Output SNR Research Articles

Research of the impact of noise reduction methods on the quality of audio signal recovery

The subject of the study is the analysis of various filtering algorithms for the quality of the resulting audio files. The importance of audio line filtering has grown significantly in recent years due to its key role in a variety of applications such as speech reduction and artificial intelligence. Taking into account the growing demand for solving problems related to speech recognition, the processing of audio series becomes important for determining the accuracy and efficiency of the obtained solution.The purpose of the work is to study the impact of noise suppression methods on the quality of restoration of an audio signal, which was alternately noisy with one of five types of noise - white, pink, brown, impulse, Gaussian with different power. To achieve the goal, the following tasks were solved: an analysis of the types of noise was carried out and analysis of noise reduction and filtering methods. A generalized model of noise reduction and filtering was developed, and an experiment was planned depending on the type and power of noise. Simulation of the experiment was performed by comparing the parameters of the signal-to-noise ratio before and after the experiment and the peak signal-to-noise ratio in the processed file. The following methods are used: spectral subtraction, filtering based on frequency filters and wavelet transformation.The following results were obtained: depending on the selected noises and algorithms, it was possible to achieve the lowest value of the peak signal-to-noise ratio of 21.52db, and the signal-to-noise ratio increased, which allowed further work with these audio files. The practical significance of this work is the increase in the number of available audio files for further work.Conclusions: the analysis of the obtained results showed that filtering based on frequency filters only worsened the output signal, that is, not only noise, but also useful information is filtered. In all runs, the SNR deteriorates to - 18dB. which is worse than no filtering. Algorithms of spectral subtraction and wavelet transformation improved SNR parameters and output audio files noisy with the most powerful noises in the range of 20dB, which can be considered acceptable for further processing. The results highlight the importance of using denoising and filtering for complex audio processing tasks, particularly neural network training tasks.

An overview of UAV communication technologies

Recently, Unmanned Aerial Vehicle (UAV) as a flexible platform has received extensive attention from scholars at home and abroad. Compared with terrestrial communication, UAV has the unique advantages of high flexibility, wide coverage and no influence of terrain. In this paper, two aspects of UAV outage probability and covert communication are discussed and two system models are established, respectively. In the first aspect, the outage probability expression is calculated using the output SNR, and then the relay drone’s best position is solved in order to minimum outage probability. In the second aspect, in the case of the presence of listener and eavesdropper in the system, the detection performance of the listener is discussed, and then the secure concealment rate of the system is analyzed.

Indoor visible light communication denoising system combining iterative variational mode decomposition and multiple frequency shift keying modulation

To reduce noise in indoor visible light communication (IVLC), the Pearson correlation coefficient difference (PCCD), a denoising system combining iterative variational mode decomposition (IVMD) and multiple frequency shift keying modulation (MFSK), is proposed. Compared with VMD, the method can directly determine the optimal number of VMD modes and solve the issue of VMD penalty factor selection to some extent. The simulation results show that, when the input SNRs vary from −15 to −8dB, the proposed method can improve the output SNRs of the 2FSK signal by an average of 15.5 dB and reduce the BER by 55.8%, improve the output SNR of the 4FSK signal by an average of 13 dB, and reduce the BER by 54.4%. The proposed method can also effectively suppress noise interference in real IVLC experiments at a distance of 1 m. In addition, the IVMD-MFSK denoising system can be applied to denoise all frequency-modulated signals with high applicability.

Adaptive pseudo‐spectrum based track‐before‐detect for targets with uncertain existence

AbstractIn the existing velocity filtering based track‐before‐detect (VF‐TBD), target existence is generally assumed to be constant, and multiple successive frames in a sliding window are jointly processed. However, when the target existence changes abruptly in a processing batch, the incorporation of noise‐only frames may corrupt target energy integration. This results in degraded detection and estimation performances with serious decision delays. A pseudo‐spectrum based VF‐TBD is proposed to effectively detect and track targets with existence uncertainty. An adaptive integration strategy is developed to realise effective energy accumulation with only informative frames by matching target appearance and disappearance times in addition to the velocity. The change of target existence can be discovered in time, and the decision delay is reduced. An estimation strategy based on the maximum output SNR is presented to supply accurate estimations of not only target motion parameters (including the position and velocity) but also time parameters (including appearance and disappearance times). The target output envelope, SNR gain and receiver operating characteristic curve of targets with uncertain existence are analysed theoretically. Numerical simulations exhibit the validity of the proposed method.The cover image is based on the Original Article Adaptive pseudo‐spectrum based track‐before‐detect for targets with uncertain existence by Peiyuan Li et al., https://doi.org/10.1049/rsn2.12502.

