Noise Power Research Articles

Standardization of scan protocols for RT CT simulator from different vendors using quantitative image quality technique.

To investigate the feasibility of standardizing RT simulation CT scanner protocols between vendors using target-based image quality (IQ) metrics. A systematic assessment process in phantom was developed to standardize clinical scan protocols for scanners from different vendors following these steps: (a) images were acquired by varying CTDIvol and using an iterative reconstruction (IR) method (IR: iDose and model-based iterative reconstruction [IMR] of CTp-Philips Big Bore scanner, SAFIRE of CTs-Siemens biograph PETCT scanner), (b) CT exams were classified into body and brain protocols, (c) the rescaled noise power spectrum (NPS) was calculated, (d) quantified the IQ change due to varied CTDIvol and IR, and (e) matched the IR strength level. IQ metrics included noise and texture from NPS, contrast, and contrast-to-noise ratio (CNR), low contrast detectability (d'). Area under curve (AUC) of the receiver operation characteristic curve of d' was calculated and compared. The level of change in the IQ ratio was significant (>0.6) when using IMR. The IQ ratio change was relatively low to moderate when using either iDose in CTp (0.1-0.5) or SAFIRE in CTs (0.1-0.6). SAFIRE-2 in CTs showed a closer match to the reference body protocol when compared to iDose-3 in CTp. In the brain protocol, iDose-3 in CTp could be matched to the low to moderate level of SAFIRE in CTs. The AUC of d' was highest when using IMR in CTp with lower CTDIvol, and SAFIRE in CTs performed better than iDose in CTp CONCLUSION: It is possible to use target-based IQ metrics to evaluate the performance of the system and operations across various scanners in a phantom. This can serve as an initial reference to convert clinical scanned protocols from one CT simulation scanner to another.

Performance Enhancement for B5G/6G Networks Based on Space Time Coding Schemes Assisted by Intelligent Reflecting Surfaces with Higher Modulation Orders.

Intelligent Reflecting Surfaces (IRS) and Multiple-Input Single-Output (MISO) technologies are essential in the fifth generation (5G) networks and beyond. IRS optimizes the signal propagation and the coverage and is a viable approach to address the issues caused by fading channels that limits the spectral efficiency, while MIMO enhances data rates, reliability, and spectral efficiency by using multiple antennas at both transmitter and receiver ends. This paper proposes an IRS-assisted MISO system using the Orthogonal Space-Time Block Code (OSTBC) scheme to enhance the channel reliability and reduce the Bit Error Rate (BER) in wireless communication systems. The proposed system exploits the benefits from the transmit diversity gain of the OSTBC scheme as well as from the bit energy to noise power spectral density (Eb/No) improvement of the IRS technology. The presented work explores these combined technologies across different modulation schemes. The obtained results outperform the similar previously published works by considering higher-order modulation schemes as well as the deployment of rate ¾ OSTBC-assisted IRS. Moreover, the obtained results demonstrate that the integration of OSTBC with IRS can yield significant performance improvements in terms of Eb/No by 7 dB and 13 dB when using 16 reflecting elements and 64 reflecting elements, respectively.

Pico-ampere resolution current measurement circuit using Gm-C filter sigma-delta modulator for low-power nanopore DNA sequencing

New generation DNA sequencers use an array of electrochemical cells equipped with nanopores, which produce pico-ampere current levels. Due to the large number of channels, low current levels and bandwidths in the order of a few kHz, in the design of these readout circuits, 2D arrays of in-channel, low noise and low power analog to digital converters are preferred. Previously many different sigma-delta modulators have been presented to convert the nanopore current signal into a digital code. Conventionally, the opamps required in these converters will eventually increase the power dissipation of each channel. In this paper a novel Gm-C filter based second order sigma-delta converter is proposed. In the given design, rather than relying on multiple opamps to achieve the necessary gain and noise performance, only a 4 transistor Gm block is used. Evaluations show that while the input referred noise remains close to previous methods, the power dissipation is considerably reduced. A prototype is also implemented to show the effectiveness of the approach. In a 180-nm design, an ENOB of 12.16 bits, RMS input referred noise of 0.2 pA at 10 kHz bandwidth and power dissipation of 8.27 μW is obtained per channel.

