Bragg peaks, under the assumption the SNR is a valid proxy for radial velocity quality and that SNR decays with range from the receiver. The proposed iterative procedure was specially designed to remove anomalous observations associated with strong SNR peaks caused by the 50 Hz sources. The procedure iteratively fits a polynomial along the radial beam (1-D case) or a surface (2-D case) to the SNR associated with the radial velocity. Observations that exceed a detection threshold were then identified and flagged. After removing suspect data, new iterations were run with updated detection thresholds until no additional spikes were found or a maximum number of iterations was reached.

Characteristics of Real-World Signal to Noise Ratios and Speech Listening Situations of Older Adults With Mild to Moderate Hearing Loss.

The first objective was to determine the relationship between speech level, noise level, and signal to noise ratio (SNR), as well as the distribution of SNR, in real-world situations wherein older adults with hearing loss are listening to speech. The second objective was to develop a set of prototype listening situations (PLSs) that describe the speech level, noise level, SNR, availability of visual cues, and locations of speech and noise sources of typical speech listening situations experienced by these individuals. Twenty older adults with mild to moderate hearing loss carried digital recorders for 5 to 6 weeks to record sounds for 10 hours per day. They also repeatedly completed in situ surveys on smartphones several times per day to report the characteristics of their current environments, including the locations of the primary talker (if they were listening to speech) and noise source (if it was noisy) and the availability of visual cues. For surveys where speech listening was indicated, the corresponding audio recording was examined. Speech-plus-noise and noise-only segments were extracted, and the SNR was estimated using a power subtraction technique. SNRs and the associated survey data were subjected to cluster analysis to develop PLSs. The speech level, noise level, and SNR of 894 listening situations were analyzed to address the first objective. Results suggested that as noise levels increased from 40 to 74 dBA, speech levels systematically increased from 60 to 74 dBA, and SNR decreased from 20 to 0 dB. Most SNRs (62.9%) of the collected recordings were between 2 and 14 dB. Very noisy situations that had SNRs below 0 dB comprised 7.5% of the listening situations. To address the second objective, recordings and survey data from 718 observations were analyzed. Cluster analysis suggested that the participants' daily listening situations could be grouped into 12 clusters (i.e., 12 PLSs). The most frequently occurring PLSs were characterized as having the talker in front of the listener with visual cues available, either in quiet or in diffuse noise. The mean speech level of the PLSs that described quiet situations was 62.8 dBA, and the mean SNR of the PLSs that represented noisy environments was 7.4 dB (speech = 67.9 dBA). A subset of observations (n = 280), which was obtained by excluding the data collected from quiet environments, was further used to develop PLSs that represent noisier situations. From this subset, two PLSs were identified. These two PLSs had lower SNRs (mean = 4.2 dB), but the most frequent situations still involved speech from in front of the listener in diffuse noise with visual cues available. The present study indicated that visual cues and diffuse noise were exceedingly common in real-world speech listening situations, while environments with negative SNRs were relatively rare. The characteristics of speech level, noise level, and SNR, together with the PLS information reported by the present study, can be useful for researchers aiming to design ecologically valid assessment procedures to estimate real-world speech communicative functions for older adults with hearing loss.

Investigation of DC-Biased Optical OFDM With Precoding Matrix for Visible Light Communications: Theory, Simulations, and Experiments