Noise reduction and QRS detection in ECG signal using EEMD with modified sigmoid thresholding.

Novel noise reduction and QRS detection algorithms in Electrocardiogram (ECG) signal based on Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and the Modified Sigmoid Thresholding Function (MSTF) are proposed in this paper. EMD and EEMD algorithms are used to decompose the noisy ECG signal into series of Intrinsic Mode Functions (IMFs). Then, these IMFs are thresholded by the MSTF for reduction of noises and preservation of QRS complexes. After that, the thresholded IMFs are used to obtain the clean ECG signal. The characteristic points P, Q, R, S and T peaks are detected using peak detection algorithm. The proposed methods are validated through experiments on the MIT-BIH arrhythmia database and Additive White Gaussian Noise (AWGN) is added to the clean ECG signal at different input SNR (SNR in). Standard performance parameters output SNR (SNR out), mean square error (MSE), root mean square error (RMSE), SNR improvement (SNR imp) and percentage root mean square difference (PRD) are employed for evaluation of the efficacy of the proposed methods. The results showed that the proposed methods provide significant quantitative and qualitative improvements in denoising performance, compared with existing state-of-the-art methods such as wavelet denoising, conventional EMD (EMD-Conv), conventional EEMD (EEMD-Conv, Stockwell Transform (ST) and Complete EEMD with Adaptative Noise with hybrid interval thresholding and higher order statistic to select relevant modes (CEEMDAN-HIT). A detail quantitative analysis demonstrate that for abnormal ECG records 207 m and 214 m at input SNR of-2 dB the SNR imp value is 12.22 and 11.58 dB respectively, which indicates that the proposed algorithm can be used as an effective tool for denoising of ECG signals.

Investigation of Accuracy of TOA and SNR of Radio Pulsar Signals for Vehicles Navigation.

It is known that X-ray and gamma-ray pulsars can only be observed by spacecraft because signals from these pulsars are impossible to be detected on the Earth's surface due to their strong absorption by the Earth's atmosphere. The article is devoted to the theoretical aspects regarding the development of an autonomous radio navigation system for transport with a small receiving antenna, using radio signals from pulsars, similar to navigation systems for space navigation. Like GNSS systems (X-ray and radio), they use signals from four suitable pulsars to position the object. These radio pulsars (out of 50) are not uniformly distributed but are grouped in certain directions (at least 6 clusters can be determined). When using small antennas (with an area of up to tens of square meters) for pulsar navigation, the energy of the pulsar signals received within a few minutes is extremely insufficient to obtain the required level of SNR at the output of the receiver to form TOA estimation, ensuring positioning accuracy up to tens of kilometers. This is one of the scientific tasks that is solved in the paper by studying the relationship between the SNR of the receiver output, which depends on the size of the antenna, the type of signal processing, and the magnitude of the TOA accuracy estimate. The second scientific task that is solved in the paper is the adaptation of all the possible approaches and algorithms suggested in the statistical theory of radars in the suggested signal algorithm for antenna processing and to evaluate the parameters of the TOA and DS pulsar signals, in order to increase the SNR ratio at the receiver output, while preserving the dimensions of the antenna. In this paper, the functional structure of signal processing in a pulsar transport navigation system is proposed, and the choice of the observed second and millisecond pulsars for obtaining a more accurate TOA estimate is discussed. The proposed estimates of positioning accuracy (TOA only, no phase) in an autonomous pulsar vehicle navigation system would only be suitable for the navigation of large vehicles (sea, air, or land) that do not require accurate navigation at sea, air, or desert. Large-sized antennas with an area of tens of square meters to hundreds of square meters can be installed in such vehicles.

