Noise Equalization Research Articles

Low-complexity adaptive multipath interference and channel noise mitigation scheme based on optimized detection for bandwidth-limited IM/DD systems.

In this Letter, we propose a low-complexity adaptive multipath interference (MPI) and channel noise mitigation (AMCM) scheme in the receiver digital signal processing (DSP) for bandwidth-limited intensity modulation and direct detection (IM/DD) transmission systems. Following channel equalization, MPI and channel noise are distributed in the low- and high-frequency parts, respectively, and exhibit the characteristics of bandstop filtering. The proposed AMCM is designed based on optimized detection, which incorporates an adaptive bandpass filter (BPF) and a log-maximum a posteriori estimation with a lookup table-based fixed number of surviving states (LUT-based FS-MAP) decoder. The adaptive BPF is capable of mitigating the MPI and channel noise based on spectral distribution. Moreover, the LUT-based FS-MAP decoder can eliminate intersymbol interference (ISI) introduced by the BPF. The proposed AMCM is implemented in an O-band 56-Gbaud IM/DD optical 4-level pulse amplitude modulation (PAM-4) system with a 10.7-GHz bandwidth over a 10-km standard single-mode fiber with different linewidths. The results demonstrate that the proposed AMCM scheme can enhance signal-to-interference ratio (SIR) tolerance to 11 dB with only three real-valued multiplications per symbol, achieving a 7% hard-decision forward error correction threshold. To the best of our knowledge, for the first time, this represents the inaugural instance of optimized detection being employed for MPI mitigation.

High-Resolution Power Doppler Using Null Subtraction Imaging.

To improve the spatial resolution of power Doppler (PD) imaging, we explored null subtraction imaging (NSI) as an alternative beamforming technique to delay-and-sum (DAS). NSI is a nonlinear beamforming approach that uses three different apodizations on receive and incoherently sums the beamformed envelopes. NSI uses a null in the beam pattern to improve the lateral resolution, which we apply here for improving PD spatial resolution both with and without contrast microbubbles. In this study, we used NSI with three types of singular value decomposition (SVD)-based clutter filters and noise equalization to generate high-resolution PD images. An element sensitivity correction scheme was also proposed as a crucial component of NSI-based PD imaging. First, a microbubble trace experiment was performed to evaluate the resolution improvement of NSI-based PD over traditional DAS-based PD. Then, both contrast-enhanced and contrast free ultrasound PD images were generated from the scan of a rat brain. The cross-sectional profile of the microbubble traces and microvessels were plotted. FWHM was also estimated to provide a quantitative metric. Furthermore, iso-frequency curves were calculated to provide a resolution evaluation metric over the global field of view. Up to six-fold resolution improvement was demonstrated by the FWHM estimate and four-fold resolution improvement was demonstrated by the iso-frequency curve from the NSI-based PD microvessel images compared to microvessel images generated by traditional DAS-based beamforming. A resolvability of [Formula: see text] was measured from the NSI-based PD microvessel image. The computational cost of NSI-based PD was only increased by 40 percent over the DAS-based PD.

Noise equalization scheme based on probabilistic shaping and complex-valued ANN for dual-polarization continuous spectrum NFDM system with high-order modulation formats

In dual-polarization continuous spectrum nonlinear frequency division multiplexing (DP-CS NFDM) systems, the presence of noise destroys the independence between subcarriers in the nonlinear spectral domain (NSD). Additionally, as the modulation order and the number of subcarriers increase, the signal power increases and the effect of noise on the performance of the system becomes more severe. In this paper, we propose a noise equalization scheme based on probabilistic shaping (PS) and complex-valued neural network (c-ANN) for dual-polarization transmission CS NFDM system with high-power signals. The scheme utilizes PS to reduce the distribution probability of high-power constellation points of the signal with high-order modulation format, to decrease the peak-to-average power ratio of the continuous spectrum subcarriers and the average power of the signal, which can achieve the suppression and equalization of the amplifier spontaneous emission (ASE) noise and the processing noise. In addition, the scheme uses the c-ANN to effectively reduce the correlation between subcarriers caused by the noise and improve the system performance. The effectiveness of the proposed scheme is verified in the DP-CS NFDM system, and the simulation results show that the Q-factor gain is enhanced by roughly 1.1 dB and 0.8 dB for the number of subcarriers of 128 and 256, respectively, compared to the classic nonlinear Fourier transform (NFT) scheme. Among them, with different noise figure (NF) and satisfying the 7% forward error correction (FEC) threshold, the 512QAM signal with an entropy of 8 after equalization increase the transmission distance by 80 km longer than that of uniform 256QAM signals for the number of subcarriers of 128. Compared with the joint scheme based on PS and real-valued neural network (r-ANN), this scheme has better equalization performance at the same complexity, and the complexity can be reduced by 50% under the same performance.