Impacts of sampling on the artificial noise-assisted terahertz secure communication systems

In this paper, we investigate an artificial noise (AN)-assisted terahertz (THz) secure communication system. Different from previous studies, we consider a non-ideal analog-to-digital converter (ADC) in the AN-THz system. Specifically, both synchronization noise and quantization noise in ADC are investigated. The normalized distortion matric is employed to calculate synchronization noise power and the Bellman’s theory is introduced for quantization noise power. Under the constrain of limited ADC power, the secrecy performance presents a ‘U-shaped’ curve versus the sampling rate and therefore the optimal sampling rate is derived. Moreover, we validate our theoretical model in the experiment, and our experimental results in 102 GHz show the synchronization noise power varies with the square of timing error, and the quantization noise power is affected by the total data length, which agree well with the model predictions.

Effect of frame rate on image quality in cardiology evaluated using an indirect conversion dynamic flat-panel detector.

To verify the effect of the frame rate on image quality in cardiology, we used an indirect conversion dynamic flat-panel detector (FPD). We quantified the input-output characteristics, and determined the modulation transfer function (MTF) and normalized noise power spectrum (NNPS) of the equipment used in cardiology at 7.5, 10, 15, and 30 frames per second (fps). We also calculated the noise power spectrum for still images and videos at all frame rates and obtained the image lag correction factor r. The input-output characteristics and the MTF agreed even when the frame rate was varied. The NNPS tended to decrease uniformly as a function of frequency at increasing frame rates. The factor r decreased as a function of the frame rate, and its minimum value was 30 fps. Our results suggest that high-frame-rate imaging in cardiology using indirect conversion dynamic FPDs is affected by image lag.

A novel method for reducing the effect of doppler frequency shift in high-speed railway mobile communication using machine learning

Currently, high-speed railway systems are rapidly expanding worldwide, necessitating reliable and efficient mobile communication solutions. However, the Doppler frequency shift caused by the high speeds of trains presents significant challenges to communication systems, particularly those using OFDM in LTE. This paper presents a novel for Doppler frequency compensation in high-speed railway communication based on the results of estimating the train's velocity using machine learning algorithms. By leveraging advanced algorithm such as neural networks, our method dynamically predicts and compensates for Doppler shifts in real-time. In this proposed novel, the Doppler frequency value is calculated based on the actual train’s velocity and the scenario of a high-speed railway, then the Doppler frequency is used to compensate the carrier frequency offset (CFO) directly at the Access Point (AP) device on the train. We conduct simulations to evaluate the effectiveness of our proposed solution in a high-speed railway scenario. The results demonstrate a marked improvement in communication reliability and data integrity, highlighting the potential of machine learning to enhance the performance of mobile communication systems in high-speed railways. The results of the proposed model are evaluated based on the system’s bit error rate BER after the CFO compensation decreases and the ratio of average energy per bit (Eb) to noise power density (N0) (Eb/N0) increases. This shows that the proposed solution works effectively and reduces the system’s bit errors while improving the communication performance. This study opens new avenues for integrating intelligent systems in transportation networks, ensuring seamless connectivity, and improving passenger experience

Surpassing the Standard Quantum Limit Using an Optical Spring.

Quantum mechanics places noise limits and sensitivity restrictions on physical measurements. The balance between unwanted backaction and the precision of optical measurements imposes a standard quantum limit (SQL) on interferometric systems. In order to realize a sensitivity below the SQL, it is necessary to leverage a backaction evading measurement technique, reduce thermal noise to below the level of backaction, and exploit cancellations of any excess noise contributions at the detector. Many proof of principle experiments have been performed, but only recently has an experiment achieved sensitivity below the SQL. In this work, we extend that initial demonstration and realize sub-SQL sensitivity nearly two times better than previous measurements, and with an architecture applicable to interferometric gravitational wave detectors. In fact, this technique is directly applicable to Advanced LIGO, which could observe similar effects with a detuned signal recycling cavity. We measure a total sensitivity below the SQL by 2.8dB, corresponding to a reduction in the noise power by 72±5.1% below the quantum limit. Through the use of a detuned cavity and the optical spring effect, this noise reduction is tunable, allowing us to choose the desired range of frequencies that fall below the SQL. This result demonstrates access to sensitivities well below the SQL at frequencies applicable to LIGO, with the potential to extend the reach of gravitational wave detectors further into the Universe.

