Showing papers on "Signal-to-noise ratio published in 1998"

Transmit beamforming and power control for cellular wireless systems

Abstract: Joint power control and beamforming schemes are proposed for cellular systems where adaptive arrays are used only at base stations. In the uplink, mobile power and receiver diversity combining vectors at the base stations are calculated jointly. The mobile transmitted power is minimized, while the signal-to-interference-and-noise ratio (SINR) at each link is maintained above a threshold. A transmit diversity scheme for the downlink is also proposed where the transmit weight vectors and downlink power allocations are jointly calculated such that the SINR at each mobile is above a target value. The proposed algorithm achieves a feasible solution for the downlink if there is one and minimizes the total transmitted power in the network. In a reciprocal network it can be implemented in a decentralized system, and it does not require global channel response measurements. In a nonreciprocal network, where the uplink and downlink channel responses are different, the proposed transmit beamforming algorithm needs to be implemented in a centralized system, and it requires a knowledge of the downlink channel responses. The performances of these algorithms are compared with previously proposed algorithms through numerical studies.

Acoustic vector-sensor beamforming and Capon direction estimation

Abstract: We examine the improvement attained by using acoustic vector-sensors for direction-of-arrival (DOA) estimation, instead of traditional pressure sensors, via optimal performance bounds and particular estimators. By examining the Cramer-Rao bound in the case of a single source, we show that a vector-sensor array's smaller estimation error is a result of two distinct phenomena: (1) an effective increase in signal-to-noise ratio due to a greater number of measurements of phase delays between sensors and (2) direct measurement of the DOA information contained in the structure of the velocity field due to the vector sensors' directional sensitivity. Separate analysis of these two phenomena allows us to determine the array size, array shape, and SNR conditions under which the use of a vector-sensor array is most advantageous and to quantify that advantage. By extending the beamforming and Capon (1969) direction estimators to vector-sensors, we find that the vector-sensors' directional sensitivity removes all bearing ambiguities. In particular, even simple structures such as linear arrays can determine both azimuth and elevation, and spatially undersampled regularly spaced arrays may be employed to increase the aperture and, hence, the performance. Large sample approximations to the mean-square error matrices of the estimators are derived and their validity is assessed by Monte Carlo simulation.

Adaptive stochastic resonance

Abstract: This paper shows how adaptive systems can learn to add an optimal amount of noise to some nonlinear feedback systems. This "stochastic resonance" (SR) effect occurs in a wide range of physical and biological systems. The noise energy can enhance the faint periodic signals or faint broadband signals that force the dynamical systems. Fuzzy and other adaptive systems can learn to induce SR based only on samples from the process. The paper derives the SR optimality conditions that any stochastic learning system should try to achieve. The adaptive system learns the SR effect as the system performs a stochastic gradient ascent on the signal-to-noise ratio. The stochastic learning scheme does not depend on a fuzzy system or any other adaptive system. Simulations test this SR learning scheme on the popular quartic-bistable dynamical system and on other dynamical systems. The driving noise types range from Gaussian white noise to impulsive noise to chaotic noise.

Analysis of noise reduction and dereverberation techniques based on microphone arrays with postfiltering

Abstract: In teleconferencing systems, the use of hands-free sound pick-up reduces speech quality. This is due to ambient noise, acoustic echo, and the reverberation produced by the acoustical environment. This paper sets out to present a theoretical analysis of noise reduction and dereverberation algorithms based on a microphone array combined with a Wiener postfilter. It is shown that the transfer function of the postfilter depends on the input signal-to-noise ratio (SNR) and on the noise reduction yielded by the array. The use of a directivity-controlled array instead of a conventional beam-former is proposed to improve the performance of the whole system. Examples in real room environments are provided, which confirm the theoretical results, It is observed that the postfilter gives a limited reduction of the reverberation. On the contrary, an appreciable reduction of acoustic echo and localized noise is obtained and makes the whole system highly attractive for hands-free communication systems.