Orthogonal frequency-division-multiplexing (OFDM) technology is widely used in visible light communication (VLC) to achieve high data rate transmission. However, the traditional direct-current (DC)-biased optical OFDM (DCO-OFDM) VLC systems suffer from the high peak-to-average power ratio (PAPR) which causes signal clipping distortion, and, thus, performance degradation. Furthermore, severe high-frequency fading due to the limited system bandwidth results in poor bit error rate (BER) performance. Precoding matrix (PM) techniques have been proposed to enhance the performance of VLC OFDM transmission, but a little or no work has been carried out in investigating the theory of PM used in OFDM VLC systems. In this paper, we aim to reveal the theory of PM-DCO-OFDM for a VLC system. To figure out the intrinsic laws of a PM method, we investigate the principles of PAPR reduction, clipping distortion optimization, and signal-to-noise ratio (SNR) distribution equalization. Based on the analysis of PAPR, we theoretically proved the simplicity of PM as a method to reduce the possibility of high PAPR by improving the autocorrelation performance of input symbols. The clipping distortion could be improved due to the reduction of high PAPR. Moreover, the relatively uniform SNR distribution can be achieved by PM through equalizing the clipping and channel noise, which is beneficial to improve the BER performance in high-frequency constrained systems. However, the PM method used in a DCO-OFDM VLC system should consider the transmitting power, modulation format, and transmission distance as a whole to achieve the transmission performance improvement. The simulation results demonstrate the complementary cumulative distribution function of PAPR can be reduced ∼3 dB, while the performance of clipping distortion power and clipping error probability are significantly improved. Furthermore, experiment is carried out with results showing that the PM method can improve the BER performance in the case that VLC OFDM transmission has enough transmitting power, but with the low transmitting power, the PM also can damage the BER performance. The simulation and experiment results are consistent with our theoretical analysis.

Energy Efficient Lighting System for Indoor Parking with Ubiquitous Communication

This paper presents visible light communication (VLC) based energy efficient lighting system in indoor parking area for illumination and at the same time would offer ubiquitous data communication. Light emitting diodes (LEDs) based VLC is used for communication and illumination at the same time. We have optimized the position of LED emitters on the ceiling in the parking area to obtain the desired signal-to-noise ratio (SNR) and bit error rate (BER). Two lighting configurations in the parking area are discussed. We compared the power transmission from LED emitters, number of emitters, SNR distribution, BER and cost for both the configurations. Multi-level pulse modulations are used in this work along with simple on off keying (OOK) for modulation. We compared OOK with M-PAM, multi-level pulse position modulation and invert multi-level pulse position modulation to obtain the required SNR and power to achieve the same BER. Simulation results are presented and discussed. It is observed that the system allows uniform illumination in the parking area and at the same time high data rate communication.

Design and Demonstration of Four-Channel Received Coil Arrays for Vertical-Field MRI

The layout of radio-frequency received coils is related to signal-to-noise ratio (SNR) in magnetic resonance imaging (MRI). In this paper, different structures of four-channel received coil arrays for vertical-field MRI are constructed and optimized by establishing the relationship between coil geometry and SNR to achieve a high SNR and a uniform SNR distribution in the region of interest (ROI). Then, the SNR distributions of three optimized configurations, including rectangular loops, non-definite shape surface coils, and solenoid loops as the main unit, are simulated and compared. The four-channel coil of solenoid loops as the main unit has been found to have the best performance with the highest mean SNR in the ROI when imaging without acceleration. In addition, g-factor and 2D SENSE SNR in yoz-plane are simply analyzed, which show a sharp decrease in SNR for all the coils. Finally, all the coils are manufactured and operated at a 0.5 T permanent magnet MRI system with phantom and joint imaging experiments. Using pixel-by-pixel manner to evaluate SNR map, the experimental results are consistent with the simulation results, while parallel imaging experiment results show that the major consideration in low field MRI is the improvement of SNR value and uniformity rather than that of the imaging speed. As different constructions of four-channel received coils are investigated, we have found the most effective configuration with high and uniform SNR for vertical-field MRI.