In Situ Detection of Interfacial Ions at the Single-Bond Level.

Detecting the ionic state at the solid-liquid interface is essential to reveal the various chemical and physical processes that occur at the interface. In this study, the adsorption states of the highly electronegative ions F- and OH- at the solid-liquid interface are detected by using the scanning tunneling microscopy break junction technique. With the active hydrogen atom of the amino group as a probe, the formed ionic hydrogen bonds are successfully detected, thereby enabling in situ monitoring of the ionic state at the solid-liquid interface. Through noise power spectral density analysis and theoretical simulations, we reveal the mechanism by which ionic hydrogen bonds at the interface affect the charge transport properties. In addition, we discover that the ionic state at the solid-liquid interface can be effectively manipulated by electric fields. Under high electric fields, the concentration of the anion near the electrode is higher, and the proportion of hydrogen bonds formed is greater than that under low electric fields. This study of the interfacial ionic state at the single-bond level provides guidance for the design of high-performance materials for energy conversion and environmental purification.

Design of a Near-Field Synthetic Aperture Radar Imaging System Based on Improved RMA

Traditional near-field synthetic aperture radar (SAR) imaging algorithms reveal target features by exploiting signal amplitude and phase information. However, electromagnetic wave propagation is constrained by short distance. Therefore, the spherical wave approximation needs to be considered. In addition, it is also limited by equipment ambient noise, azimuth-distance coupling, wave scattering, and transmission power. Both the amplitude and phase of the signal suffer from the interference of multiple clutter, so they cannot be effectively utilized. To address these issues, this paper introduces a covering penetration detection system based on an improved Range Migration Algorithm (IMRMA) imaging method. Firstly, the proposed method minimizes interferences from the front end of the system using an optimized window to balance denoising and information preservation. Next, interval non-uniform interpolation, instead of Stolt interpolation decoupling, is employed to reduce the computational overhead significantly. To minimize the effects due to wave scattering and propagation loss, distance information is enhanced using amplitude and phase compensation. This reduces scattering effects and enhances image quality. An experimental system is constructed based on a vector network analyzer (VNA) to image the target. The proposed method takes about half the time of traditional RMA. The PSNR in the chunky bowl experiment is higher than 14 dB, which is higher than all the compared methods in the paper. The test results show that the designed system and the reported method can effectively achieve high-resolution images by strengthening the target intensity and suppressing the environmental artifacts.

A High-Resolution Discrete-Time Second-Order ΣΔ ADC with Improved Tolerance to KT/C Noise Using Low Oversampling Ratio.

This work presents a novel ΣΔ analog-to-digital converter (ADC) architecture for a high-resolution sensor interface. The concept is to reduce the effect of kT/C noise generated by the loop filter by placing the gain stage in front of the loop filter. The proposed architecture effectively reduces the kT/C noise power from the loop filter by as much as the squared gain of the added gain stage. The gain stage greatly relaxes the loop filter's sampling capacitor requirements. The target resolution is 20 bit. The sampling frequency is 512 kHz, and the oversampling ratio (OSR) is only 256 for a target resolution. Therefore, the proposed ΔΣ ADC structure allows for high-resolution ADC design in an environment with a limited OSR. The proposed ADC designed in 65 nm CMOS technology operates at supply voltages of 1.2 V and achieves a peak signal-to-noise ratio (SNR) and Schreier Figure of Merit (FoMs) of 117.7 dB and 180.4 dB, respectively.

Noise Reduction Using Sparsity Constrained and Regularized Iterative Thresholding Algorithm and Dictionary

Dictionary-based methods are recognized for their ability to estimate clear speech from speech contaminated with noise. However, these techniques face a limitation in distinguishing between speech and noise components. The presented algorithm addresses this challenge by introducing an innovative solution through an iterative thresholding method. In this method, the thresholding is based on noise characteristics and remains independent of variations in noise power. To determine the stopping criteria for thresholding, the algorithm leverages the structure of the speech signal in time–frequency domains using the Gini Index. Remarkably, this technique adeptly extracts reliable signal components from a noisy time–frequency magnitude spectrum, performing well under non-varying and varying Signal-to-Noise Ratio (SNR) conditions. Importantly, it achieves this without the need for mask functions, voice activity detection techniques, noise or mixture dictionaries, or SNR information, which are essential components in other dictionary-based methods. Following the thresholding process, the clean speech is assessed using a dictionary-based approach to restore perceptual loss. In evaluating its performance, the algorithm is compared with traditional enhancement techniques concerning perceptual evaluation of speech quality and short-time objective intelligibility. The assessment is conducted under various background noise conditions, including babble, white, factory, and Volvo noises. The proposed algorithm exhibits superior performance, particularly in low and varying SNR scenarios.

