Noise Power Spectral Density Research Articles

Modeling and characteristics of MWIR HgCdTe APD at different post-annealing processes

Mid-wavelength infrared (MWIR) HgCdTe electron-initiated avalanche photodiodes (e-APDs) have presented excellent performances to resolve and count photons with linear mode. Aiming at low flux, the ROIC noise can be extremely reduced by certain gain, and very low excess noise makes opportunity for noise equivalent photon (NEPh) to be 1. Therefore, the main issue for SNR of HgCdTe APD is gain normalized dark current density (GNDCD) at high reverse bias. In this work, the architecture of multiplication region is modeled and studied. The depth and width of multiplication region are controlled by regulating the p-type doping concentration, ion implantation and post thermal annealing conditions as well. Proper processes can keep the peak electric field away from the implantation damage region, effectively increase the Shockley–Read–Hall (SRH) lifetime, reduce the multiplication region concentration and finally increase the operating voltage. Considered with dark current and gain, depletion region (I region) width is optimized and characterized to be 3–3.6 μm when I region concentration is ∼1 × 1015 cm−3 in our case. The GNDCD of MW APD (cut off wavelength ∼5.16 μm @80 k) is less than 10−6 A/cm2@≤-10 V, with avalanche gain of ∼1570@-9.8 V. The excess noise factor (F) is measured to be 1–1.4 by noise power spectral density (PSD). The NEPh value is less than 5 photons with gain up to ∼280 for MW 128 × 128 HgCdTe APD array. Simulation results anticipate that GNDCD can be further reduced by decreasing the doping concentration of I region to below 5 × 1014 cm−3. Furthermore, increasing the p-type doping concentration and band gap will significantly reduce GNDCD below to ∼10−10 A/cm2@-10 V for 4.22 μm Hg1-xCdxTe (x = 0.332) APD.

Seafloor depth controls seismograph orientation uncertainty

SUMMARY This study evaluates the seafloor ambient noise environment that varies with the water depth based on a correction analysis of the horizontal sensor orientation for ocean-bottom seismographs. As ocean-bottom seismographs are mainly deployed as ‘free-fall’ installations, we have no information on which direction a horizontal sensor faces at the seafloor. An accurate sensor orientation is crucial for data processing based on seismic wavefields. Among several seismological approaches that use passive sources to correct the horizontal sensor azimuth, the particle motion of teleseismic Rayleigh waves is widely used for broad-band ocean-bottom seismographs. We performed seafloor seismic observations in the Hyuga-nada region at the western end of the Nankai subduction zone and deployed broad-band and short-period seismographs. However, studies have yet to investigate whether orientation correction via the Rayleigh-wave polarization method is valid for short-period data. The results of the Rayleigh wave method from our campaign observation data showed that the estimation uncertainty of short-period sensor orientations increased with a decreasing water depth; we observed a transition depth for the uncertainty at 2200–2600 m. The measurement quality, or the cross-correlation coefficient between the radial and Hilbert-transformed vertical components, also decreased at depths shallower than 2000 m. Moreover, an analysis of the noise power spectral densities showed that ambient noise levels during long periods (>10 s) increased with decreasing depth. Infragravity waves controlled vertical long-period noise levels, while ocean currents dominated horizontal long-period noise; both of these reduced the Rayleigh-wave signals as a function of environmental noise. Infragravity waves also likely distorted the Rayleigh waveforms. Both mechanisms contributed to the sudden rise in orientation uncertainty and low measurement quality at shallow stations (i.e. <2000 m). We confirmed that the variation in orientation uncertainty with the water depth can be used as an index for the ambient noise environment of the seafloor.

