Demodulation Method Research Articles

Design of High-Precision Parallel AWG Demodulation System.

Here, we present a high-precision demodulation method that supports the arrayed waveguide grating (AWG) system, which includes a 1 × 8 AWG as the primary filter with a 0.5 nm channel spacing and a 1 × 4 AWG as the auxiliary filter with a 1 nm channel spacing. The high precision is achieved through an innovative method of decoupling three channels, involving two adjacent channels of the primary filter and one channel of the secondary auxiliary filter. Simulation results show that the AWGs have a good transmission spectrum with crosstalk below -24.8 dB, non-uniformities below 0.8 dB, insertion loss below -3.7 dB, 3 dB bandwidth of 0.25 nm, and 10 dB bandwidth of 0.43 nm. The interrogation precision can reach 8 pm, with a dynamic range of 0.4 nm, corresponding to a single FBG.

Fringe-to-pulse counting demodulation of a laser interferometer for primary vibration calibration

A high accuracy and real-time amplitude-phase demodulation method based on the pulse counting of optical fringes is proposed for a laser interferometer to realize amplitude and phase measurement of the vibration in primary vibration calibration. The two orthogonally analog signals with high frequency are converted into two digital signals through the comparison module instead of a high-speed data acquisition device. Then one displacement increment during a quarter period of the digital signal can be obtained by the high-frequency clock through comparing the four states of two orthogonally digital signals. The actual output rate of the demodulation data will be decreased by subsample with the vibration frequency. The results of experiment illustrated the deviations were within the limits and the displacement waves were well reconstructed, not only for homodyne interferometer but also for heterodyne interferometer. The proposed method involves less complicated hardware equipment and algorithm, so it is sufficient for real-time and high-precision demodulation of the laser interference signals to realize vibration measurements in primary vibration calibration.

Frequency Shift Keying-Based Long-Range Underwater Communication for Consecutive Channel Estimation and Compensation Using Chirp Waveform Symbol Signals

Currently, the demand for long-range underwater communication (UWC) is increasing. Conventional long-range UWC studies utilize vertical line array (VLA) and equalization techniques such as TRM and DFE to mitigate the long multi-path delay. However, recently developed underwater platforms such as unmanned underwater vehicles (UUVs) utilize a single hydrophone, and it is hard to apply the conventional long-range UWC system to these platforms. This paper proposes frequency shifting-based modulation to overcome the large multi-path delay without any optimization or training symbol. Unlike FSK, the proposed modulation method transmits the data using linear frequency modulation (LFM). The proposed demodulation method estimates the multi-path delay using data-modulated LFM and utilizes the estimated multi-path to compensate for the subsequent data signal. Therefore, the proposed method has better BER performance than FSK, and it is demonstrated through a simulation and ocean experiment with a single hydrophone.

Floquet engineering-based frequency demodulation method for wireless THz short-range communications

This study introduces a novel theoretical framework for detecting and decoding wireless communication signals in the nanoscale range operating at terahertz (THz) frequencies. Initially, we investigate the Floquet states in a dressed 2D semiconductor quantum well and derive an analytical expression to determine its longitudinal conductivity. The results indicate that the longitudinal conductivity of a dressed 2D semiconductor can be tailored to specific requirements by manipulating the frequency of the external dressing field. Furthermore, carefully selecting the intensity and polarization type of the external dressing field enables fine-tuning and optimization of the conductivity. To evaluate the effectiveness of each dressing field configuration, we present a figure of Merit (FoM) assessment that determines the maximum possible change in conductivity within the considered frequency range. The proposed theory introduces a mechanism capable of identifying frequency-modulated communication signals in the THz range and performing frequency demodulation. We comprehensively analyze of the demodulator’s transfer function in the receiver. Consequently, we establish that the transfer function exhibits linear behavior over a specific frequency range, rendering it suitable for frequency demodulation. Finally, we provide a numerical illustration of a frequency demodulation scenario. The breakthrough uncovered in this study opens up possibilities for the development of high-efficiency, lightweight, and cutting-edge chip-scale wireless communication devices, circuits, and components.