Secrecy Performance Analysis for MIMO-DF Relay Systems With MRT/MRC and TZF/MRC Schemes

Transmit beamforming is a diversity technique in multiple-input multiple-output (MIMO) systems. It improves the diversity order and enhances the information security of the MIMO systems. In this paper, we mathematically analyze the secure performance of a MIMO decode-and-forward (DF) relay system under the presence of an eavesdropper and with the imperfect channel state information (CSI) of the eavesdropping channel. To enhance the secrecy performance, we employ multiple antennas at all legitimate nodes and utilize two linear beamforming schemes, i.e., maximal ratio transmission (MRT) and transmission zero-forcing (TZF), at the transmitter and maximal ratio combining (MRC) scheme at the receiver. The probability density function (PDF) of the output SNR for different numbers of antennas at the transmitter and receiver is plotted and discussed. After that, we apply this PDF to derive the closed-form expressions of the secrecy outage probability (SOP) and ergodic secrecy capacity (ESC) of the considered MIMO-DF relay system over Rayleigh fading channels for MRT/MRC and TZF/MRC schemes. In addition, based on the obtained analysis results, we provide the location of the relay that minimizes the system SOPs. All the analysis results are validated by Monte-Carlo simulations. The results show that the TZF/MRC scheme provides better SOP and ESC than the MRT/MRC scheme. Moreover, the number of antennas at the legitimate nodes and the location of the eavesdropper significantly impact the secrecy performance.

Sinusoidal-assisted synchrosqueezing transform: Algorithms and biomedical applications

Intermittent oscillation signals (IOSs) exist widely in biomedical systems. They are always contaminated by various randomnesses like noise and artifacts. Compared with traditional time–frequency analysis (TFA) methods, adaptive TFA methods show significant advantages in separating IOSs. However, these methods are implemented by assuming that the input signal is in a weakly noisy environment and have narrow-band limitation for extracting IOSs. Besides, it is difficult for these methods to alleviate the noise in the gap between time where IOSs happen. Therefore, in this paper, a new method called the sinusoidal-assisted synchrosqueezing transform (SASST) is proposed for separating IOSs in strongly noisy environments. The SASST method locates the IOSs with the aid of a sinusoidal signal. Such a sinusoidal signal fills the energy blank in the gap between time where IOSs happen. This enables the ridge detection approach, which is the necessary tool for mode retrieval of SST-based methods, to focus on the assisted sinusoidal signal rather than noise. Thus, the background noise in the gap is suppressed. Moreover, this sinusoidal-assisted framework can be introduced into any SST-based TFA method. Depending on the characteristics of different biomedical signals, different SST-based methods are chosen to achieve better separation. As a result, SASST is capable of extracting both narrow- and wide-band IOSs in strongly noisy environments. The effectiveness and advantages of the proposed algorithm are verified by both numerical simulations and real-world cases. Even in a strongly noisy environment of −10 dB, SASST achieves output SNR of 12.66 dB and 10.53 dB in narrow- and wide-band simulation, respectively.

Controlled Symmetry with Woods-Saxon Stochastic Resonance Enabled Weak Fault Detection.

Weak fault detection with stochastic resonance (SR) is distinct from conventional approaches in that it is a nonlinear optimal signal processing to transfer noise into the signal, resulting in a higher output SNR. Owing to this special characteristic of SR, this study develops a controlled symmetry with Woods-Saxon stochastic resonance (CSwWSSR) model based on the Woods-Saxon stochastic resonance (WSSR), where each parameter of the model may be modified to vary the potential structure. Then, the potential structure of the model is investigated in this paper, along with the mathematical analysis and experimental comparison to clarify the effect of each parameter on it. The CSwWSSR is a tri-stable stochastic resonance, but differs from others in that each of its three potential wells is controlled by different parameters. Moreover, the particle swarm optimization (PSO), which can quickly find the ideal parameter matching, is introduced to attain the optimal parameters of the CSwWSSR model. Fault diagnosis of simulation signals and bearings was carried out to confirm the viability of the proposed CSwWSSR model, and the results revealed that the CSwWSSR model is superior to its constituent models.

