Demodulation Scheme Research Articles

An Improved Pgc Demodulation Scheme Based Efa and Dual Cosine Laser Frequency Modulation

An Improved Pgc Demodulation Scheme Based Efa and Dual Cosine Laser Frequency Modulation

Differential Data-Aided Beam Training for RIS-Empowered Multi-Antenna Communications

The Reconfigurable Intelligent Surface (RIS) constitutes one of the prominent technologies for the next generation of wireless communications. It is envisioned to enhance the signal coverage in cases when the direct link of the communication is weak. Recently, beam training based on codebook selection is proposed to obtain the optimized phase configuration of the RIS. After that, the data is transmitted and received by using the classical coherent demodulation scheme (CDS). This training approach is able to avoid the large overhead required by the channel sounding process, and it also circumvents complex optimization problems. However, the beam training still requires the transmission of some reference signals to test the different phase configurations of the codebook, and the best codeword is chosen according to the measurement of the received energy of the reference signals. Then, the overhead due to the transmission of reference signals reduces the spectral efficiency. In this paper, a zero overhead beam training for RIS is proposed, relying on data transmission and reception based on non-CDS (NCDS). At the BS, the received differential data can also be used for the determination of the best beam for the RIS. Therefore, the efficiency of the system is significantly enhanced since reference signals are fully avoided. After choosing the best codebook, NCDS is still more suitable to transmit information for high mobility scenarios as compared to the classical CDS. Analytical expressions for the Signal-to-Interference and Noise Ratio (SINR) for the non-coherent RIS-empowered system are presented. Moreover, a detailed comparison between the NCDS and CDS in terms of efficiency and complexity is also given. The extensive computer simulation results verify the accuracy of the presented analysis and showcase that the proposed system outperforms the existing solutions.

Integrated Photonic Linear Frequency Discriminator Filter for 5G Phase-Modulated Microwave Photonic Links

The design, fabrication and characterization of a passive linearized field discriminator (FD) filter is presented. The FD filter is designed for silicon-on-insulator (SOI) platform using foundry process design kits (PDKs). Unlike previous FD filters, the design consists of only two MZI stages. The fabrication is performed using the SiEPIC process. Limitations in the knowledge of the exact design of the PDKs, such as waveguide paths and structure are overcome by designing the device with symmetry both in the number of PDK passive components as well as optical path lengths. Excellent agreement with the theoretical results is obtained for the linearity of the transfer function, which extends over a wide bandwidth (80 GHz). The device is tested in a system evaluation simulation for a phase modulated fiber optic link and the results are compared to that of a typical intensity modulation direct detection scheme. Performance of 8 dB in carrier to intermodulation is obtained for modulating frequencies up to 50 GHz using a complementary transfer function with balanced detection demodulation scheme.

Dynamic Phase Extraction in an Ameliorated Distributed Vibration Sensor Using a Highly Stable Homodyne Detection

In this work, a highly stable homodyne phase demodulation scheme is proposed and experimentally demonstrated in an ameliorated distributed vibration sensor (DVS) using dual-wavelength probes and direct-detection receivers. According to the difference between central wavelengths of two probes, the vibration location and the frequency information can be simultaneously demodulated using a reflectometer and an interferometer in direct-detection receivers. An improved phase demodulation scheme is then employed in the interferometer part for the vibration sensing, since it is robust against the high-order harmonic distortion (due to nonlinearity) and the light intensity disturbance, and it is also fully independent of the applied modulation depth. Different patterns of piezoelectric transducer induced vibration are applied to the fiber under test. Experimental results demonstrate that the low harmonic distortion and the accurate phase extraction in the improved phase demodulation scheme make a good agreement with the theoretical analysis. This indicates that the proposed scheme will greatly extend the detected scope of the DVS, in which the quantitative measurement of vibrations is necessary.