2-D companding for noise reduction in strain imaging

Abstract: Companding is a signal preprocessing technique for improving the precision of correlation-based time delay measurements. In strain imaging, companding is applied to warp 2-D or 3-D ultrasonic echo fields to improve coherence between data acquired before and after compression. It minimizes decorrelation errors, which are the dominant source of strain image noise. The word refers to a spatially variable signal scaling that compresses and expands waveforms acquired in an ultrasonic scan plane or volume. Temporal stretching by the applied strain is a single-scale (global), 1-D companding process that has been used successfully to reduce strain noise. This paper describes a two-scale (global and local), 2-D companding technique that is based on a sum-absolute-difference (SAD) algorithm for blood velocity estimation. Several experiments are presented that demonstrate improvements in target visibility for strain imaging. The results show that, if tissue motion can be confined to the scan plane of a linear array transducer, displacement variance can be reduced two orders of magnitude using 2-D local companding relative to temporal stretching.

HMM-based strategies for enhancement of speech signals embedded in nonstationary noise

Abstract: An improved hidden Markov model-based (HMM-based) speech enhancement system designed using the minimum mean square error principle is implemented and compared with a conventional spectral subtraction system. The improvements to the system are: (1) incorporation of mixture components in the HMM for noise in order to handle noise nonstationarity in a more flexible manner, (2) two efficient methods in the speech enhancement system design that make the system real-time implementable, and (3) an adaptation method to the noise type in order to accommodate a wide variety of noise expected under the enhancement system's operating environment. The results of the experiments designed to evaluate the performance of the HMM-based speech enhancement systems in comparison with spectral subtraction are reported. Three types of noise-white noise, simulated helicopter noise, and multitalker (cocktail party) noise-were used to corrupt the test speech signals. Both objective (global SNR) and subjective mean opinion score (MOS) evaluations demonstrate consistent superiority of the HMM-based enhancement systems that incorporate the innovations described in this paper over the conventional spectral subtraction method.

A voice activity detector employing soft decision based noise spectrum adaptation

Abstract: In this paper, a voice activity detector (VAD) for variable rate speech coding is decomposed into two parts, a decision rule and a background noise statistic estimator, which are analysed separately by applying a statistical model. A robust decision rule is derived from the generalized likelihood ratio test by assuming that the noise statistics are known a priori. To estimate the time-varying noise statistics, allowing for the occasional presence of the speech signal, a novel noise spectrum adaptation algorithm using the soft decision information of the proposed decision rule is developed. The algorithm is robust, especially for the time-varying noise such as babble noise.

Multi-beam antenna system for cellular radio base stations

Abstract: A base transceiver station operating a sectorized cell of a cellular radio system operates a plurality of narrow uplink main receive beams, and one or a plurality of uplink diversity received beams. A scanning means scans each of theuplink main receive beams to locate a communications channel on the main uplink beams. A diversity receiver receives a diverse beam signal from the diverse beam(s), which is compared with a beam signal received from a main uplink beam, and the main beam signal from the main beam, or a diverse beam signal from the diversity antenna is selected, depending on the comparative signal to noise ratio and signal strength of the main beam signal and diversity beam signal.

Analog error-correcting codes based on chaotic dynamical systems

Abstract: The properties of chaotic dynamical systems make them useful for channel coding in a variety of practical communication applications. To illustrate this, a novel analog code based on tent map dynamics and having a fast decoding algorithm is developed for use on unknown, multiple, and time-varying signal-to-noise ratio (SNR) channels. This code is shown to be an attractive alternative to both digital codes and linear modulation in such scenarios. Several properties and interpretations of the codes are developed, along with some methods for their optimization.