Seismic Signature of Rain and Wind Inferred From Seismic Data

AbstractSeismic stations are increasingly used to monitor river activity and to quantify sediment transport during flood events. In tropical regions, cyclone‐induced floods are often associated with heavy rain and strong wind episodes, generating complex seismic records involving the simultaneous signature of water, sediment, rainfall and wind. Hence, seismic characterization of rain and wind is then required to better decipher each process and improve our understanding of the river seismic signature. In this study, we investigate experimentally the seismic response of rain and wind using data recorded by geophones deployed in various soil types and at different burial depth (BD), co‐located with various meteorological instruments. Our results show that the power spectral density (PSD) of the seismic noise intensifies at a frequency between 60 and 500 Hz for rain and 5 and 500 Hz for wind, in the presence of rain precipitation as low as 0.025 mm/min and/or wind speed ≥3 m/s. PSD analysis indicates that the seismic signal associated with rain decreases with the BD with a value of ∼2–5 dB in a depth difference of 10 cm. We also observe that each soil type has its own seismic signature. The 4‐min root mean square correlation between the seismic signal amplitude and the rain precipitation suggests that they best correlate with Pearson coefficient >0.90 at BD of 30 cm. The transfer function between the precipitation rate (or kinetic energy) and the seismic signal amplitude shows that the signal recorded by the geophone can be used as a robust proxy for these parameters.

A Novel Approach for Modeling and Digital Generation of RF Signals Distorted by Bandlimited Phase Noise

In radar and communication systems, phase noise is one of the main causes of performance degradation. Phase noise increases the uncertainty in radar measurements and limits the achievable data rates in communication systems. When radio frequency (RF) signals distorted by bandlimited phase noise are modeled, the phase noise power spectral density (PSD) is usually approximated by a scalar root-mean-square (RMS) phase error derived from a simple integration of the PSD. This disregards the close-to-carrier noise excess. In this article, we show that this convention simplification describes the real behavior of phase noise inadequately. In addition, we present a simulation of realistic phase noise behavior. The novel additive colored noise (ACN) model requires a representative phase noise PSD of the phase-locked loop (PLL) signal generator phase noise to be modeled. The developed ACN approach is validated by comparing the measured PSD of different PLL signal generators with the respective simulated RF signals distorted by phase noise. As a simple metric for assessing the quality of the phase noise models, we use the influence of phase noise on carrier frequency estimation. It is shown that the novel approach shows a significant improvement in the agreement between the simulated and measured precision compared to standard additive white Gaussian noise (AWGN) models. The results show that advanced phase noise models, as proposed in this paper, are necessary to adequately model and predict the performance of radar and communication systems.

Detailed Analysis and Modeling of Phase Noise and Systematic Phase Distortions in FMCW Radar Systems

In coherent continuous-wave (CW) radar systems, such as frequency-modulated CW (FMCW) radar systems, measurement precision is distorted by phase noise and systematic phase errors during radar signal generation. Unfortunately, to date, these phase distortions have typically been modeled based on many simplifications, often leading to overoptimistic predictions of radar performance. For example, phase noise is regularly considered based on additive white Gaussian noise (AWGN) models, ignoring its colored spectral property. Systematic errors are also frequently not properly separated from stochastic distortions, or not precisely measured and modeled. To overcome these issues, an advanced CW radar and frequency synthesizer model is proposed, analyzed, and experimentally verified in this paper. It is shown how systematic phase errors can be measured and how the influence of phase distortions on radar measurement can be accurately predicted. The proposed modeling approach was investigated for range correlation and range precision. The key metrics are the phase noise power spectral density (PSD) for range correlation and the variance of the frequency estimate for range precision. A 24-GHz FMCW radar system was used for the experimental verification. Long-range radar targets with distances of 38 to 880 m were created with an analog fiber optical link. Therefore, a precise and systematic evaluation of all effects was possible. The proposed phase distortion modeling approach realistically represented the range-dependent radar measurement effects. This enables the most precise simulation of and prediction for FMCW radar performance to date.