Harmonic active mode-locking optoelectronic oscillator with suppressed supermode noise based on pulse intensity feedback.

A harmonic active mode-locking optoelectronic oscillator (HAML-OEO) with pulse intensity feedback is proposed and experimentally demonstrated. It is capable of generating microwave pulses characterized by suppressed supermode noise, uniform intensity, and tunable repetition rates. Unlike traditional HAML-OEOs, active mode-locking and pulse intensity feedback are simultaneously achieved through the use of a dual-drive Mach-Zehnder modulator (DDMZM). By synchronously feeding back the generated microwave pulses to the DDMZM, each pulse undergoes a loss proportional to its intensity, facilitating pulse intensity equalization and supermode noise suppression. In the experiment, intensity-equalized microwave pulse trains with repetition rates of 499 kHz and 998 kHz are generated by the 5th- and 10th-order HAML-OEOs, respectively, with the measured supermode noise suppression ratios exceeding 40 dB.

Joint Equalization and Impulsive Noise Mitigation for OTFS Based on EP

Joint Equalization and Impulsive Noise Mitigation for OTFS Based on EP

Partially decoupled polarization demultiplexing and phase noise equalizer for Alamouti code-based simplified coherent systems.

Alamouti space-time block code (STBC) combined with a simple heterodyne coherent receiver can realize polarization-insensitive phase-diversity detection to reduce the cost. In the receiver, a joint equalizer has been used for STBC's polarization demultiplexing and phase tracking. However, the joint equalizer requires two different step size parameters to update the tap weight coefficients for polarization demultiplexing and the phase noise estimation. This leads to the search process being complex so requiring more iterations for convergence. In this paper, we propose a partially decoupled equalizer that consists of a polarization and phase decoupled equalizer (PPDE) and a pilot-aided blind phase search (P-BPS) algorithm to accelerate the convergence and improve the phase noise tolerance. By theoretically calculating the phase noise, the PPDE can achieve polarization demultiplexing with only one single step size parameter, thus suppressing the searching space and greatly reducing the iterations required for convergence. In the carrier phase recovery stage, the P-BPS algorithm can effectively improve the phase noise tolerance and solve the cyclic slip problem of BPS. We conduct numerical simulations and an experiment to transmit a quadrature phase-shift keying (QPSK) signal. The results demonstrate that the number of iterations required for PPDE convergence is only half of that of the joint equalizer while maintaining polarization-insensitive characteristics in large phase noise. Meanwhile, the achievable linewidth tolerance of P-BPS is increased by three times compared with DD-LMS.

Development of an adaptive finite impulse response filter optimization algorithm using rough set theory

Signal processing is crucial that as one sends information, there is a corresponding process to encode, decode, and clean the signal of unwanted noise and disruptions via use of filters. Due to the environment and how unpredictable it can be and how noise can come from almost anywhere, the typical filter to be used are adaptive filters. Adaptive filters are non-linear filters and have been used regularly regarding adaptive signal processing, this means that the filter changes accordingly and adapts to the environmental noise surrounding it. The world today has numerous applications for adaptive filters such as channel equalization and acoustic noise cancellation. This incentivizes the further development of this specific technology and the constant research that is ongoing. The main component when it comes to adaptive filtering is the algorithms used for the filter. This research compares the least mean square (LMS) and recursive least square (RLS) algorithms concerning their effectiveness in filtering out unwanted acoustic noises. The paper will cover the design and implementation of an optimized rough set based adaptive finite impulse response (FIR) filter for acoustic noise cancellation. The microstrip and bowtie antenna were used to relay the data. The software MATLAB was used for the simulation.