System and method for measuring channel quality information

Abstract: A system and method to measure channel quality in terms of signal to noise ratio for the transmission of coded signals over fading channels. A Viterbi decoder metric for the Maximum Likelihood path is used as a channel quality measure. This Euclidean distance metric is filtered in order to smooth out short term variations. The filtered or averaged metric is a reliable channel quality measure which remains consistent across different coded modulation schemes and at different mobile speeds. The filtered metric is mapped to the signal to noise ratio per symbol using a threshold based scheme. Use of this implicit signal to noise ratio estimate is used for the mobile assisted handoff and data rate adaptation in the transmitter.

Reducing the peak-to-average power ratio in OFDM radio transmission systems

Abstract: An important difficulty which has to be solved in OFDM transmission systems is the large peak-to-average power ratio of the OFDM signal. Without any measures, the signal is limited by the power amplifier in the transmitter which causes interference both of the signal itself and in adjacent frequency bands. A method is proposed which considerably reduces the peak-to-average power ratio of the OFDM signal by means of signal processing.

Symbol rate and modulation level-controlled adaptive modulation/TDMA/TDD system for high-bit-rate wireless data transmission

Abstract: This paper proposes a time-division multiple-access/time-division duplex (TDMA/TDD)-based symbol rate and modulation level-controlled adaptive modulation system for high-bit-rate data transmission. The proposed system controls both the symbol rate and modulation level for the next transmission time slot according to the estimated carrier power to noise spectral density ratio (C/N/sub 0/) and delay spread for the time slot to achieve higher bit rate and higher transmission quality as well as higher delay-spread immunity. It is demonstrated by computer simulation and laboratory experiments that the proposed system can achieve a higher average bit rate with higher transmission quality in comparison with the fixed-rate quaternary phase-shift keying (QPSK) system and modulation level-controlled adaptive modulation system in both flat Rayleigh and frequency-selective fading environments. The simulated and experimental results also show that the proposed adaptive modulation techniques can be applied to 1-2-Mb/s indoor and outdoor microcellular systems with its delay spread of up to 250 ns and its terminal mobility of up to pedestrian speed without employing any special antifrequency-selective fading techniques, such as the adaptive equalizer and space diversity.

Modular home-networking communication system and method using disparate communication channels

Abstract: A modular home-networking communications system which uses a physical layer modulation scheme suitable for transmission in both RF and powerline communication channels. The modulation system is based on direct-sequence spread-spectrum (DS-SS) using Barker codes to spread the information symbols, which provides both operation at low signal to noise ratio and very good resistance to time dispersion distortion due to the excellent autocorrelation properties of the Barker codes. This type of modulation system is ideal for the powerline communications channel since it spreads the transmission power over a wide range of frequency, lowering the power spectral density enough that it will provide long distance coverage without violating FCC radiated emission and conducted power regulations.

A robust voice activity detector for wireless communications using soft computing

Abstract: Discontinuous transmission based on speech/pause detection represents a valid solution to improve the spectral efficiency of new generation wireless communication systems. In this context, robust voice activity detection (VAD) algorithms are required, as traditional solutions present a high misclassification rate in the presence of the background noise typical of mobile environments. This paper presents a voice detection algorithm which is robust to noisy environments, thanks to a new methodology adopted for the matching process. More specifically, the VAD proposed is based on a pattern recognition approach in which the matching phase is performed by a set of six fuzzy rules, trained by means of a new hybrid learning tool. A series of objective tests performed on a large speech database, varying the signal-to-noise ratio (SNR), the types of background noise, and the input signal level, showed that, as compared with the VAD standardized by ITU-T in Recommendation G.729 annex B, the fuzzy VAD, on average, achieves an improvement in reduction both of the activity factor of about 25% and of the clipping introduced of about 43%. Informal listening tests also confirm an improvement in the perceived speech quality.