Performance Perspective of Gate-All-Around Double Nanosheet CMOS Beyond High-Speed Logic Applications

In this review paper, the performance characteristics of Gate-All-Around (GAA) double nanosheet (NS) MOSFETs are described over a broad temperature range, from 78 K to 473 K (200 oC). Emphasis is on the analog operation, showing good potential. Besides the transistor length, the impact of the metal gate Effective Work Function and the vertical distance between the nanosheets has been studied. Among others, a clear Zero Temperature Coefficient (ZTC) gate voltage has been observed that can be modeled by considering the shift with temperature of the threshold voltage and the maximum transconductance. A trade-off has been noticed between the transistor efficiency and the unit gain frequency, whereby the optimal operation point occurs in strong inversion regime. The feasibility of designing simple analog circuits has also been demonstrated. Finally, a detailed investigation of the low-frequency noise behavior yields good values for the flicker noise Power Spectral Density in comparison with other technology nodes.

Reverse engineering of one-qubit filter functions with dynamical invariants

We derive an integral expression for the filter-transfer function of an arbitrary one-qubit gate through the use of dynamical invariant theory and Hamiltonian reverse engineering. We use this result to define a cost function which can be efficiently optimized to produce one-qubit control pulses that are robust against specified frequency bands of the noise power spectral density. We demonstrate the utility of our result by generating optimal control pulses that are designed to suppress broadband detuning and pulse amplitude noise. We report an order of magnitude improvement in gate fidelity in comparison with known composite pulse sequences. More broadly, we also use the same theoretical framework to prove the robustness of nonadiabatic geometric quantum gates under specific error models and control constraints.

СТАТИСТИЧЕСКИЕ ХАРАКТЕРИСТИКИ СИСТЕМЫ ОТНОСИТЕЛЬНОЙ ПЕРЕДАЧИ ИНФОРМАЦИИ НА ОСНОВЕ ХАОТИЧЕСКИХ ИМПУЛЬСОВ В КАНАЛЕ С ГАУССОВСКИМ ШУМОМ

The purpose of this paper is to analyze the statistical characteristics of a differentially coherent communication scheme based on the use of chaotic pulses in the presence and absence of thermal noise for various distributions of chaotic signal instantaneous values. To achieve this goal, a numerical simulation for the performance of direct chaotic differentially coherent communication scheme is carried out in the work by a computer simulation. A numerical simulation was carried out, confirming the previously obtained analytical bit error probability estimates vs energy per bit to gaussian noise power spectral density ratio. The minimum energy per bit to gaussian noise power spectral density ratio values, which provide the given error probabilities, are obtained. It is shown that the proposed communication system works effectively at high values of processing gain(the behavior of the communication system was studied for various values of processing gain), and in the case of high values of processing gain, the results obtained do not depend on the choice of a specific discrete chaotic signal distribution.

Maximum likelihood separation of anthropogenic and wind-generated underwater noise.

A method is presented for simultaneous estimation of the probability distributions of both anthropogenic and wind-generated underwater noise power spectral density using only acoustic data recorded with a single hydrophone. Probability density models for both noise sources are suggested, and the model parameters are estimated using the method of maximum likelihood. A generic mixture model is utilized to model a time invariant anthropogenic noise distribution. Wind-generated noise is assumed normally distributed with a wind speed-dependent mean. The mean is then modeled as an affine linear function of the wind-generated noise level at a reference frequency, selected in a frequency range where the anthropogenic noise is less dominant. The method was used to successfully estimate the wind-generated noise spectra from ambient noise recordings collected at two locations in the southern Baltic Sea. At the North location, 3 km from the nearest shipping lane, the ship noise surpasses the wind-generated noise almost 100% of the time in the frequency band 63-400 Hz during summer for wind speed 7 m/s. At the South location, 14 km to the nearest shipping lane, the ship noise dominance is lower but still 40%-90% in the same frequencies and wind speed.