Successive Interference Cancellation for Orthogonal Chirp Division Multiplexing

In this paper, we propose a communication receivers’ architecture to simplify the Orthogonal Chirp Division Multiplexing (OCDM) channel equalization and to subtract multi-carrier interference followed by a successive interference cancellation (SIC) scheme in order to cancel the remaining interference. The interference introduced by underwater acoustic channel is estimated using a pre-acknowledged pilot symbol sequence, and then the interference can be optimally estimated and subtracted from the received signal. This process is repeated simultaneously for all OCDM carriers until a stationary point or a threshold is reached. Simulation results from Watermark are applied to illustrate the performance of the OCDM scheme with the presented successive interference cancellation algorithm. Results shows that the Bit Error Rate (BER) enhancement can reaches 102 in BCH1 channel. As expected, the combination of OCDM and presented SIC algorithm is shown to increase the output SNR over OCDM alone in multi-path shall water acoustic channel.

Tunable performance of indium tin oxide-zinc oxide as Q-switcher

This work successfully demonstrated the tunable performance of a Q-switched pulse erbium-doped fiber laser (QPEDFL) using Indium Tin Oxide-Zinc Oxide (ITO-ZnO)-based SA. The ITO-ZnO is a material growth between transparent conducting oxides and transition metal oxides on a glass slide. The mechanical exfoliation technique is applied to serve the ITO-ZnO as SA and inserted in a single-ring cavity design. The QPEDFL in a single ring cavity gives the repetition rate, pulse width, average output power, pulse energy, and SNR of 38.49 kHz, 5.50 µs, 0.47 mW, 12.72 nJ, and 64.20 dB, respectively. Furthermore, the ITO-ZnO as SA provides a tuning range of 30.40 nm. By tuning the TBF, the wavelength changes from 1531.60 nm to 1562.0 nm, causing the pulse repetition rate and pulse width of the QPEDFL to vary from 41.50 kHz to 17.20 kHz, and 4.22 µs to 10.05 µs, respectively. According to the results obtained, it can confidently say the suggested pulse laser has potential in the application of optical communication systems as a light source.

An MMSE graph spectral magnitude estimator for speech signals residing on an undirected multiple graph

The paper uses the K-graphs learning method to construct weighted, connected, undirected multiple graphs, aiming to reveal intrinsic relationships of speech samples in the inter-frame and intra-frame. To benefit from the learned multiple graphs’ property and enhance interpretability, we study the spectral property of speech samples in the joint vertex-frequency domain by using the new graph weight matrix. Moreover, we propose the representation of minimum mean-square error (MMSE) graph spectral magnitude estimator for speech signals residing on undirected multiple graphs. We use the MMSE graph spectral magnitude estimator to improve speech enhancement performance. The numerical simulation results show that the proposed method outperforms the existing methods in graph signal processing (GSP) and the baseline methods for speech enhancement in discrete signal processing (DSP) in terms of PESQ, LLR, output SNR, and STOI results. These results also demonstrate the validity of the learned multiple graphs.

Pseudo-spectrum-based multi-sensor multi-frame detection in mixed coordinates

Multi-sensor track-before-detect (MS-TBD) can greatly enhance the weak target detection ability due to utilizing multi-frame (MF) data from multiple sensors. However, in the existing MS-TBD methods, when the resolutions of the MS are different, the target echoes obtained by the MS are arranged to the measurement space with unified resolution. This process may remove some valuable information of raw sensor data or introduce additional noise, which may lead to inadequate integration of the echo energy and degradation of the output envelope. For the sake of solving the issues mentioned above, a pseudo-spectrum (PS) method in mixed coordinates is investigated for TBD in MS systems. For each sensor, the conversion of each measurement cell's position from sensor coordinates to Cartesian coordinates is carried out and the prediction of that is conducted with an assumed velocity in Cartesian framework. Then the predicted position is converted back to global sensor coordinates, which takes one of the sensors as the origin. A PS is designed around the predicted global polar position and its samples are added to the integration frame for MF accumulation. This avoids additional spatial alignment and facilitates well-maintained target envelope, leading to effective energy integration and the improvement of estimation accuracy. The procedures of coordinate transformation and MF accumulation in multiple sensors are derived and the analysis of theoretical output SNR is provided. The effectiveness and the superiority of the proposed method is demonstrated by several simulations.