Uplink channel capacity of space-division-multiple-access schemes

Abstract: The signal-to-noise ratio (SNR) and signal bandwidth have been viewed as the dominant factors determining the channel capacity. In wireless communications, the channel capacity can be increased for a given SNR and a given spectral region, by exploiting the spatial diversity provided by the use of multiple antennas and transceivers at a base station. We calculate the channel capacity enhancement of a so-called space-division-multiple-access (SDMA) system and investigate its dependence with respect to different decoding schemes, terminal positions, and receiver numbers. Inner and outer capacity boundaries for joint decoding and independent decoding are presented, along with physical explanations as to how these boundaries can be achieved. We show that exploitation of the spatial diversity not only increases the overall achievable rates of both joint and independent decoding, but also closes the gap between their corresponding capacity regions, thus bringing the performance of the low-cost independent decoding scheme close to that of the optimal joint decoding. Practical issues of optimum projection and power control are also addressed.

Adaptive error correction for a communications link

Abstract: A method of data transfer between a transmitter and a receiver over a communications link achieves maximum throughput by dynamically adapting a coding rate, and specifically an error correction encoder, as a function of a measured reverse channel signal parameter. The method comprises the steps of transmitting a signal from the transmitter to the receiver, the receiver receiving and measuring the signal to noise ratio of the transmitted signal. The receiver determines an appropriate code rate and encoding technique as a function of the measured signal to noise ratio and transmits an encoding identifier of the determined encoder to the transmitter. The transmitter encodes its data according to the encoding identifier and transmits the encoded message to the receiver. The receiver receives the encoded message and decodes the message according to the determined code rate and encoding technique.

Pulse elongation and deconvolution filtering for medical ultrasonic imaging

Abstract: Range sidelobe artifacts which are associated with pulse compression methods can be reduced with a new method composed of pulse elongation and deconvolution (PED). While pulse compression and PED yield similar signal-to-noise ratio (SNR) improvements, PED inherently minimizes the range sidelobe artifacts. The deconvolution is implemented as a stabilized inverse filter. With proper selection of the excitation waveform an exact inverse filter can be implemented. The excitation waveform is optimized in a minimum mean square error (MMSE) sense. An analytical expression for the power spectrum of the optimal pulse is presented and several techniques to numerically optimize the excitation pulse are shown. The effects of PED are demonstrated in computer simulations as well as ultrasonic images.

Multiresolution local-statistics speckle filtering based on a ratio Laplacian pyramid

Abstract: Speckle filtering in synthetic aperture radar (SAR) images is a key point to facilitate applicative tasks. A filter aimed at speckle reduction should energetically smooth homogeneous regions, while preserving point targets, edges, and linear features. A compromise, however, should be arranged on textured areas. In this work, a ratio Laplacian pyramid (RLP) is introduced to match the signal-dependent nature of speckle noise. Local statistics filtering is applied to the different spatial resolutions of the RLP of a speckled image. For natural scenes, each pyramid layer is characterized by an signal-to-noise ratio (SNR) increasing as resolution decreases. Thus, each filter may be adjusted to achieve adaptivity also across scales. In addition, the estimation of the local statistics driving the filter is more accurate thanks to the multiresolution framework. A complete procedure is setup, and a general formulation, in which the variance of speckle is theoretically derived at each resolution, is developed. Experiments carried out on remotely sensed optical images corrupted with synthetic speckle, as well as on true SAR images, show the potentiality of the pyramid-based approach compared with other established despeckle algorithms, in terms both of SNR improvements and of enhancement in visual quality.

Design of a fibre optic multi-point sensor for gas detection

Abstract: We report the design of a multi-point fibre optic methane sensor using a DFB laser source with a branched fibre network and micro-optic cells. Measurements are performed through derivative spectroscopy, with line scanning and digital signal processing, to give sensitivities down to a few ppm metre. The form of the derivative signal obtained from the system is modelled theoretically and compared with the experimental signal. The main limitation in the signal to noise ratio of the system is due to interference effects (etalon fringes) from the cells and we show how these effects may be minimised.