Multiantenna GLR Detection of Rank-One Signals With Known Power Spectral Shape Under Spatially Uncorrelated Noise

We establish the generalized likelihood ratio (GLR) test for a Gaussian signal of known power spectral shape and unknown rank-one spatial signature in additive white Gaussian noise with an unknown diagonal spatial correlation matrix. This is motivated by spectrum sensing problems in dynamic spectrum access, in which the temporal correlation of the primary signal can be assumed known up to a scaling, and where the noise is due to an uncalibrated receive array. For spatially independent identically distributed (i.i.d.) noise, the corresponding GLR test reduces to a scalar optimization problem, whereas the GLR detector in the general non-i.i.d. case yields a more involved expression, which can be computed via alternating optimization methods. Low signal-to-noise ratio (SNR) approximations to the detectors are given, together with an asymptotic analysis showing the influence on detection performance of the signal power spectrum and SNR distribution across antennas. Under spatial rank- $P$ conditions, we show that the rank-one GLR detectors are consistent with a statistical criterion that maximizes the output energy of a beamformer operating on filtered data. Simulation results support our theoretical findings in that exploiting prior knowledge on the signal power spectrum can result in significant performance improvement.

Impact of an endorectal coil for 1H-magnetic resonance spectroscopy of the prostate at 3.0 T in comparison to 1.5 T: Do we need an endorectal coil?

ObjectivesTo evaluate the influence of endorectal coil (ERC) regarding spectral quality and diagnostic suitability and diagnostic performance in 3.0T 1H-magnetic resonance spectroscopy imaging (MRSI) compared to 1.5T MRSI. Materials and methodsThe study was approved by the Institutional Review Board. MRSI of the prostate was performed on 19 patients at 1.5T with ERC (protocol 1), at 3.0T with a disabled ERC (protocol 2) and at 3.0T with ERC (protocol 3). Age, weight, body size, body-mass-index, prostate volume, time between measurements, diagnostic suitability of spectra, histopathological results after biopsy of cancer suspect lesions (CSL), sensitivity and specificity were evaluated. Signal-to-noise ratio (SNR) was calculated and compared using semiparametrical multiple Conover-comparisons. Correlations between SNR and prostate volume and BMI were indicated using Pearson correlation coefficient. Distribution of SNR was evaluated for prostate quadrants. ResultsDiagnostic suitable spectra were achieved in 76 % (protocol 1, 100% in CSL), 32 % (protocol 2, 59% in CSL) and 50 % (protocol 3, 80% in CSL) of the voxels. SNR was significantly higher in protocol 3 compared to protocol 2 and 1 (93,729 vs. 27,836 vs. 32,897, p<0.0001) with significant difference between protocol 2 and 1 (p<0.023). Highest SNR was achieved in the dorsal prostate (protocols 1 and 3; p<0.0001). Sensitivity at 3.0T was higher with use of ERC. Specificity was highest at 1.5T with ERC. ConclusionThe ERC improves the diagnostic suitability and the SNR in MRSI at 3.0T. Less voxels at 3.0T with disabled ERC are suitable for diagnosis compared to 1.5T with ERC. MRSI at 3.0T with ERC shows the highest SNR. SNR in dorsal quadrants of the prostate was higher using ERC.

Mixture of PLDA for Noise Robust I-Vector Speaker Verification

In real-world environments, noisy utterances with variable noise levels are recorded and then converted to i-vectors for cosine distance or PLDA scoring. This paper investigates the effect of noise-level variability on i-vectors. It demonstrates that noise-level variability causes the i-vectors to shift, causing the noise contaminated i-vectors to form clusters in the i-vector space. It also demonstrates that optimal subspaces for discriminating speakers are noise-level dependent. Based on these observations, this paper proposes using signal-to-noise ratio (SNR) of utterances as guidance for training mixture of PLDA models. To maximize the coordination among the PLDA models, mixtures of PLDA models are trained simultaneously via an EM algorithm using the utterances contaminated with noise at various levels. For scoring, given a test i-vector, the marginal likelihoods from individual PLDA models are linearly combined by the posterior probabilities of the test utterance’s SNR. Verification scores are the ratio of the marginal likelihoods. Results based on NIST 2012 SRE suggest that the SNR-dependent mixture of PLDA is not only suitable for the situations where the test utterances exhibit a wide range of SNR, but also beneficial for the test utterances with unknown SNR distribution. Supplementary materials containing full derivations of the EM algorithms and scoring functions can be found in http://bioinfo.eie.polyu.edu.hk/mPLDA/SuppMaterials.pdf .