Análisis de la técnica NOMA-OFDM en un canal multitrayecto y usando estimación de canal

NOMA (Non-Orthogonal Multiple Access) is a non-orthogonal access technique that can increase spectral efficiency and is considered a candidate technology for 5G. NOMA-OFDM combines the non-orthogonal access of NOMA with OFDM, which is widely used due to several advantages such as its high spectral efficiency. Channel estimation is an essential process in a NOMA-OFDM system, so in this paper a channel estimation scheme with preamble for the downlink is proposed considering a multipath channel and the LS (Least Square) technique. The analysis of the results is performed based on graphs of BER (Bit Error Rate) vs Eb/N0 (Energy per bit to noise power spectral density ratio) of the simulation implemented in Matlab and shows that channel estimation is possible with the LS method with the advantage that it is a simple technique although it produces a degradation of approximately 3 dB in the BER compared to the ideal case of perfect estimation. In addition, the results show that the selection of the injection factor is very important for the performance of the users to be adequate.

A MEMS frequency modulation electrometer based on pre-bias charge mechanism to enhance performance

This paper proposes a prototype of micro-electromechanical frequency modulation electrometers based on pre-bias charge mechanism with a single-anchor circular beam (SACB) resonator. The SACB can overcome the uneven energy distribution in the traditional axial-extended tuning forks structure to weaken the geometric nonlinearity. The charge sensitivity is directly related to the pre-bias charge proven by both theorical and experimental results. With increase of pre-bias charge, the resonator works from the clumsy region to the sensitive region. The SACB electrometer has sensitivity of 5.14 ppm fC−1 under 1.416 pC bias in open-loop measurement and 4.52 ppm fC−1 in closed-loop measurement. Real-time dynamic modulation detection is completed with 0.354 fC step variation. Through the analysis of the noise power spectral density, increasing the pre-bias charge can suppress the noise floor of the resonator. As the bias is increased from 0.708 pC to 1.416 pC, the charge resolution is increased by almost 20 times, and the dynamic range is enlarged by 131%. The pre-bias mechanism can be also used in other resonant sensing applications for improvement of performance.

Shot and Johnson noises in interband cascade infrared photodetectors

Shot and Johnson noises are often incorrectly thought of as two independent noise sources. This incorrect picture has affected the evaluation of detectivities in interband cascade infrared photodetectors (ICIPs). In this work, a unified picture of shot and Johnson noises is developed for ICIPs based on a fundamental framework to understand the origin of Johnson noise and clarify the possible confusion between Johnson and shot noises. General, yet concise expressions are derived to evaluate the current noise power spectral density and detectivity for ICIPs even with complicated structures. Also, simple expressions for the signal current due to absorption of photons and the corresponding photon noise are derived, consistent with the previous results derived from alternative methods. Furthermore, a formula is derived to correctly evaluate the detectivity for conventional photodetectors under a reverse bias. The derived formulas with discussion are expected to improve the understanding of noises in ICIPs and other types of photodetectors and help us to appropriately evaluate their detectivities.

Temperature-Dependent Threshold Voltage Extraction of FinFETs Using Noise Measurements

In this article, a temperature-dependent threshold voltage extraction method based on noise measurement is proposed. This method induces a mathematical solution for acquiring channel temperatures ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> ) of transistors in the saturation region to extract threshold voltages. In order to gain accurate channel temperature, a small-signal equivalent circuit model was established to determine transconductance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$g_{m}$ </tex-math></inline-formula> ). Then, the extracted transconductance and measured noise power spectral density (NPSD) were used to obtain channel temperatures. On this basis, the temperature-dependent threshold voltage ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {th}}$ </tex-math></inline-formula> ) was derived. To validate the reliability of this method, a four-Fin six-finger N-FinFET and a four-Fin eight-finger N-FinFET were fabricated using the 14-nm bulk FinFET technology. In this study, the scattering parameters were obtained from 0.2 to 40.2 GHz. Also, the NPSDs were measured from 1 to 500 Hz, while gate voltage and drain voltage were set as 0.3, 0.49, and 0.75 V. Besides, the transistor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I_{\mathrm {ds}}$ </tex-math></inline-formula> – <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {ds}}$ </tex-math></inline-formula> characteristics was also investigated when drain–source bias voltage changed from 0.05 to 0.9 V. Compared with the measurement results, the calculation results of drain–source current model using temperature-dependent threshold voltage achieved higher accuracy. Also, the root mean square errors (RMSEs) were less than 0.60% for four-Fin six-finger N-FinFET and less than 0.51% for four-Fin eight-finger N-FinFET. Therefore, the proposed extraction method can be applied to accurately predict transistor temperature-dependent threshold voltage.