A fast wavelength detection method based on OTDR and 1-DDCNN in series overlapping spectra

To improve the rapidity and reliability of the subway tunnel fire monitoring system and realize the monitoring of small fire sources, the method of regional subsection demodulation is used to group several adjacent nearly identical ultra-weak fiber Bragg gratings (UWFBGs) sensors into a group, and the 1-D dilated convolutional neural network (1-DDCNN) is used to demodulate the same group of highly overlapping sensing signals. The well-trained 1-DDCNN model can achieve extremely low signal demodulation error. The experiment shows that the UWFBG demodulation scheme proposed in this paper improves the detection accuracy of the subway tunnel fire monitoring system and shortens the detection time. The root-mean-square error (RMSE) of four highly overlapping peak wavelengths of sensing signals is less than 1.5 pm, and the average demodulation time is less than 30 ms.

An improved initial rotor position estimation method using high-frequency pulsating voltage injection for PMSM

High frequency pulsating voltage injection method is a good candidate for detecting the initial rotor position of permanent magnet synchronous motor. However, traditional methods require a large number of filters, which leads to the deterioration of system stability and dynamic performance. In order to solve these problems, a new signal demodulation method is proposed in this paper. The proposed new method can directly obtain the amplitude of high-frequency current, thus eliminating the use of filters, improving system stability and dynamic performance and saving the work of adjusting filter parameters. In addition, a new magnetic polarity detection method is proposed, which is robust to current measurement noise. Finally, experiments verify the effectiveness of the method.

Radar Sensing of Displacement Motions With High Robustness Against Additive Noise

Doppler radar uses phase demodulation to extract the target displacement motion contained in the phase of the echo signal. The demodulation performance is vulnerable to the additive Gauss noise. Especially when the signal-to-noise ratio (SNR) is extremely low in the scenarios of long-range or subtle displacement motion sensing, it may be impossible to extract the correct phase information. In this article, a phase demodulation method with high robustness against additive noise is proposed for accurate displacement motion reconstruction. Mathematical derivations are performed to analyze the noise effect on phase demodulation, and it shows that the influence of phase noise is much smaller than the additive noise. Based on this finding, the key idea of the proposed method is to transform the additive noise of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I$</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">$Q$</tex-math> </inline-formula> signals into phase noise. The simulation results validate the noise analysis and verify the high robustness of the proposed method against additive noise. Furthermore, experiments were carried out to evaluate the proposed method under different radial distances and displacement amplitudes. The experimental results show that the proposed method enables accurate motion sensing even in low-SNR scenarios. In our experiments, we observe that the relative root-mean-square error (RRMSE) of the reconstructed displacement motion can be greatly reduced with the proposed method.

NOMA security scheme based on constellation camouflage and selective mapping.

This study aims to present a non-orthogonal multiple access (NOMA) security scheme based on constellation camouflage and selective mapping. To improve the security of the system, we use a four-dimensional chaos model to camouflage high-power signals at the transmitter. The constellation diagram of high power is disguised from binary phase-shift keying (BPSK) form to quadrature phase-shift keying (QPSK) form, and after power multiplexing, further camouflaged from 8 points to 16 points. To improve the transmission performance of the designed system as much as possible and not increase the computational complexity, we use the selective mapping method in the process of power multiplexing and use the region decision method for demodulation at the receiving end. The proposed scheme is verified by experiments on a 2-km 7-core optical fiber, and achieves the safety transmission of a power division multiplexing-orthogonal frequency-division multiplexing (PDM-OFDM) signal with a net rate of 97.38 Gb/s without signal damage.The maximum achievable key space of the proposed scheme is 10135. Hence, it is a feasible and secure non-orthogonal multiple access-passive optical network scheme.

Traction Machine State Recognition Method Based on DPCA Algorithm and Convolution Neural Network.