Almost lossless compression of noisy images

Abstract An almost lossless compression method for images is introduced adapted to the temporal noise of image sensors. In a first step, a non-linear gray value transform is applied to generate an image with a gray value independent temporal noise and less bits than the original image. The chosen value for the standard deviation of the temporal noise in the transformed image determines how accurately mean values and the standard deviation of temporal noise can be computed and to which extent the image can be compressed further by a lossless compression in a second step. Just a measurement of the noise characteristics according to the open and international EMVA standard 1288, a non-linear gray value transform for noise equalization, and an open source lossless compression algorithm are required to use this new compression method.

Multi-layered adaptive neoangiogenesis Intra-Operative quantification (MANIOQ).

Quantification of vascularization volume can provide valuable information for diagnosis and prognosis in vascular pathologies. It can be adapted to inform the surgical management of gliomas, aggressive brain tumors characterized by exuberant sprouting of new blood vessels (neoangiogenesis). Filtered ultrafast Doppler data can provide two main parameters: vascularization index (VI) and fractional moving blood volume (FMBV) that clinically reflect tumor micro vascularization. Current protocols lack robust, automatic, and repeatable filtering methods. We present a filtrating method called Multi-layered Adaptive Neoangiogenesis Intra-Operative Quantification (MANIOQ). First, an adaptive clutter filtering is implemented, based on singular value decomposition (SVD) and hierarchical clustering. Second a method for noise equalization is applied, based on the subtraction of a weighted noise profile. Finally, an in vivo analysis of the periphery of the B-mode hyper signal area allows to measure the vascular infiltration extent of the brain tumors. Ninety ultrasound acquisitions were processed from 23 patients. Compared to reference methods in the literature, MANIOQ provides a more robust tissue filtering, and noise equalization allows for the first time to keep axial and lateral gain compensation (TGC and LGC). MANIOQ opens the way to an intra-operative clinical analysis of gliomas micro vascularization.

Exploring ways to maximize the amplitude of steady state broadband noise signals using time reversal in order to excite structures acoustically

Exciting structures with a broadband noise signal is a method used to assess a structure’s health and how it responds to the noise. Past work has shown that time reversal (TR) acoustics has provided a robust method to focus impulses at high amplitudes. Maximization of the highest possible amplitude while maintaining the desired spectral shape can be challenging. This study explores the benefits of using TR with equalization methods to a steady state broadband noise signal to acoustically excite structures. Tradeoffs exist between the possible amplitude of the focused noise and the duration of the noise and the amount of equalization employed. The spatial extent of the focusing will also be discussed. The use of TR to generate high amplitude broadband noise is compared to standard point application of noise equalization with the overall goal to use this high amplitude noise to excite structures under test.

Noise equalization scheme based on complex-valued ANN for multiple-eigenvalue modulated nonlinear frequency division multiplexing systems.

In multiple-eigenvalue modulated nonlinear frequency division multiplexing (NFDM) systems, the noise degrades the accuracy of the nonlinear Fourier transform (NFT) algorithm, resulting in perturbations in the received eigenvalues and the corresponding discrete spectrum. Moreover, with the increase in the number of eigenvalues and the order of the modulation formats, the impact of noise on the performance of the system is even more. A noise equalization scheme based on complex-valued artificial neural network (c-ANN) for multiple-eigenvalue modulated NFDM systems is proposed. This sceheme inputs the eigenvalues perturbation and the impaired discrete spectrum corresponding to the eigenvalues into the c-ANN in complex form. The scheme constructs a complex-valued logic structure with both amplitude and phase information, overlapping reuse input features and, thereby, effectively reducing the effect of noise on the multiple-eigenvalue NFDM system. The effectiveness of the scheme is verified in long-haul seven-eigenvalue modulated single-polarization NFDM simulation systems with 1GBaud 16APSK/16QAM/64APSK/64QAM modulation formats, and the results show that the scheme outperforms the NFT receiving without equalization by 1 to 2 orders of magnitude in terms of bit error rate (BER). Among them, the transmission distance of the 64APSK signal after equalization exceeds 800km while the BER meets 7% forward error correction (FEC) threshold, which is 600km longer than that of the disequilibrium case, and the spectral efficiency (SE) can reach 1.85bit/s/Hz. Compared with other schemes, the proposed scheme has better equalization performance under the same complexity, and the complexity can be reduced by half or even under the same performance.