Combining IST-Based CFO Compensation and Neural Network-Based Demodulation for Eigenvalue-Modulated Signal

Eigenvalue-based communication technologies using inverse scattering transform (IST) have gained attention as a new transmission strategy in optical fiber communications. In recent years, several studies on artificial neural network (ANN)-based equalization and demodulation schemes for eigenvalue-modulated signal have been conducted to enhance the receiver sensitivity. However, in the case of a presence of a carrier frequency offset (CFO) at receiver, the effects of the CFO on ANN receiver of eigenvalue-modulated signal is yet to be reported. In this study, we numerically and experimentally investigated the generalization performances of eigenvalue domain ANN-based demodulator on CFO. Furthermore, we propose to combine an ANN-based demodulator with a CFO compensation method based on IST and a relation between frequency and eigenvalue shifts. The proposed method, based on an appropriate soliton pulse, achieves a high CFO estimation accuracy of submegahertz order even if the CFO reaches <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 2.5 GHz under the noiseless condition. In the presence of noise and a large CFO of 2.5 GHz, the method attains a CFO estimation accuracy below 60 MHz for OSNR = 10 dB with a low pilot pulse rate, such as 0.064%. We show the simulation results obtained after applying the proposed CFO compensation to the ANN demodulator, which is valid for 2.5 GHz CFO and long-haul transmission over 5000 km. Experiments performed in this study demonstrate successful demodulation of an eigenvalue-modulated signal with OSNR penalty <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&lt; $</tex-math></inline-formula> 1 dB in the presence of CFO within 1 GHz at 2.5 Gb/s.

Two Year Cosmology Large Angular Scale Surveyor (CLASS) Observations: Long Timescale Stability Achieved with a Front-end Variable-delay Polarization Modulator at 40 GHz

Abstract The Cosmology Large Angular Scale Surveyor (CLASS) is a four-telescope array observing the largest angular scales (2≲ ℓ ≲ 200) of the cosmic microwave background (CMB) polarization. These scales encode information about reionization and inflation during the early universe. The instrument stability necessary to observe these angular scales from the ground is achieved through the use of a variable-delay polarization modulator as the first optical element in each of the CLASS telescopes. Here, we develop a demodulation scheme used to extract the polarization timestreams from the CLASS data and apply this method to selected data from the first 2 yr of observations by the 40 GHz CLASS telescope. These timestreams are used to measure the 1/f noise and temperature-to-polarization (T → P) leakage present in the CLASS data. We find a median knee frequency for the pair-differenced demodulated linear polarization of 15.12 mHz and a T → P leakage of &lt;3.8 × 10−4 (95% confidence) across the focal plane. We examine the sources of 1/f noise present in the data and find the component of 1/f due to atmospheric precipitable water vapor (PWV) has an amplitude of 203 ± 12 μ K RJ s for 1 mm of PWV when evaluated at 10 mHz; accounting for ∼17% of the 1/f noise in the central pixels of the focal plane. The low levels of T → P leakage and 1/f noise achieved through the use of a front-end polarization modulator are requirements for observing of the largest angular scales of the CMB polarization by the CLASS telescopes.

A novel ADC-less analog demodulation scheme for NR-STAR-MQAM constellations

Extreme high-speed and high-capacity communications are one of the requirements for technologies to be implemented in the new generations of wireless networks. Moreover, new generations of wireless systems utilize millimeter-wave (mm-wave) frequency bands to have access to the much needed bandwidth. In multi-giga or tera bit-per-second wireless communications, digital signal processing (DSP) encounters great challenges. Implementing mixed-signal devices like analog-to-digital converter (ADC) to achieve high data rates leads to ultra-high power consumption. In this paper, we propose a straightforward and energy-efficient ADC-less analog demodulator for multiple-star M-ary quadrature amplitude modulation (QAM) constellations which are referred to as NR-STAR-MQAM. Our proposed demodulator is based on amplitude threshold estimation and phase detection, and, can extract information bits directly from the received signal. The robustness of the proposed scheme against analog processing errors has been analyzed.

Deep-learning-assisted fiber Bragg grating interrogation by random speckles

Fiber Bragg gratings (FBGs) have been widely employed as a sensor for temperature, vibration, strain, etc. measurements. However, extant methods for FBG interrogation still face challenges in the aspects of sensitivity, measurement speed, and cost. In this Letter, we introduced random speckles as the FBG's reflection spectrum information carrier for demodulation. Instead of the commonly used InGaAs cameras, a quadrant detector (QD) was first utilized to record the speckle patterns in the experiments. Although the speckle images were severely compressed into four channel signals by the QD, the spectral features of the FBGs can still be precisely extracted with the assistance of a deep convolution neural network (CNN). The temperature and vibration experiments were demonstrated with a resolution of 1.2 pm. These results show that the new, to the best of our knowledge, speckle-based demodulation scheme can satisfy the requirements of both high-resolution and high-speed measurements, which should pave a new way for the optical fiber sensors.

Optimization of the phase generated carrier demodulation algorithm based on support vector regression.