Transcriptomic analysis of the response mechanisms of black rockfish (Sebastes schlegelii) under noise stress from offshore wind farms

During the operational phase of offshore wind farms, the generation of low-frequency underwater noise has received widespread attention due to its potential adverse impact on fish health. This study conducted a field survey of underwater noise at offshore wind farms located in Shandong province, China. Subsequently, a small-scale experiment was conducted to study the stress on black rockfish (Sebastes schlegelii). The fish were exposed to noise with dominant frequency of 80 Hz, 125 Hz and 250 Hz. These frequencies are same with the frequencies from wind power noise (wpn) at the actual site. After a 40-day experimental period, transcriptome sequencing was conducted on brain, liver, and kidney tissues of black rockfish to elucidate the underlying molecular mechanisms involved in the response to noise stress originating from offshore wind farms. The results revealed that the 125 Hz group exhibited the highest number of differentially expressed genes (DEGs) between the noise-exposed and control check group (CK group), with a total of 797 in the brain, 1076 in the liver, and 2468 in the kidney. Gene Ontology (GO) analysis showed that DEGs were significantly enriched in entries related to cellular processes, membrane components, binding, and metabolism. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that DEGs were enriched mainly in metabolism, immunity, apoptosis, signal transduction, and diseases. The findings indicate that prolonged exposure to underwater noise from offshore wind farms may induce metabolic imbalance, immune dysfunction, and an increased risk of myocardial diseases in black rockfish.

Dephasing in Fluxonium Qubits from Coherent Quantum Phase Slips

Phase slips occur across all Josephson junctions (JJs) at a rate that increases with the impedance of the junction. In superconducting qubits composed of JJ-array superinductors—such as fluxonium—phase slips in the array can lead to decoherence. In particular, phase-slip processes at the individual array junctions can coherently interfere, each with an Aharonov-Casher phase that depends on the offset charges of the array islands. These coherent quantum phase slips (CQPS) perturbatively modify the qubit frequency, and therefore charge noise on the array islands will lead to dephasing. By varying the impedance of the array junctions, we design a set of fluxonium qubits in which the expected phase-slip rate within the JJ array changes by several orders of magnitude. We characterize the coherence times of these qubits and demonstrate that the scaling of CQPS-induced dephasing rates agrees with our theoretical model. Furthermore, we perform noise spectroscopy of two qubits in regimes dominated by either CQPS or flux noise. We find that the noise power spectrum associated with CQPS dephasing appears to be featureless at low frequencies and not 1/f. Numerical simulations indicate that this behavior is consistent with charge noise generated by charge-parity fluctuations within the array. Our findings broadly inform JJ-array-design trade-offs, relevant for the numerous superconducting-qubit designs employing JJ-array superinductors. Published by the American Physical Society 2024

RETNet: Resolution enhancement Transformer network for magnetic particle imaging based on X-space

Magnetic Particle Imaging (MPI) can visualize the concentration distribution of superparamagnetic iron-oxide nanoparticles (SPIONs) in tissues with the advantages of high sensitivity and high temporal resolution. However, the low spatial resolution of MPI limits its application. Increasing the gradient strength of the selection field can improve the resolution of MPI, but also increase power consumption and noise. A feasible and cost-effective method to address this limitation is to reconstruct high gradient (HG) image from low gradient (LG) image using algorithms. Deep learning has been a powerful tool for improving the resolution of medical imaging techniques. In this study, we propose a Resolution Enhancement Transformer Network (RETNet) for reconstructing HG image with high-resolution from LG image with low-resolution as input, avoiding high power consumption and high noise in the system with HG field. RETNet leverages a shallow feature extractor to capture shallow features, a cross-scale-Transformer (CST) to focus on textural features, a residual-swin-Transformer (RST) to focus on structural features, and an image reconstruction module to aggregate these three types of features and reconstruct the HG image. Textural and structural features extracted can ensure the integrity of the details and the realization of high definition in the reconstructed image. Ablation experiments demonstrate the significant contribution of these two modules to reconstruct the HG image. Comparative experiments, including experiments at noise-free and multiple noise levels, confirm the high robustness of RETNet. Simulation, phantom, and in vivo experiments consistently demonstrate that RETNet outperforms competing methods and effectively improves the resolution of MPI.