It is important to improve the identification accuracy of the operating status of elevator traction machines. The distribution difference of the time-frequency signals utilized to identify operating circumstances is modest, making it difficult to extract features from the vibration signals of traction machines under various operating conditions, leading to low recognition accuracy. A novel method for identifying the operating status of traction machines based on signal demodulation method and convolutional neural network (CNN) is proposed. The original vibration time-frequency signals are demodulated by the demodulation method based on time-frequency analysis and principal component analysis (DPCA). Firstly, the signal demodulation method based on principal component analysis is used to extract the modulation features of the experimentally measured vibration signals. Then, The CNN is used for feature vector extraction, and the training model is obtained through multiple iterations to achieve automatic recognition of the running state. The experimental results show that the proposed method can effectively extract feature parameters under different states. The diagnostic accuracy is up to 96.94%, which is about 16.61% higher than conventional methods. It provides a feasible solution for identifying the operating status of elevator traction machines.

Reference velocity demodulation method for accelerometer shock testing based on enhanced CEEMD and threshold correction

High-G accelerometers are critical for measuring high shock signals and must be calibrated to improve measurement accuracy. A laser Doppler velocimeter (LDV) is required to calibrate a high-G accelerometer to provide a high-precision reference velocity. The LDV signal must be demodulated to obtain the velocity. However, the phase method is susceptible to noise interference, while the conventional periodic distribution method is challenging to demodulate and severely affected by signal oscillations. We propose a novel periodic distribution method based on enhanced complementary ensemble empirical mode decomposition (CEEMD) and threshold correction to demodulate the LDV signal. First, the LDV signal is processed with CEEMD to obtain multiple intrinsic mode functions (IMFs) and the residual. Next, each IMF is partially zeroed to obtain the noise-reduced LDV signal. Then, the over-threshold peak of the noise-reduced LDV signal is calculated. Finally, the demodulated velocity of the LDV signal is obtained by correcting the noise-reduced LDV signal according to the over-threshold peak point and calculating all the zero points. Simulation and experimental results show that the proposed method outperforms the phase method based on enhanced CEEMD and the periodic distribution method based on enhanced CEEMD and can significantly reduce noise interference. The results show that the proposed method can accurately demodulate the LDV signal to obtain a highly accurate reference velocity, improving the reliability of accelerometer shock testing.

Research on vibration and noise characteristics of scroll compressor with condenser blockage fault based on signal demodulation

The scroll compressor is the core component of the air conditioning system. It is important to accurately evaluate the operation status of the air conditioning system. In this paper, the condenser failure is simulated to explore the impact on the scroll compressor by building an air conditioning system experimental platform. The characteristic frequencies and generation mechanisms of vibration and noise signals are discussed through Time-frequency analysis. The characteristic frequencies in the x, y, and z directions are shaft frequency, second harmonic frequency of stator slot and magnet frequency. Abnormal vibration of the scroll compressor caused by changes in pressure and unbalanced electromagnetic force. The modulation characteristic frequency of the signal and the trend of modulation characteristic changes under fault conditions are discussed through signal demodulation methods. The amplitude modulation of the characteristic frequency is enhanced by the unbalanced electromagnetic force on the shaft rotor. The amplitude of the modulation characteristic frequency of the vibration signal in the three directions and the noise signal increases by 45.0%, 17.3%, 71.4% and 123.0%. This study reveals the mechanism and modulation characteristics of vibration and noise of the scroll compressor, and provides support for its fault diagnosis and status recognition.

Multi-Eigenvalue Demodulation Using Complex Moment-Based Eigensolver and Neural Network

Optical eigenvalues originating in optical solitons are the potential for becoming information carriers not affected by chromatic dispersion and nonlinear effects in optical fibers. They are obtained by attributing the associated eigenvalue equations deduced by solving the nonlinear Schrödinger equation with inverse scattering transform (IST) to the matrix eigenvalue problem, and maintaining constant values regardless of the transmission distance. The eigenvalue communication systems require to solve the eigenvalues in soliton-by-soliton. While effective eigenvalue solution methods have not been studied well in telecommunication systems, one of the most well-known eigenvalue solution methods is the QZ decomposition-based method. However, the QZ algorithm requires a large complexity. To reduce the complexity, a method to demodulate the optical eigenvalues using a complex-moment eigenvalue solver (CME) was investigated. CME is a parallelizable eigenvalue solver that can extract any eigenvalue. This paper proposes a novel optical eigenvalue demodulation method that combines CME and an artificial neural network (ANN) based on employing an on-off encoded discrete eigenvalue modulation scheme. The ANN is sensitive to the input order of the units; therefore, the eigenvalues must be sorted. A lightweight sorting algorithm is hence required. In addition to the proposed scheme, this study proposes partial sorting using CME and ANN. Here, 2000 km fiber-transmission experiments for an on-off-encoded four-discrete- eigenvalue were conducted. The experimental results indicated that the proposed demodulation method obtained bit error rate (BER) characteristics comparable to conventional methods by devising an extraction range of eigenvalues in CME.