Application of microphone arrays to interference cancellation by using null broadening beamforming

Beamforming is an important technology for array systems, the spatial filtering can be achieved by focusing the main beam to the target and null point to the interference. Comparing to the noise suppression method based single-channel, the signal from beamforming output shows lower distortion and higher signal-to-interference plus noise ratio. This study is to investigate the null broadening (bearing, width and depth) control of beamforming, the purpose is to overcome the bearing error between interference and null by producing a broadening null, and to improve the interference signal suppression. Considering the requirements of real-time and broadband in the acoustic system, the fixed beamforming process is chosen and combined with the convex optimization technique. There are several advantages form fixed process that are better robustness due to avoiding the signal self-cancellation from the issue of model mismatch and low-complexity computation contributes to achieving the real-time and broadband spatial filtering in the present process. In the experiment of the chirp signal, the SNR of beamformer output is increased from 2 to 10.5 dB, the correlation coefficient for target is increased from 0.52 to 0.82, and the interference is reduced from 0.54 to 0.07. In the experiment of the broadband voice signal, the SNR of beamformer output is increased from 2 to 6.5 dB, the correlation coefficient for target is increased from 0.37 to 0.68, and the interference is reduced from 0.58 to 0.19. The experimental results verify that the proposed algorithm can effectively controlled the capability of null broadening and have better interference suppression than other algorithms.

Prediction Error Method (PEM)-Based Howling Cancellation in Hearing Aids: Can We Do Better?

This work develops an effective technique acoustic feedback cancellation (AFC) in the digital hearing aid (DHAid) devices. The normalized least mean square (NLMS) algorithm-based AFC method may suffer from a biased convergence. The biased convergence problem is considerably resolved by the prediction error method (PEM)-based AFC (PEM-AFC); however, it may demonstrate a slow convergence. The proposed method’s main structure is based two adaptive filters. The main adaptive AFC filter receives its input from the DHAid receiver signal, while the auxiliary AFC filter is activated by a probe signal. The main idea is to apply a lattice filtering-based pre-processing for decorrelation in the main AFC filter’s update equation. This produces a Newton-like adaptive algorithm with fast convergence. Additionally, the lattice filtering is executed on a sample-by-sample basis, in contrast to the frame-based execution in the traditional PEM-AFC method. As the AFC system converges, the level of the probe signal is decreased to improve the output SNR; however, the low-level input signal slows down auxiliary AFC filter’s convergence. In order to improve the convergence speed, the gradient information from a maximum Versoria-criterion (MVC) is incorporated into the auxiliary AFC filter’s update algorithm. The two adaptive filters’ coefficients are exchanged, to ensure that both adaptive filters converge to a good estimate of the true acoustic feedback path. Simulations show that the proposed method works well for speech/signals and for DHAid devices with different gain settings. Additionally, the proposed method shows robust performance in the event of a sudden change in the acoustic environment.

Rolling Bearing Fault Diagnosis Based on Exact Moment Dynamics for Underdamped Periodic Potential Systems

This research is to build a more general bridge over the model investigation on stochastic resonance (SR) and the laboratory design in rolling bearing faults. To this end, we generalize the derivative matching moment closure method to the underdamped biased periodic potential systems to disclose the non-monotonic evolution of the spectral amplification factor. With the exact moment dynamics available, a two-layer loop algorithm for detecting the incipient bearing faults is then developed. With the outer loop to optimize the output SNR for the best time scale factor and the inner loop to maximize the spectral amplification factor for optimal system parameter, the semi-analytic results are directly related with this laboratory application. The analog and experimental verification based on different datasets show that the proposed method can perform as well as the existing SR method, even under strong noise background. Particularly, the proposed method does not depend on the amplitude of input signal when optimizing parameters, but only on noise intensity and characteristic fault frequency, thus it has higher detection efficiency than the existing simulation based SR methods.