Decoherence induced by a sparse bath of two-level fluctuators: Peculiar features of 1/f noise in high-quality qubits

Progress in fabrication of semiconductor and superconductor qubits has greatly diminished the number of decohering defects, thus decreasing the devastating low-frequency 1/f noise and extending the qubits' coherence times (dephasing time T2* and the echo decay time T2). However, large qubit-to-qubit variation of the coherence properties remains a problem, making it difficult to produce a large-scale register where all qubits have a uniformly high quality. In this work, we show that large variability is a characteristic feature of a qubit dephased by a sparse bath made of many (n≫1) decohering defects, coupled to the qubit with similar strength. We model the defects as two-level fluctuators (TLFs) whose transition rates γ are sampled from a log-uniform distribution over an interval [γm,γM], which is a standard model for 1/f noise. We investigate decoherence by such a bath in the limit of high-quality qubit, i.e., when the TLF density d is small (the limit of sparse bath, with d=n/w≪1, where n is the number of TLFs and w=ln[γM/γm] is the log-width of the distribution). We show that different realizations of the bath produce very similar noise power spectra S(f)∼1/f, but lead to drastically different coherence times T2* and T2. Thus the spectral density S(f) does not determine coherence of a qubit coupled to a sparse TLF bath, as opposed to a dense bath; instead, decoherence is controlled by only a few exceptional fluctuators, determined by their value of γ. We show that removing only two of these TLFs greatly increases T2 and T2* times. Our findings help theoretical understanding and further improvements in the coherence properties of semiconductor and superconductor qubits, battling the 1/f noise in these platforms. Published by the American Physical Society 2024

Design and FPGA Implementation of Signal Strength Measurement Techniques for Satellite Communication Systems

Communication receivers perform three major functions, frequency down conversion, IF demodulation and subcarrier demodulation. The functioning of a receiver is mainly controlled by input signal strength and relative dynamics. Signal strength is measured in terms of Signal to Noise ratio (SNR) and Carrier to Noise power density (C/No). Any measure of signal strength indirectly gives information about receiver performance for that period. Apart from this, SNR measurement in close loop with Phase Locked Loop (PLL) parameter forms the adaptive PLL system, which is one of the driving forces for this paper. The focus of this paper is to find suitable signal strength measurement techniques and their implementation for satellite communication systems. Signal to Noise Variance method (SNV) and Narrow band Wide band Power Ratio (NWPR) methods are considered based on the performance and realization aspects. All techniques require division, logarithm, and multiplication functions for their realization in hardware. CO-ordinate Rotation Digital Computer (CORDIC) algorithm is considered for realizing logarithm function. A comparison study is done for developed algorithm with Intellectual Property (IP) core. Developed SNR techniques are simulated for Binary Phase Shift Keying (BPSK) demodulator system and performance is evaluated for Additive White Gaussian Noise (AWGN). The paper describes the FPGA design and simulations of these techniques. Developed design is targeted to commercial and space qualified FPGA platforms. FPGA implementations results are compared with system level simulation results, and both are found to be satisfactory. Application of developed system in adaptive BPSK demodulator is also presented.