Digital phase shift based simulated coherence phase demodulation technology for [formula omitted]-OTDR

In this paper, we propose a digital phase demodulation scheme for phase-sensitive optical time-domain reflectometer (Φ-OTDR) systems based on simulated coherence for digital phase shift, in which three-path signals with a phase interval of 120° can be obtained by employing digital simulated orthogonal coherence for phase shift instead of using a hardware 3×3 coupler and three detectors, while the high-frequency component can be eliminated through cross differential between simulated coherence signals. On this basis, the phase variation of Rayleigh backscattering (RBS) light can be analyzed by differential cross multiplication (DCM). The performance of the proposed scheme is evaluated through experiments by detecting a series of vibration signals with various sensing distances, vibration frequencies, and waveforms. The experimental results demonstrate that the phase variation caused by external vibration can be effectively reconstructed and a strain resolution of 0.5 nɛ and the SNR of 51.03 dB can be achieved through the proposed demodulation method, which significantly simplifies the system and effectively suppresses the deviation of phase interval and noise caused by hardware demodulation.

Modulation and demodulation with quadrature square waves as carriers to improve spectrum utilization

Frequency division modulation enables fast and highly accurate detection of multiple signals, but its spectrum utilization is extremely low. Of course, existing methods improve the spectrum utilization by using quadrature signals as carriers, but it requires the carrier generation to be synchronized with the start of the acquisition. This is difficult to achieve when the carrier generation and the signal acquisition are not controlled by the same clock. Therefore, this paper proposes a demodulation method for the case where the carrier signal is a pair of quadrature square wave signals and the start of the carrier is not synchronized with the sampling. The method demodulates two signals modulating a pair of quadrature carriers by calculating the phase of one independent carrier signal. In this paper, three-wavelength multispectral images are acquired, and the demodulation results are compared with those acquired by the time-division method. The results show that there is a high similarity between the two, which proves the effectiveness of the method proposed in this paper, improves spectrum utilization, and is useful for the acquisition of multiplexed signals.

Signal Demodulation Method in the PD-NOMA System Using a Nonlinear Algorithm with Successive Cancellation of Demodulated Components

A method for signal demodulation in a system with power-domain non-orthogonal multiple access is proposed. The method implements the principle of successive cancellation of demodulated components taking into account the variance of the estimation error and using a nonlinear function. The results of simulation of the proposed method in a cellular communication system are presented: the use of the proposed method allows an improvement by 1–3.5 dB compared to known algorithms, depending on the power ratio of signals transmitted by three user terminals.

Signal Demodulation Method in the PD-NOMA System Using a Nonlinear Algorithm with Successive Cancellation of Demodulated Components

Signal Demodulation Method in the PD-NOMA System Using a Nonlinear Algorithm with Successive Cancellation of Demodulated Components

순환형-하다마드 코드로 직교 변조된 위성항법 보강 신호의 FFT 기반 심볼 복조 기법

In this paper, a fast Fourier transform (FFT)-based symbol demodulation method is proposed for a satellite navigation augmentation signal orthogonally modulated using Cyclic-Hadamard code. The proposed method rearranges the code and performs zero-padding interpolation to enable discrete Fourier transform computation by using the radix-2 FFT algorithm. The proposed method was compared with a correlation receiver in terms of symbol demodulation performance and receiver implementation complexity. Simulation results revealed that the proposed method achieves the same symbol error rate as the correlation receiver while reducing the computational complexity required at higher data rates.