The phase generated carrier (PGC) algorithm is often used in the demodulation of interference signals in optical fiber sensors for its high sensitivity, good linearity, and large dynamic range. However, the PGC demodulation method is often distorted by the amplitude of the interference signal and the depth of modulation. In this study, the support vector regression (SVR) method is used to compensate the distortion of the PGC demodulation schemes. Simulation results showed that the SVR algorithm can effectively reduce the nonlinear error of the PGC demodulation system. The fitting accuracy of the SVR algorithm is 97.5% and greater than 90% in noiseless and noise systems, which is better than the back propagation (BP) neural network algorithm. Also, the SVR-based algorithm can better restore the amplitude with smaller mean square error and good correlation. A vibration monitoring system has been built, and experiment results confirm that the performance of the SVR-based algorithm is better than direct PGC demodulation and BP algorithm with the mean square error of 0.0005 and relevance of 0.94.

A Dual-Adaptive Denoising Algorithm for Brillouin Optical Time Domain Analysis Sensor

A dual-adaptive denoising algorithm based on complementary ensemble empirical mode decomposition (CEEMD) and particle swarm optimization (PSO) is proposed to improve the signal-to-noise ratio (SNR) of Brillouin optical time domain analysis (BOTDA) sensor. Here, CEEMD is employed to decompose the measurement signal into a series of intrinsic mode functions (IMFs) adaptively and accurately. The spectrum centroid method is applied to quantify objectively the range of denoising. Then PSO threshold algorithm is dedicatedly designed to search for the optimal/sub-optimal denoising threshold for noised IMFs, which can adjust the threshold size adaptively according to the noise level of input signal. The results show that the SNR can be improved by more than 14 dB and the Brillouin frequency shift (BFS) accuracy is optimized by 1.12 MHz in 22.5 km sensing fiber. This algorithm does not need any condition prediction in the process of denoising, which offers an adaptation and high SNR demodulation scheme for BOTDA sensor with only modifying the software.

Intelligent Matching of the Control Voltage of Delay Line Interferometers for Differential Phase Shift Keying-Modulated Optical Signals

In optical communications, differential phase shift keying (DPSK) provides a desired modulation format that offers high tolerance to nonlinear effects in high-speed transmissions. A DPSK demodulator converts the phase-coded signal into an intensity-coded signal at receivers. One demodulation scheme is called balanced detection and is based on a tunable delay line interferometer (DLI). Demodulation performances are determined by the phase delay generated by the DLI, while the phase delay is controlled by a tunable driving voltage on the DLI device. However, a problem in the dynamic adjustment of the control voltage prevents the application of DPSK demodulators. The receivers need to scan the whole control voltage range of the DLI and find the control voltage that maximizes the demodulation performance, but the scan-based method needs to undergo a very long searching time. In our work, we found that the relation between DLI control voltages and demodulation performance can be predicted rapidly by a feedforward neural network (FNN). In this paper, we propose a new method to quickly locate the best DLI control voltage based on an FNN. We also verify the proposed method in simulations and telecommunication systems, and the results show that the proposed method can significantly improve the efficiency of resolving the best demodulation voltages.

PAM4 rolling-shutter demodulation using a pixel-per-symbol labeling neural network for optical camera communications.

The typical optical camera communication (OCC) modulation scheme is based on binary intensity modulation. To increase the transmission data rate, multi-level modulation format is highly desirable. In this work, we bring forward and demonstrate a rolling shutter 4-level pulse amplitude modulation (PAM4) demodulation scheme for OCC systems using pixel-per-symbol labeling neural network (PPSL-NN) for the first time up to the authors' knowledge. A bit-rate distance product of 28.8 kbit/s • m per color is achieved. The proposed scheme is to calculate and re-sample the pixel-per-symbol (PPS) to make sure the same number of pixels in each PAM4 symbol is corresponding to a label for the neural network. Experiment results reveal that the proposed scheme can efficiently demodulate high speed PAM4 signal in the rolling shutter OCC pattern.

On the modeling of amplitude-sensitive electron spin resonance (ESR) detection using voltage-controlled oscillator (VCO)-based ESR-on-a-chip detectors.