Covert Communications via Two-Way IRS With Noise Power Uncertainty

Covert Communications via Two-Way IRS With Noise Power Uncertainty

Comparative study of DCT-and DHT-based OFDM systems over doubly dispersive fading channels

Abstract In high-mobility operating scenarios orthogonal frequency division multiplexing (OFDM) system lacks its optimality, intercarrier interference (ICI) occurs and the Doppler shifts deteriorate the orthogonality of the subcarriers. However, this problem can be overcome by utilizing complicated equalizers at the receiver. Discrete cosine transform (DCT) and discrete Hartley transform (DHT) have been used instead of discrete Fourier transform (DFT) in the standard OFDM system. The performance results achieved enhancement over dispersive selective channels that cannot be accomplished with a standard OFDM system, even with utilizing complex equalizers. In this paper, the performance of the DCT-based OFDM system and DHT-based OFDM system is compared and analyzed with respect to DFT-based OFDM system performance over doubly dispersive fading channel at various Doppler shifts, the block diagrams of the proposed systems are provided to simplify the theoretical analysis by making it easier to follow. Simulation results emphasized that the performance of DCT and DHT-based OFDM systems under doubly dispersive fading conditions scenario outperforms DFT-based OFDM system of order 3 dB energy per bit to noise power spectral density ratio (Eb/N0).

Spin noise spectroscopy of an alignment-based atomic magnetometer

Optically pumped magnetometers (OPMs) are revolutionizing the task of magnetic-field sensing due to their extremely high sensitivity combined with technological improvements in miniaturization which have led to compact and portable devices. OPMs can be based on spin-oriented or spin-aligned atomic ensembles which are spin polarized through optical pumping with circular or linear polarized light, respectively. Characterization of OPMs and the dynamical properties of their noise is important for applications in real-time sensing tasks. In our work, we experimentally perform spin noise spectroscopy of an alignment-based magnetometer. Moreover, we propose a stochastic model that predicts the noise power spectra exhibited by the device when, apart from the strong magnetic field responsible for the Larmor precession of the spin, white noise is applied in the perpendicular direction aligned with the pumping-probing beam. By varying the strength of the noise applied as well as the linear-polarization angle of incoming light, we verify the model to accurately predict the heights of the Larmor-induced spectral peaks and their corresponding linewidths. Our work paves the way for alignment-based magnetometers to become operational in real-time sensing tasks. Published by the American Physical Society 2024

Dual-Split CT to Simulate Multiple Radiation Doses From a Single Scan-Liver Lesion Detection Compared With Dose-Matched Single-Energy CT.

The aim of this study was to evaluate the potential use of simulated radiation doses from a dual-split CT scan for dose optimization by comparing their lesion detectability to dose-matched single-energy CT acquisitions at different radiation dose levels using a mathematical model observer. An anthropomorphic abdominal phantom with liver lesions (5-10 mm, both hyperattenuating and hypoattenuating) was imaged using a third-generation dual-source CT in single-energy dual-source mode at 100 kVp and 3 radiation doses (5, 2.5, 1.25 mGy). The tube current was 67% for tube A and 33% for tube B. For each dose, 5 simulated radiation doses (100%, 67%, 55%, 45%, 39%, and 33%) were generated through linear image blending. The phantom was also imaged using traditional single-source single-energy mode at equivalent doses. Each setup was repeated 10 times. Image noise texture was evaluated by the average spatial frequency (fav) of the noise power spectrum. Liver lesion detection was measured by the area under the receiver operating curve (AUC), using a channelized Hotelling model observer with 10 dense Gaussian channels. Fav decreased at lower radiation doses and differed between simulated and single-energy images (eg, 0.16 mm-1 vs 0.14 mm-1 for simulated and single-energy images at 1.25 mGy), indicating slightly blotchier noise texture for dual-split CT. For hyperattenuating lesions, the mean AUC ranged between 0.92-0.99, 0.81-0.96, and 0.68-0.89 for single-energy, and between 0.91-0.99, 0.78-0.91, and 0.70-0.85 for dual-split at 5 mGy, 2.5 mGy, and 1.25 mGy, respectively. For hypoattenuating lesions, the AUC ranged between 0.90-0.98, 0.75-0.93, and 0.69-0.86 for the single-energy, and between 0.92-0.99, 0.76-0.87, and 0.67-0.81 for dual-split at 5 mGy, 2.5 mGy, and 1.25 mGy, respectively. AUC values were similar between both modes at 5 mGy, and slightly lower, albeit not significantly, for the dual-split mode at 2.5 and 1.25 mGy. Lesion detectability was comparable between multiple simulated radiation doses from a dual-split CT scan and dose-matched single-energy CT. Noise texture was slightly blotchier in the simulated images. Simulated doses using dual-split CT can be used to assess the impact of radiation dose reduction on lesion detectability without the need for repeated patient scans.