Error estimates for minimum variance analysis

Abstract: Analytical estimates of errors, associated with random statistical noise in magnetic field and other data to which the minimum/maximum variance analysis technique is commonly applied, are derived from first principles. A systematic expansion procedure is used in which the expansion parameter is proportional to the noise amplitude and inversely proportional to the square root of the number of vector data samples, K. The two special cases where the signal-to-noise ratio is large and small are considered for arbitrary noise distributions. The ideal case of small errors and isotropic Gaussian noise allows determination of uncertainty cones of elliptic cross section for all three eigenvectors, x1, x2, x3, and uncertainty intervals for all three eigenvalues, λ1, λ2, λ3, of the variance matrix, all in terms of the eigenvalues themselves and the number of data points. Denoting the angular standard deviation (in radians) of vector xi toward or away from vector xj by Δϕij these results are Δϕij = ±[λ3(λi + λj − λ3)/(K − 1)(λi − λj)2]1/2 and Δλi = ±[2λ3(2λi − λ3)/(K − 1)]1/2 where λ3 is the smallest eigenvalue. The predictions from these formulas compare favorably with results from simple bootstrap numerical error analysis. Applications to maximum variance analysis of electric field data and to the study of anisotropic plasma pressure tensors are discussed as special cases.

Convergence and stability assessment of Newton-Kantorovich reconstruction algorithms for microwave tomography

Abstract: For newly developed iterative Newton-Kantorovitch reconstruction techniques, the quality of the final image depends on both experimental and model noise. Experimental noise is inherent to any experimental acquisition scheme, while model noise refers to the accuracy of the numerical model, used in the reconstruction process, to reproduce the experimental setup. This paper provides a systematic assessment of the major sources of experimental and model noise on the quality of the final image. This assessment is conducted from experimental data obtained with a microwave circular scanner operating at 2.33 GHz. Targets to be imaged include realistic biological structures, such as a human forearm, as well as calibrated samples for the sake of accuracy evaluation. The results provide a quantitative estimation of the effect of experimental factors, such as temperature of the immersion medium, frequency, signal-to-noise ratio, and various numerical parameters.

Signal to noise ratio scaling and density limit estimates in longitudinal magnetic recording

Abstract: A simplified general expression is given for SNR for digital magnetic recording for transition noise dominant systems. High density media are assumed in which the transition parameter scales with the in-plane grain diameter. At a fixed normalized code density, the SNR varies as the square of the bit spacing times the read track width divided by the grain diameter cubed. This scaling law is shown to be quite general and useful for error rate analysis. Density optimization argues for track width narrowing rather than bit length reduction, limited by edge track considerations. Utilization of Arrhenius thermal signal decay yields limiting density estimates, neglecting electronics noise, in the range 50-100 Gbit/in/sup 2/ increasing with an increase in medium thickness/grain diameter ratio.

Method for functional brain imaging from magnetoencephalographic data by estimation of source signal-to-noise ratio

Abstract: An improved method, termed “statistical synthetic aperture magnetometry” (SSAM) of transforming magnetoencephalographic (MEG) measurements into corresponding three-dimensional images of the electrophysiological activity within the brain. The computed images are static, representing the time-integrated brain activity over a selected period. By selecting the time periods and frequency bands of interest, the SSAM method selectively images brain activity relating to different types of brain pathology or to cognitive events. Unlike prior art methods, the SSAM method compensates for the growth of ionic signal source strength estimates with depth into the head, resulting, in part, from the declining sensitivity of the MEG sensors. This is achieved by computing and displaying functions of the ratio of source strength to its noise for each element comprising the image. That is, a functional image is determined by an array of voxels where each voxel is based upon a function of source signal-to-noise ratio (SNR) rather than the source strength, alone. By using functions of SNR to represent source activity, the SSAM method achieves more accurate and higher resolution source localization. Each voxel is represented as a function of the ratio of a source power estimate to a source noise variance estimate. Such functions are found to be maximum at the true locations of sources, whereas plots of source power alone (as in prior art methods), show maxima which appear deeper and more diffuse in the brain than they in fact are.