Active Control Algorithm of Hybrid Vibroacoustic for Vehicle Interior Sound Quality

Background: In some applications, retaining the residual noise at a specified frequency can provide a better vehicle interior sound quality for occupant’s driving experience. The hybrid vibro-acoustic adaptive noise equalizer (HVA-ANE) algorithm introduces a sound retention factor on the basis of the hybrid vibro-acoustic filter-u, and filter-x least mean square (HVA-FUXLMS) algorithm to achieve control of the sound quality, but it is not possible to retain varying degrees of different frequency bands. The hybrid vibro-acoustic empirical-mode-decomposition frequencydomain block adaptive noise equalizer (HVA-EBANE) algorithm introduces Empirical-Mode- Decomposition (EMD) and frequency domain block methods to achieve different degrees of retention of noise in different frequency bands but cannot deal with the irrelevant frequency components in the error signal. Objective: This paper proposes an improved active control algorithm for vehicle interior sound quality, the so-called hybrid vibro-acoustic EMD frequency-domain block FELMS (HVA-EBFELMS) algorithm. Methods: Based on the filtered error, the least mean square algorithm and the residual filter of the specific frequency band are designed according to the psychoacoustic parameters of each component. The filter filters the irrelevant frequency components in the residual signal, and only retains the frequency components that have a great influence on the sound quality so as to achieve the regulation of the desired sound quality. Results: In order to verify the effectiveness of our algorithm, we used the noise and vibration in the vehicle at idle speed as the object and compared the noise control effect with HVA-ANE and HVAEBANE algorithms considering the sound quality. The simulation experiment shows that our algorithm reduces the loudness of the ear-side noise by more than 40% while taking into account the noise and vibration control. Conclusion: The loudness control effect of hybrid vibro-acoustic EMD frequency-domain block FELMS (HVA-EBFELMS) algorithm is better than HVA-ANE and HVA-EBANE algorithms; it has a better effect of improving loudness as well.

Active sound quality control of vehicle interior noise using a dual sampling-rate active noise equalization algorithm

In-vehicle active sound quality control (ASQC) system is an advanced application of active noise control (ANC) technology, which always suppresses the interior sound pressure or improves the psychoacoustic features. However, the connection between the sound quality control state and the vehicle's working state is normally ignored, and the passenger's sound perception typically expects a linear relationship between the vehicle speed and sound loudness. This paper presents a dual sampling-rate active noise equalization algorithm. The low sampling-rate signal is used to improve system computing efficiency, the high sampling-rate signal is used to improve the ASQC effect, and their conversion communication uses a hold (low to high) and a sampler (high to low). The data relating to the ASQC system was collected, and some sound quality evaluations were conducted for determining two appropriate sampling-rate values. Combining a genetic algorithm and the corresponding ASQC simulation system, the algorithmic optimal convergence coefficients and gain coefficients were further determined at different engine speeds. The verification results of ASQC using this proposed algorithm show that the loudness of interior noise is effectively suppressed; the nonlinear index is reduced to 1.37, improving by 37% relative to the original noise and by 20% compared to the ANC system.

2D Constellation Distortion for Subduing Equalization Noise in Bandwidth- Limited IMDD Systems

Bandwidth-limited IMDD systems suffer from the noise boosted by the strong equalization at the receiver. This letter proposes a multiplication-free approach that reduces the impacts of the equalizer-enhanced colored noise through time-interleaving the received symbols and distorting the two-dimensional (2D) constellation such that the noise correlation is subdued. The 2D distortion map is predefined and retrieved from a look-up table. The proposed 2D constellation distortion is evaluated after the linear feed-forward equalizer and Volterra nonlinear equalizer. Experimental results show a BER reduction of 40% when the 2D constellation distortion is employed after the equalizer for the 135 Gbaud PAM4 and 110 Gbaud PAM6 signals. Owing to the proposed approach, we transmit a net data rate of 250 Gbps/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> PAM4 and PAM6 in the O-band over 2 km of SSMF at a BER of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3.8\times 10^{-3}$ </tex-math></inline-formula> below the 6.7% overhead HD-FEC using a 47 GHz SiP modulator, linear equalization, and the proposed 2D distortion.