In this paper, we present an in-depth analysis of a voltage-controlled oscillator (VCO)-based sensing method for electron spin resonance (ESR) spectroscopy, which greatly simplifies the experimental setup compared to conventional detection schemes. In contrast to our previous oscillator-based ESR detectors, where the ESR signal was encoded in the oscillation frequency, in the amplitude-sensitive method, the ESR signal is sensed as a change of the oscillation amplitude of the VCO. Therefore, using VCO architecture with a built-in amplitude demodulation scheme, the experimental setup reduces to a single permanent magnet in combination with a few inexpensive electronic components. We present a theoretical analysis of the achievable limit of detection, which uses perturbation-theory-based VCO modeling for the signal and applies a stochastic averaging approach to obtain a closed-form expression for the noise floor. Additionally, the paper also introduces a numerical model suitable for simulating oscillator-based ESR experiments in a conventional circuit simulator environment. This model can be used to optimize sensor performance early on in the design phase. Finally, all presented models are verified against measured results from a prototype VCO operating at 14 inside a 0.5 magnetic field.

Self-Synchronized DS/SS With High Spread Factors for Robust Millimeter-Wave Datalinks

This paper presents direct sequence spread spectrum (DS/SS) datalinks operating at 92-100 GHz with spreading factors up to 100K. Unlike traditional DS/SS datalinks which rely on preamble and cyclic dispreading for synchronization, the reported datalink uses a self-synchronous demodulation scheme, avoiding the large hardware complexity associated with exceptionally large spreading factors, and avoiding the difficulties of synchronizing the long de-spreading codes that are applicable to mm-wave systems. A demonstration link chipset is presented operating at 92-100 GHz with a spreading factor of 104K and a spread bandwidth of 6.0 GHz (baseband bandwidth of 56Kb/s) while consuming a total of 425mW.

An improved phase generated carrier demodulation scheme for sinusoidal phase-modulating interferometer to detect air-solid interface acoustic waves

When acoustic waves reach an air–solid interface, surface acoustic waves will be generated, and such waves may carry important acoustic information. In order to detect acoustic waves at air–solid interface, a non-contact detection method based on a partial-fiber sinusoidal phase-modulating interferometer (SPMI) is proposed in this paper. An improved phase generated carrier (PGC) demodulation scheme is also proposed to eliminate demodulation error caused by changes of interference signal parameters such as interference signal visibility, phase modulation depth and carrier phase delay. In our research, the improved PGC demodulation algorithm is first used to accurately calculate phase modulation depth and carrier phase delay, and then the in-phase and quadrature components of an interference signal are pre-normalized. Next, the visibility coefficient of the interference signal at each moment is derived by self-multiplying. Finally, the in-phase and quadrature components are completely normalized. The accuracy and effectiveness of the sinusoidal phase-modulating interferometer method and the improved PGC demodulation algorithm for detecting acoustic waves at air–solid interface are proven by numerical simulations and experiments. The air–solid interface acoustic waves excited by various acoustic sources are detected in experiments. The experiment results show that the detectable frequency range of the system is 100 Hz-3 kHz, the minimum detectable amplitude is 0.045 rad/√Hz, and the average signal-to-noise-and-distortion ratio (SINAD) is 28.98 dB.

A Demodulation Scheme Based on Measuring Interference Fringe Visibility With a Highly Birefringent Fiber Based Michelson Interferometer

We propose a novel demodulation scheme based on measuring interference fringe visibility and demonstrate it using a typical Michelson interferometer (MI) configuration. The key component to achieve the scheme is a section of highly birefringent fiber (HBF) spliced into the sensing arm to function as the sensing element. The optical path difference (OPD) leads to interference fringes, while the birefringence of the HBF results in a visibility envelop. It is possible to detect measurands associated with birefringence through measuring the visibility, which is attributed to a flexible use of the fundamental principle of interferometry. As one of the potential applications, temperature sensing employing the MI configuration is performed. Moreover, the technique has the advantage of being immune to element instabilities, such as power fluctuation of the light source, phase shift of the reference arm, noise of the photo detector, and wavelength shift of the optical spectrum analyzer (OSA). This work may provide an alternative method to achieve high precision interferometry with low cost.