Performance Analysis of ACO/DCO-OFDM Hybrid PLC-VLC Receivers With Blanking Non-Linearity

Blanking non-linearity is broadly used in impulsive noise communication environments due to its efficiency and ease of deployment to mitigate such noise. During the blanking procedure, data samples with impulsive noise are identified and clipped to zero, which removes impulsive noise from the system thereby, improving the system performance. In this regard, this paper investigates the performance of hybrid power line communication-visible light communication (PLC-VLC) systems with blanking nonlinearity. The signal-to-noise (SNR) ratio at the output of the blanking device is deduced using a closed-form analytical expression. The results show that there is good agreement between simulation results and theory if there is a sufficiently large number of orthogonal frequency division multiplexing (OFDM) sub-carriers. In addition, the study also indicates that the blanking method is more effective in curbing impulsive noise in comparison to the clipping technique. According to the threshold optimisation investigations, there exists a worst-case SINR value that minimizes the output SNR at the OFDM receiver after blanking. Furthermore, the findings also revealed that proper blanking threshold selection is essential for obtaining the best performance.

Simultaneous Wireless Information and Power Transfer Over KG Fading Channels

In this paper, we proposed a novel expression for the probability density function (PDF) and the cumulative density function (CDF) of the output SNR for the M-branch Selection Combining (M-SC) receiver over Generalized-K (KG) fading channels. Unlike conventional energy sources, the proposed scheme uses a Power splitter (PS) scheme at the receiver side. The received signal is split into information decoding and energy harvesting receiver with adjustable power levels. The expressions of our system consider arbitrary channel parameters and diversity branches. We analyze the proposed model and derive the closed-form expression for average SNR and average bit error rate (ABER) to evaluate the system performance. The obtained results are corroborated with the help of Monte-Carlo simulations. The effects of system parameters, such as power splitter ratio, modulation order, and shaping parameters of KGfading channels, are studied. This type of system will benefit reliable data transmission in an energy-limited scenario.

Research on Co-Channel Interference Cancellation for Underwater Acoustic MIMO Communications

Multiple-input–multiple-output (MIMO) communication systems utilize multiple transmitters to send different pieces of information in parallel. This offers a promising way to communicate at a high data rate over bandwidth-limited underwater acoustic channels. However, underwater acoustic MIMO communication not only suffers from serious inter-symbol interference, but also critical co-channel interference (CoI), both of which degrade the communication performance. In this paper, we propose a new framework for underwater acoustic MIMO communications. The proposed framework consists of a CoI-cancellation-based channel estimation method and channel-estimation-based decision feedback equalizer (CE-DFE) with CoI cancellation functionalities for underwater acoustic MIMO communication. We introduce a new channel estimation model that projects the received signal to a specific subspace where the interference is free; therefore, the CoI is cancelled. We also introduce a CE-DFE with CoI cancellation by appending some filters from traditional CE-DFE. In addition, the traditional direct adaptive decision feedback equalization (DA-DFE) method and the proposed method are compared in terms of communication performance and computational complexity. Finally, the sea trial experiment demonstrates the effectiveness and merits of the proposed method. The proposed method achieves a more than 1 dB of output SNR over traditional DA-DFE, and is less sensitive to parameters. The proposed method provides a new approach to the design of robust underwater acoustic MODEM.

Modification over Dithered DPLL to reduce the effect of narrowband channel interference

Digital signal processing based digital phase locked loop (DSP DPLL) are most commonly used for carrier phase tracking in the recent times. Phase locked loop (PLL) behaves in nonlinear fashion at the time of signal acquisition. The linearity is restored in the PLL behavior once acquisition is over and signal tracking is taking place. But the same PLL or DSP-DPLL shows non-linearity both during acquisition and tracking when narrowband channel interference is present in the received signal. In this paper, a single tone signal is introduced as channel interference to study the effect on DPLL and its modified versions. To overcome the effect of channel interference, a single tone dither signal is included in the loop of DPLL. Although an improvement in acquisition and tracking performance is observed, but addition of dither signal contributes to the phase error variance and consequently output noise to increase. Therefore, a further modification is proposed by incorporating an additional phase control in the digital control oscillator (DCO) of the loop to improve the output SNR. The proposed loop is implemented on reconfigurable logic platform using System Generator, a tool from Xilinx used to design real time DSP application. The hardware simulation results demonstrate a comparison among traditional DPLL, dithered DPLL and phase controlled dithered DPLL where the proposed version of the loop outperforms others in terms of acquisition and noise rejection. Keywords DSP Digital Phase Locked Loop, Phase Controlled DPLL, Channel Interference, Dither DPLL, VHDL System Design, Modified DCO