Vacuum pressure imaging solution based on fiber-optic Fabry-Pérot interferometer and optical barcode

Slight variations in vacuum can have a huge impact on industrial, medical, and scientific applications. For sub-atmospheric pressure measurements, conventional demodulation methods for fiber-optic sensors based on the wavelength tracking or power interrogation of the single resonant peak encounter difficulties in the direct vacuum level detection, in addition to cost and sensitivity issues which are one of the key obstacles for further applications of sensing probes. Here we demonstrate a total solution based on a fiber-based Fabry-Pérot interferometer (FPI) and an optical barcode based on Fréchet distance. The vacuum sensing fiber tip based on FPI prepared using the fixed-length cutting and fiber-end grinding techniques address the need for low-cost, high-sensitivity sensing for potential applications. Optical barcoding technique provides direct vacuum information by monitoring the overall behavior of the spectral resonance peaks. This work lays the foundation for the development of a low-cost, compact vacuum pressure sensing solution with direct vacuum reading.

A novel modulation-sourced model and a modulation-carrier spectrum-based demodulation method for rotating machinery signal analysis

Rotating machinery (RM) plays an essential role in modern industries. However, the complex internal motion behavior and vibration transmission paths lead to monitored signals characterized by various modulations, mainly amplitude modulation (AM), frequency modulation (FM), and their coupling effects. Although vibration signal models have been widely studied to interpret the vibration characteristics of RM, the generality and modulation properties of existing models remain to be improved. Furthermore, traditional frequency spectrum-based analysis and well-known demodulation methods face challenges in extracting modulation-carrier frequency pairs and the modulation types, thereby failing to thoroughly reveal the vibration characteristics of RM. Toward the above issues, firstly, a general modulation-sourced model is constructed by synthesizing as many AM-FM phenomena as possible to represent the monitored vibration signal of different RM, such as planetary gearboxes (PGs), rolling bearings (RBs), and so on. Secondly, drawing on the merits of the convolutional neural network (CNN), an elastic comb-shaped convolution kernel (ECCK) and a modified activation function called restricted-rectified linear unit (R-ReLU) are innovatively proposed to automatically obtain a modulation-carrier spectrum (MCS) from the frequency spectrum. Theoretical derivation of the MCS is provided to interpret the components in terms of the proposed model. More importantly, considering the inevitable pseudo demodulated components, a MCS-based demodulation strategy, the MCSD, is introduced to reveal the true modulation-carrier frequency pairs and their corresponding modulation types. Simulation studies with different modulation scenarios are analyzed to validate the effectiveness of the proposed method. Finally, experimental studies are conducted and four mainstream demodulation methods are picked for comparison, confirming the proposed method’s effectiveness and outperformance.

Optical Frequency-Domain Reflectometry Based Distributed Temperature Sensing Using Rayleigh Backscattering Enhanced Fiber

An innovative optical frequency-domain reflectometry (OFDR)-based distributed temperature sensing method is proposed that utilizes a Rayleigh backscattering enhanced fiber (RBEF) as the sensing medium. The RBEF features randomly high backscattering points; the analysis of the fiber position shift of these points before and after the temperature change along the fiber is achieved using the sliding cross-correlation method. The fiber position and temperature variation can be accurately demodulated by calibrating the mathematical relationship between the high backscattering point position along the RBEF and the temperature variation. Experimental results reveal a linear relationship between temperature variation and the total position displacement of high backscattering points. The temperature sensing sensitivity coefficient is 7.814 μm/(m·°C), with an average relative error temperature measurement of −1.12% and positioning error as low as 0.02 m for the temperature-influenced fiber segment. In the proposed demodulation method, the spatial resolution of temperature sensing is determined by the distribution of high backscattering points. The temperature sensing resolution depends on the spatial resolution of the OFDR system and the length of the temperature-influenced fiber. With an OFDR system spatial resolution of 12.5 μm, the temperature sensing resolution reaches 0.418 °C per meter of RBEF under test.