Exact MIMO Zero-Forcing Detection Analysis for Transmit-Correlated Rician Fading

We analyze the performance of multiple input/multiple output (MIMO) communications systems employing spatial multiplexing and zero-forcing detection (ZF). The distribution of the ZF signal-to-noise ratio (SNR) is characterized when either the intended stream or interfering streams experience Rician fading, and when the fading may be correlated on the transmit side. Previously, exact ZF analysis based on a well-known SNR expression has been hindered by the noncentrality of the Wishart distribution involved. In addition, approximation with a central-Wishart distribution has not proved consistently accurate. In contrast, the following exact ZF study proceeds from a lesser-known SNR expression that separates the intended and interfering channel-gain vectors. By first conditioning on, and then averaging over the interference, the ZF SNR distribution for Rician-Rayleigh fading is shown to be an infinite linear combination of gamma distributions. On the other hand, for Rayleigh-Rician fading, the ZF SNR is shown to be gamma-distributed. Based on the SNR distribution, we derive new series expressions for the ZF average error probability, outage probability, and ergodic capacity. Numerical results confirm the accuracy of our new expressions, and reveal effects of interference and channel statistics on performance.

Research on the Frequency Spectrum Management Method of VLF Based on the Propagation Prediction Technology

VLF communication is one of the most effective means to command underwater platform. The spectrum resource of vlf communication is limited, so it is very important for enhance the reliability of vlf communication to strengthen the vlf communication spectrum management. It makes use of the well prediction of the vlf frequency band, to establish the signal field predicting model and atmospheric noise statistics predicting model respectively, predicts the field of signal and noise level, and then calculated the signal-to-noise ratio (SNR). According to the SNR distribution we can determine the relationship of the optimal communication frequency, time and location of receiver. So the efficiency of spectrum management for vlf communication can be enhanced.

Exploiting multipath fading with a mobile robot

In indoor or urban applications, a moving robot with wireless communications will experience multipath fading. This causes rapid signal strength variations due to interfering reflections of the radio signal. By making short stops at positions with high signal-to-noise ratio (SNR), the robot can trade trajectory tracking accuracy for increased link quality. This represents a type of opportunistic communication-aware motion planning. We propose two novel strategies for improving the link capacity or throughput when either the robot has full knowledge of how the SNR varies along the trajectory, or when only the SNR distribution is known or can be estimated. In the latter case, this leads to an optimal stopping problem over a finite horizon. Both cases are analyzed for independent as well as correlated SNR samples, and a bounded maximum trajectory tracking error. We derive the resulting SNR distributions for the proposed strategies and use them to show how the expected capacity and throughput vary with the allowed tracking error. The results are confirmed by simulations and experiments. Experiments in six different locations validate the communication model and show that the proposed motion planning is robust to non-static fading and can yield throughput improvements of more than 100%.

Random matrix models, double-time Painlevé equations, and wireless relaying

This paper gives an in-depth study of a multiple-antenna wireless communication scenario in which a weak signal received at an intermediate relay station is amplified and then forwarded to the final destination. The key quantity determining system performance is the statistical properties of the signal-to-noise ratio (SNR) γ at the destination. Under certain assumptions on the encoding structure, recent work has characterized the SNR distribution through its moment generating function, in terms of a certain Hankel determinant generated via a deformed Laguerre weight. Here, we employ two different methods to describe the Hankel determinant. First, we make use of ladder operators satisfied by orthogonal polynomials to give an exact characterization in terms of a “double-time” Painlevé differential equation, which reduces to Painlevé V under certain limits. Second, we employ Dyson's Coulomb fluid method to derive a closed form approximation for the Hankel determinant. The two characterizations are used to derive closed-form expressions for the cumulants of γ, and to compute performance quantities of engineering interest.