Multi-Tone Active Noise Equalizer With Spatially Distributed User-Selected Profiles

In this work we propose a multi-channel active noise equalizer (ANE) that can deal with multi-frequency noise signals and assigns simultaneously different equalization gains to each frequency component at each monitoring sensor. For this purpose, we state a pseudo-error noise signal for each sensor of the ANE, which has to be cancelled out in order to get the desired equalization profiles. Firstly the optimal analytic solution for the ANE filters in the case of single-frequency noise is provided, and an adaptive algorithm based on the Least Mean Squared (LMS) is proposed for the same case. We also show that this adaptive strategy reaches the theoretical solution in steady state. Secondly, we state an equivalent approach for the case of multi-frequency noise based on two alternatives: a common pseudo-error signal at each sensor for all frequencies, and a different pseudo-error signal at each sensor for each frequency. The analytic and adaptive solutions for the ANE control filters have been developed for both pseudo-error alternatives. Finally, the ability of the proposed ANE to achieve simultaneously different user-selected noise profiles in different locations has been validated by their transfer functions and simulations.

A computationally efficient active sound quality control algorithm using local secondary-path estimation for vehicle interior noise

Current active noise equalization or active sound profiling algorithms with a parallel structure are typically used for sound quality improvement of multi-harmonic noise. The computational efficiency and system performance may, however, be severely degraded due to an increase in the length of estimated secondary path or the number of controlled frequencies. To alleviate this problem, a local secondary path estimation and filtered-error structure based active sound quality control (LFE-ASQC) algorithm is proposed in this paper. The algorithm utilizes a set of low-order local secondary path (LSP) models to perform filtering operations and uses the filtered pseudo-error signals instead of usual filtered reference signals to update control filter weights, thus it not only has good spectral reshaping capability but also requires notably low computational effort. Two new LSP modeling methods are also proposed. Moreover, a computational complexity analysis of the proposed LFE-ASQC algorithm is provided. Numerical simulations are conducted to evaluate the accuracy of the LSP modeling methods and the performance of the LFE-ASQC algorithm. In addition, the powerful sound quality of a real vehicle interior noise during acceleration is designed and realized. Experimental results demonstrate that the proposed algorithm achieves satisfactory active sound quality control for stationary and non-stationary multi-tonal noises.

Compressed Sensing-Based Super-Resolution Ultrasound Imaging for Faster Acquisition and High Quality Images.

Goal:Typical SRUS images are reconstructed by localizing ultrasound microbubbles (MBs) injected in a vessel using normalized 2-dimensional cross-correlation (2DCC) between MBs signals and the point spread function of the system. However, current techniques require isolated MBs in a confined area due to inaccurate localization of densely populated MBs. To overcome this limitation, we developed the ℓ1-homotopy based compressed sensing (L1H-CS) based SRUS imaging technique which localizes densely populated MBs to visualize microvasculature in vivo.Methods:To evaluate the performance of L1H-CS, we compared the performance of 2DCC, interior-point method based compressed sensing (CVX-CS), and L1H-CS algorithms. Localization efficiency was compared using axially and laterally aligned point targets (PTs) with known distances and randomly distributed PTs generated by simulation. We developed post-processing techniques including clutter reduction, noise equalization, motion compensation, and spatiotemporal noise filtering for in vivo imaging. We then validated the capabilities of L1H-CS based SRUS imaging technique with high-density MBs in a mouse tumor model, kidney, and zebrafish dorsal trunk, and brain.Results:Compared to 2DCC and CVX-CS algorithms, L1H-CS achieved faster data acquisition time and considerable improvement in SRUS image quality.Conclusions and Significance:These results demonstrate that the L1H-CS based SRUS imaging technique has the potential to examine microvasculature with reduced acquisition and reconstruction time to acquire enhanced SRUS image quality, which may be necessary to translate it into clinics.