Reconstruction Compression Correlation Demodulation for Raman Optical Time Domain Reflection

A novel optical mechanism and scheme of Raman optical time domain reflection (ROTDR) for improving achievable spatial resolution is proposed. Herein, the Raman backscattering characteristic of the optical fiber based on the amplified spontaneous emission (ASE) detection is first theoretically analyzed. Then, the propagation model of the ASE Raman anti‐Stokes trace is established. Based on the propagation model, the time domain difference reconstruction is applied to the whole collected Raman anti‐Stokes trace. The reconstructed Raman anti‐Stokes signal and ASE signal, which are first proposed here, show a distinct correlation characteristic. For this characteristic, a higher signal‐to‐noise ratio (SNR) demodulation scheme, named compression correlation demodulation, is used to detect the temperature change along the optical fiber. The positive correlation peak generated by the proposed mechanism produces a multiplied amplification effect through compressing the whole intensity points of Raman anti‐Stokes in the fiber under test (FUT) region. Furthermore, the proposed scheme reduces the crosstalk of the non‐FUT in the demodulation process. Benefiting from this new optical sensing mechanism and scheme, a simulation experiment with 7.5 mm spatial resolution and 0.1 °C temperature sensitivity is demonstrated, and the spatial resolution is independent of sensing distance. These advances greatly facilitate the practicability of ROTDR.

Modified phase-generated carrier demodulation of fiber-optic interferometric ultrasound sensors

We propose and demonstrate a modified phase-generated carrier (PGC) demodulation scheme optimized for detection of ultrasound using interferometric sensors with sinusoidal fringes. The sensor used in demonstration is made from a pair of weak fiber Bragg-gratings at the ends of a coiled fiber that form a low-finesse Fabry-Perot interferometer. The phase of the laser source is modulated using an electro-optic phase modulator to generate the carrier signal and obtain 2 quadrature (the sine and cosine) terms at the first and the second order carrier frequencies. The signal of interest (ultrasound) has much higher frequency than the environmental perturbation but a very small amplitude that causes only small phase shift. Using small-signal approximation, for each of the 2 quadrature terms, we separate the contributions from the environmental perturbations (quasi-DC component) and from the ultrasound (AC component). The AC components that contain the information of the ultrasound signal are then further amplified with a large gain. The signal of interest is constructed by simple algebraic operations on the 2 quasi-DC components and the 2 amplified AC components involving multiplying and summing. This work provides a simple and robust demodulation method with potentially high sensitivity for fiber-optic interferometric ultrasound sensors.

High-precision and wide-wavelength range FBG demodulation method based on spectrum correction and data fusion.

Optical fiber sensing technology plays an important role in the application of the sensing layer of the Internet of Things. The core of this technology is the demodulation of the fiber Bragg grating (FBG) sensing system. Since the FBG sensor utilizes the wavelength change to respond to the measured size, it is of great significance to improve the accuracy of the FBG wavelength demodulation. However, the demodulation performance of the current FBG wavelength demodulation method still has much room for improvement in terms of accuracy and stability. To this end, we propose a composite gas cell demodulation scheme based on spectrum correction and data fusion by using differential photodetectors, fitting extrapolation, data fusion methods, etc. The issue of low demodulation accuracy arising due to noise, temperature drift, spectral distortion, etc., was addressed to improve the demodulation performance of the FBG. In the experiment, four FBGs with different center wavelengths were used to verify their demodulation accuracy in the range of 1510-1590 nm. The maximum repeatability error of the FBG wavelength was measured to be 2.51 pm, and the linearity was as high as 99.9% or more; under the working environment of -20 °C to 60 °C, the maximum full-scale error did not exceed ±1.71 pm, which is improved by 54.3% compared with the traditional method.

A CNN-based FBG demodulation method adopting the GAF-assisted ascending dimension of complicated signal

We introduce the convolutional neural network (CNN) to extract the effective information of some complex signals in the fiber sensing, and verify the feasibility in the specific process of fiber Bragg grating (FBG) demodulation. In the experiments, in order to eliminate the cross interference in the energized coil, classical double grating configuration is adopted to distinguish magnetic field and temperature. At the same time, the introduction of thermal induced chirp (TIC) phenomenon produces more wavelength components to achieve more precise demodulation. The signal received by oscilloscope presents complex waveform, and the traditional analytical solution cannot demodulate it precisely, while the deep learning capabilities of neural networks can be leveraged to solve this problem. The one-dimensional (1D) time-series signal is transformed into a two-dimensional (2D) image by using the Gramian angle field (GAF) method. On this basis, the data are augmented according to the characteristics of signal noise. Five classical neural network structures are used to process the data. The root mean square errors (RMSEs) of the demodulation results can achieve 0.3 °C and 17.1 Gs respectively, which are relatively high precision in terms of intensity demodulation. This method can be extended to demodulate 1D frequency domain signals and wavelength domain signals, rendering a demodulation scheme to process some complex signals in optical fiber sensing effectively.