Evolutionary algorithm-based optimisation of the signal-to-noise ratio for indoor visible-light communication utilising white light-emitting diode

Visible-light communication system that utilises white light-emitting diode (LED) lighting equipment has been proposed and expected to provide uniform wireless communications and illumination simultaneously. Owing to multipath transmission channel characteristics, up to now, it is still challenging to obtain uniform signal-to-noise ratio (SNR) for each position within the indoor environment. In this study, an evolutionary algorithm (EA)-based alternative scheme is proposed to optimise the SNR distribution for indoor visible-light communication systems. Presented analysis shows that in three distributed lighting configurations, when the optical powers of individual white LED lighting equipment are dynamically controlled by tailored EA, the dynamic range of SNR referenced against the peak SNR can be reduced by up to about 24.7% whereas the uniformity illuminance ratio is improved from less than 0.63 to over 0.70 with the impact to root-mean-square delay spread is negligible. Furthermore, the relationship between the field of view of receivers and the optimisation performance is presented as well.

Wa-LiD: A New LiDAR Simulator for Waters

A simulator (Wa-LiD) was developed to simulate the reflection of LiDAR waveforms from water across visible wavelengths. The specific features of the simulator include 1) a geometrical representation of the water surface properties; 2) the use of laws of radiative transfer in water adjusted for wavelength and the water's physical properties; and 3) modeling of detection noise and signal level due to solar radiation. A set of simulated waveforms was compared with observed LiDAR waveforms acquired by the HawkEye airborne and Geoscience Laser Altimeter System (GLAS) satellite systems in the near infrared or green wavelengths and across inland or coastal waters. Signal-to-noise ratio (SNR) distributions for the water surface and bottom waveform peaks are compared with simulated and observed waveforms. For both systems (GLAS and HawkEye), Wa-LiD simulated SNR conform to the observed SNR distributions. Moreover, Wa-LiD showed a good ability to reproduce observed waveforms according to some realistic water parameters fitting.

Non-sky-averaged sensitivity curves for space-based gravitational-wave observatories

The signal-to-noise ratio (SNR) is used in gravitational-wave observations as the basic figure of merit for detection confidence and, together with the Fisher matrix, for the amount of physical information that can be extracted from a detected signal. SNRs are usually computed from a sensitivity curve, which describes the gravitational-wave amplitude needed by a monochromatic source of given frequency to achieve a threshold SNR. Although the term ‘sensitivity’ is used loosely to refer to the detector’s noise spectral density, the two quantities are not the same: the sensitivity includes also the frequency- and orientation-dependent response of the detector to gravitational waves and takes into account the duration of observation. For interferometric space-based detectors similar to LISA, which are sensitive to long-lived signals and have constantly changing position and orientation, exact SNRs need to be computed on a source-by-source basis. For convenience, most authors prefer to work with sky-averaged sensitivities, accepting inaccurate SNRs for individual sources and giving up control over the statistical distribution of SNRs for source populations. In this paper, we describe a straightforward end-to-end recipe to compute the non-sky-averaged sensitivity of interferometric space-based detectors of any geometry. This recipe includes the effects of spacecraft motion and of seasonal variations in the partially subtracted confusion foreground from Galactic binaries, and it can be used to generate a sampling distribution of sensitivities for a given source population. In effect, we derive error bars for the sky-averaged sensitivity curve, which provide a stringent statistical interpretation for previously unqualified statements about sky-averaged SNRs. As a worked-out example, we consider isotropic and Galactic-disk populations of monochromatic sources, as observed with the ‘classic LISA’ configuration. We confirm that the (standard) inverse-rms average sensitivity for the isotropic population remains the same whether or not the LISA orbits are included in the computation. However, detector motion tightens the distribution of sensitivities, so for 50% of sources the sensitivity is within 30% of its average. For the Galactic-disk population, the average and the distribution of the sensitivity for a moving detector turn out to be similar to the isotropic case.