Fingerprints of Qubit Noise in Transient Cavity Transmission.

Noise affects the coherence of qubits and thereby places a bound on the performance of quantum computers. We theoretically study a generic two-level system with fluctuating control parameters in a photonic cavity and find that basic features of the noise spectral density are imprinted in the transient transmission through the cavity. We obtain analytical expressions for generic noise and proceed to study the cases of quasistatic, white and 1/f^{α} noise in more detail. Additionally, we propose a way of extracting the noise power spectral density in a frequency band only bounded by the range of the qubit-cavity detuning and with an exponentially decaying error due to finite measurement times. Our results suggest that measurements of the time-dependent transmission probability represent a novel way of extracting noise characteristics.

Noise spectroscopy study of methylammonium lead tribromide single-crystal detectors: Gamma-ray spectroscopy applications

Metal halide perovskites have been studied since 2016 for gamma-ray spectroscopy applications. In this work, we study devices based on methylammonium lead tribromide single crystals as gamma-ray detectors. These detectors can measure the signal of a single gamma-ray photon but the energy resolution is limited by the noise of the detectors. Such noise is multicomponent and a deeper investigation was carried out by measuring the noise power spectral density of the devices for different bias voltages. Non-biased devices were found to behave as an idealized equivalent electrical circuit with the main noise source being thermal noise. In the case of biased devices, the dominant noise source is found to be the 1/f noise which becomes preponderant at lower frequency (<1 MHz). These results demonstrate the major contribution of the flicker noise in perovskite detectors of this kind and lay the foundation for next developments to make them compatible with spectrometric applications.

Federated Edge Learning With Misaligned Over-the-Air Computation

Over-the-air computation (OAC) is a promising technique to realize fast model aggregation in the uplink of federated edge learning (FEEL). OAC, however, hinges on accurate channel-gain precoding and strict synchronization among edge devices, which are challenging in practice. As such, how to design the maximum likelihood (ML) estimator in the presence of residual channel-gain mismatch and asynchronies is an open problem. To fill this gap, this paper formulates the problem of misaligned OAC for FEEL and puts forth a whitened matched filtering and sampling scheme to obtain oversampled, but independent samples from the misaligned and overlapped signals. Given the whitened samples, a sum-product ML (SP-ML) estimator and an aligned-sample estimator are devised to estimate the arithmetic sum of the transmitted symbols. In particular, the computational complexity of our SP-ML estimator is linear in the packet length, and hence is significantly lower than the conventional ML estimator. Extensive simulations on the test accuracy versus the average received energy per symbol to noise power spectral density ratio (EsN0) yield two main results: 1) In the low EsN0 regime, the aligned-sample estimator can achieve superior test accuracy provided that the phase misalignment is not severe. In contrast, the ML estimator does not work well due to the error propagation and noise enhancement in the estimation process. 2) In the high EsN0 regime, the ML estimator attains the optimal learning performance regardless of the severity of phase misalignment. On the other hand, the aligned-sample estimator suffers from a test-accuracy loss caused by phase misalignment.