On the capacity of the blockwise incoherent MPSK channel

Abstract: The capacity of M-ary phase-shift keying (MPSK) over an additive white Gaussian noise (AWGN) channel with carrier phase unknown but constant over L symbols is investigated. It is shown that capacity-achieving channel inputs are uniformly distributed and independent MPSK symbols. Capacity over a range of signal-to-noise ratio (SNR) and L is presented for binary phase-shift keying (BPSK) and quaternary phase-shift keying (QPSK). Upper and lower easy-to-compute bounds on capacity are derived. It is proven that for large L the coherent capacity is approached. An analytic asymptotic expression for low L/spl middot/SNR is derived exhibiting the expected quadratic dependence on the SNR.

Simultaneous distributed measurement of strain and temperature from noise-initiated Brillouin scattering in optical fibers

Abstract: The simultaneous determination of strain and temperature distributions from the measurement of noise-initiated Brillouin scattering (NIBS) power and frequency shift in optical fibers is discussed. Equations governing the growth of the NIBS signal are derived and from these, we calculate the dependence of the Brillouin power on temperature and strain. We study the potential problem given by the need to normalize the nonlinear Brillouin signal and present a new technique that solves this problem by mathematically combining the values of the Stokes and anti-Stokes powers to produce a linear effective power. Experimental results are presented that support this theory and allow the verification of the coefficients governing the dependence of the Brillouin power and frequency shift on temperature and strain. The signal-to-noise ratio of the sensor is discussed, and it is found that the noise associated with the field statistics plays a limiting role in the sensor performance and that an optimum value for the Brillouin gain factor can be determined. A simultaneous distributed temperature and strain sensor is demonstrated; preliminary results show a strain resolution of 100-/spl mu/m strain, a temperature resolution of 4/spl deg/C, and a spatial resolution of 40 m, over a sensing length of 1200 m.

Improved azimuthal resolution of forward looking SAR by sophisticated antenna illumination function design

Abstract: In comparison to side looking synthetic aperture radar (SAR), in a forward looking SAR it is much more difficult to achieve high angular resolution. The reason for this resolution problem is that terrain points situated symmetrically about the flight path have the same Doppler history, and the gradient of the Doppler frequency is small in the flight direction. A promising way to improve the resolution consists in using minimum variance unbiased (MVU) estimation in the receiver. Unfortunately, MVU estimation leads to undesirable noise enhancement. It is shown that an appropriate method to determine the achievable angular resolution consists in studying this noise enhancement. To minimise the noise enhancement and thus maximise the angular resolution, the author proposes antennas with specific aperture illumination functions. These illumination functions result in radiation patterns which are spread in the angular domain and are simultaneously fine-structured. Quantitative results concerning the noise enhancement and the angular resolution are presented and discussed.

Efficient estimation of power spectral density from laser Doppler anemometer data

Abstract: A non-biased estimator of power spectral density (PSD) is introduced for data obtained from a zeroth order interpolated laser Doppler anemometer (LDA) data set. The systematic error, sometimes referred to as the “particle-rate filter” effect, is removed using an FIR filter parameterized using the mean particle rate. Independent from this, a procedure for estimating the measurement system noise is introduced and applied to the estimated spectra. The spectral estimation is performed in the domain of the autocorrelation function and assumes no further process parameters. The new technique is illustrated using simulated and measured data, in the latter case with direct comparison to simultaneously acquired hot-wire data.

An efficient algorithm for estimating the signal-to-interference ratio in TDMA cellular systems

Abstract: A new algorithm is proposed for estimating the signal-to-interference plus noise ratio S/(I+N) in time-division multiple-access (TDMA) cellular systems. The S/(I+N) estimator is evaluated for use in the IS-54/136 system and a GSM-like system, and compared with existing techniques. The algorithm has a mean square prediction error that is comparable to the best known S/(I+N) estimation schemes, but with a significantly reduced computational complexity.