A volume microstrip RF coil for MRI microscopy

Quantitative magnetic resonance imaging (MRI) studies of small samples such as a single cell or cell clusters require application of radiofrequency (RF) coils that provide homogenous B 1 field distribution and high signal-to-noise ratio (SNR). We present a novel design of an MRI RF volume microcoil based on a microstrip structure. The coil consists of two parallel microstrip elements conducting RF currents in the opposite directions, thus creating homogenous RF field within the space between the microstrips. The construction of the microcoil is simple, efficient and cost-effective. Theoretical calculations and finite element method simulations were used to optimize the coil geometry to achieve optimal B 1 and SNR distributions within the sample and predict parameters of the coil. The theoretical calculations were confirmed with MR images of a 1-mm-diameter capillary and a plant obtained with the double microstrip RF microcoil at 11.7 T. The in-plane resolution of MR images was 24 μm×24 μm.

Downlink System Capacity Analysis in Distributed Antenna Systems

This paper focuses on the downlink system capacity in distributed antenna systems (DAS). Due to the complexity of actual wireless environments, a composite channel model is established which takes into account three factors, i.e., path loss, lognormal shadowing and Rayleigh fading. Based on the channel model, the probability density function (PDF) of the output signal-to-noise ratio (SNR) is derived. To facilitate the analysis, the distribution of the output SNR is approximated by a lognormal distribution. After that, by making use of selective diversity (SD) scheme for distributed antennas, an approximate analytical expression of the capacity for a mobile station (MS) over a given position is derived. Furthermore, considering the distribution of MSs in the system, a closed-form expression of the system capacity is obtained. Numerical results show that the closed-form expression can evaluate the system capacity performance of DAS very accurately.

WE‐C‐110‐04: Local Dose Constraints in Fluence Field Modulated CT

Purpose: Fluence field modulated computed tomography (FFMCT) presents a new paradigm for CT imaging. Spatial modulation of the x‐ray fluence field, whereby the fluence pattern can change independently for each projection, can potentially meet user‐prescribed, regionally‐varying image quality objectives, while reducing radiation exposure to the patient. This work studies the potential to meet image quality objectives while limiting dose to local regions of interest via FFMCT. Methods: All experiments were carried out in simulation using cylindrical and anthropomorphic phantoms. Fluence patterns were optimized to meet prescribed signal‐to‐noise ratio (SNR) criteria using a simulated annealing method with dose constraints on locally defined regions of interest. Optimizations were repeated using different weighting factors on the local dose constraints. Resulting SNR and dose distributions were compared to those of a fixed bowtie filtered fluence pattern. Results: Results using FFMCT had superior agreement with the target SNR objectives and resulted in integral dose reductions of up to 50% when compared to results using bowtie filtered fluence fields. Increasing the relative weight of the local dose constraint resulted in further dose reductions (30–40% integral dose) to local regions of interest, with some tradeoff in SNR where overlap between the target low dose regions occurred with target high SNR regions of interest. Conclusions: These results support the hypothesis that FFMCT has the potential to meet prescribed image quality objectives, while decreasing radiation dose to the patient. They also indicate that fluence field modulation may be optimized to prioritize dose reduction to local regions of interest when attempting to meet particular noise objectives.

Approximations of EESM Effective SNR Distribution

The Probability Density Function (PDF) or Cumulative Distribution Function (CDF) of the effective Signal to Noise Ratio (SNR) is an important statistical characterization in the performance analysis of an Orthogonal Frequency Division Multiple Access (OFDMA) system using Exponential Effective SNR Mapping (EESM). However, the exact closed form of PDF is extremely difficult to obtain. A general approximation method known as Moment Matching Approximating (MMA) is used to approximate the distribution of effective SNR by a simple expression. In this paper, the approximation by Gaussian, Generalized Extreme Value (GEV) and Pearson distribution are studied. Results show that Gaussian approximation is very useful when the number of sub-carriers is sufficiently large. Both GEV and Pearson approximation are accurate enough in approximating the distribution of effective SNR in a general case.