A Wasserstein GAN Autoencoder for SCMA Networks

In the view of the exponential growth of mobile applications, the Sparse Code Multiple Access (SCMA) is one promising code-domain Non-Orthogonal Multiple Access (NOMA) technique. The challenge in the adoption of SCMA in practical networks is twofold: designing optimal codebooks at the transmitter and decoding the data at the receiver. However, most of the works available in the literature address only one aspect. In this letter, we design an end-to-end SCMA en/deconding structure based on the integration between a state-of-the-art autoencoder architecture and a novel Wasserstein Generative Adversarial Network (WGAN) that improves the robustness to the channel noise. We compare the performance obtained by the proposed network with conventional computationally intensive solutions and a deep learning based autoencoder. The performance achieved show better performances in terms of Symbol Error Rate (SER), especially at low energy per bit to noise power spectral density ratio.

Degradation Characteristics and Reliability Assessment of 1310 nm VCSEL for Microwave Photonic Link

The long-term reliability of the commercially available vertical-cavity surface-emitting laser (VCSEL) at 1310 nm wavelength is investigated. To do so, a high current accelerated life test is used to evaluate the 1310 nm VCSEL reliability. Variations of properties that depend on the operating condition are characterized by the light-current-voltage, leakage current and low-frequency noise. When the aging current is 6 mA, 8 mA and 10 mA, the maximum output power reduces by 5%, 6% and 15% of the initial value, respectively. It is demonstrated theoretically and experimentally that the leakage current increases and reverse bias breakdown voltage decreases after the accelerated current aging test. The current noise power spectral density increases after the device ages, and the noise increases with the augment of the electrical stress. When the bias current of VCSEL is below the threshold, the frequency index factor and noise amplitude gradually increase with the bias current increase. Further, lifetime fitting curves of the devices at an accelerating current of 6 mA, 8 mA and 10 mA are obtained, and the median lifetime of 67 years at the operating current is extrapolated.

Three-dimensional stacked filter: A non-linear filter for series images obtained using a transmission electron microscope

De-noising is an important issue in quantitative high-resolution transmission electron microscopy (HRTEM), and its roles become even more important in applications such as beam-sensitive materials and dynamic characterisations, where the attainable signal-to-noise ratio (SNR) of HRTEM images is frequently limited. In this study, we introduce a three-dimensional stacked filter (3DSF), a novel non-linear filter in which a series of HRTEM images is stacked into a 3D data cube and then treated with the Wiener filter in the 3D domain. In comparison to the traditional Wiener filter, which is widely used for individual images, this filter can accurately estimate the power spectral density of noise and filter images with a higher SNR, fewer artefacts and greater computation efficiency, which works particularly well for HRTEM images containing periodic information and feature similarities in successive micrographs, as demonstrated by simulated and experimental images of graphene and metal–organic framework (MOF). When applied to an ultra-low dose (∼8 e/Å2) HRTEM image stack of MOF MIL-101, the 3DSF could distinguish 40 consecutive frames, revealing the trajectory of subtle lattice shrinkage during the exposure.

Line shape of a delayed self-heterodyne varied with noise types and delays.

The delayed self-heterodyne and self-homodyne (DSH) method is widely used for measuring the line shapes of high coherent lasers. This method results in an autocorrelation of a laser line under the condition of a delay that is much larger than its coherent time. In practice, the delay is often not so long, especially for very narrow linewidth lasers, resulting in errors in rebuilding the laser's line shape from the DSH line. Many papers were devoted to the topic, but most of them are based on the formula for white noise. Analytical formulas of phase variance for 1/f noises are presented in this paper; the DSH line shapes for different noise types and different delay lengths are simulated based on the formulas. Some experimental data of the DSH line, combined with the power spectral density of frequency noise, are processed, showing good agreement with the theoretical analysis. It is indicated that the DSH line shape shows complicated behaviors varied with the delay, with noise types, and with the measurement duration. Such effects are to be compensated for in retrieving the laser's linewidth from the DSH data.