Hybrid vibro-acoustic active control method for vehicle interior sound quality under high-speed

For the problem of active noise control (ANC) and active vibration control (AVC) methods, only noise and vibration can be controlled separately. Active sound quality control (ASQC) method and AVC method are combined to carry out an in-depth study on the active control method of vehicle interior sound quality, using the vibration-sound transfer function and considering the requirements of sound quality. Combined with the adaptive noise equalizer (ANE) algorithm, a sound retention factor was introduced on the basis of the hybrid vibro-acoustic filter-u and filter-x least mean square (HVA-FUXLMS) algorithm, a hybrid vibro-acoustic adaptive noise equalizer (HVA-ANE) algorithm was proposed to control the sound quality. Based on the filter-error least mean square algorithm (FELMS) algorithm, a hybrid vibro-acoustic empirical-mode-decomposition frequency-domain block filter-error least mean square (HVA-EMDFELMS) algorithm for vehicle interior sound quality was proposed. Vibration and noise at high speeds are collected and analyzed for sound quality levels. This article used HVA-ANE and HVA-EMDFELMS algorithms to perform ASQC simulation experiments. The results showed that the noise loudness was greatly reduced while the noise and vibration control was taken into account by the HVA-ANE algorithm and HVA-EMDFELMS algorithm. Hybrid vibro-acoustic active control method for vehicle interior sound quality can effectively improve the sound quality of vehicle and can be applied to the active control of vehicle noise and related engineering noise.

An efficient narrowband active sound profiling system with online secondary path modeling

Active noise equalization or active sound profiling techniques for sound quality enhancement tend to balance the sound pressure levels (SPLs) of certain frequency points or frequency bands of target noise to meet human perception requirements rather than simply minimizing the SPLs like active noise control (ANC) technique. Therefore, when the secondary path is time-varying, online secondary path modeling (OSPM) appears particularly important in the active sound quality enhancement systems. This paper presents a novel parallel-structure narrowband active sound profiling (NASP) system with OSPM. In the system, the OSPM subsystem uses the control signals to estimate low-order local secondary path models at the controlled frequencies instead of the usual high-order global model. This way may ensure the convergence speed and accuracy of modeling. Meanwhile, the main sound profiling subsystem employs the estimated local secondary path models to profile the targeted multi-tonal narrowband noise based on the internal model FXLMS algorithm. By using bandpass filter banks, each tonal component may be tuned relatively independently. In addition, the proposed system enjoys good profiling accuracy and stability since no additional random noise is introduced. Several simulations are provided to demonstrate the superiority of the proposed NASP system with OSPM in cancellation mode over the conventional NANC system with OSPM and evaluate the behavior of the proposed system in different time-varying scenarios. Finally, real-time experiments are also conducted to confirm the system’s ability to deal with sudden changes in the secondary path and its sound profiling capability.

КОРРЕКТИРОВКА ПОДАЧИ ТОПЛИВА В СИСТЕМЕ COMMON RAIL ПРИ ДИАГНОСТИРОВАНИИ ДВИГАТЕЛЯ АВТОМОБИЛЯ

Analysis of technical condition of diesels with accumulator Common Rail power supply system shows that the largest share of fuel equipment failures is associated with malfunction of high-pressure fuel injectors. The electronic engine control unit generates commands for biphasic fuel injection from each injector. Due to the wear of the injector elements, there is an uneven fuel supply to the engine cylinders and, as a rule, deterioration of its operation. (Research purpose) The research purpose is in studying the process of adjusting the fuel supply in the Common Rail system when diagnosing the engine of a Ford Transit vehicle. (Materials and methods) The most relevant method of commissioning Common Rail fuel system injectors are various service procedures, such as the Low Injection Training procedure. Authors used a scanner and appropriate software to estimate total fuel delivery at idle mode. Authors performed the study on a 2.4 liter Duratorq diesel engine. (Results and discussion) The article presents the engine parameters before and after adjustment (Small Injection Procedure). Before adjustment, two cylinders of the engine received more fuel than the other cylinders. It manifests in an increase in crankshaft speed. After the adjustment, the fuel supply to the cylinders was equalized, resulting in an equalization of crankshaft RPM, reduced vibration and noise. (Conclusions) The study showed that fuel adjustment and Low Injection Training should be a must for engine diagnostics. Correction is effective if the value of injection discrepancy is no more than 5 mg/stroke.