Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication technology.Unlike other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental platform.Based on such a platform,we first construct a real signal dataset with ten modulation methods.Then,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature classification.We also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated signals.Finally,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other algorithms.It also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

Lensless complex amplitude demodulation based on deep learning in holographic data storage

To increase the storage capacity in holographic data storage(HDS),the information to be stored is encoded into a complex amplitude.Fast and accurate retrieval of amplitude and phase from the reconstructed beam is necessary during data readout in HDS.In this study,we proposed a complex amplitude demodulation method based on deep learning from a single-shot diffraction intensity image and verified it by a non-interferometric lensless experiment demodulating four-level amplitude and four-level phase.By analyzing the correlation between the diffraction intensity features and the amplitude and phase encoding data pages,the inverse problem was decomposed into two backward operators denoted by two convolutional neural networks(CNNs)to demodulate amplitude and phase respectively.The experimental system is simple,stable,and robust,and it only needs a single diffraction image to realize the direct demodulation of both amplitude and phase.To our investigation,this is the first time in HDS that multilevel complex amplitude demodulation is achieved experimentally from one diffraction intensity image without iterations.

Demodulation Based on Harmonic Wavelet and Its Application into Rotary Machinery Fault Diagnosis

The harmonic wavelet transform（HWT） and its fast realization based on fast Fourier transform（FFT） are introduced. Its ability to maintain the same amplitude-frequency feature is revealed. A new method to construct the time-frequency（TF） spectrum of HWT is proposed, which makes the HWT TF spectrum able to correctly reflect the time-frequency-amplitude distribution of the signal. A new way to calculate the HWT coefficients is proposed. By zero padding the data taken out, the non-decimated coefficients of HWT are obtained. Theoretical analysis shows that the modulus of the coefficients obtained by the new calculation way and living at a certain scale are the envelope of the component in the corresponding frequency band. By taking the cross section of the new TF spectrum, the demodulation for the component at a certain frequency band can be realized. A comparison with the Hilbert demodulation combined with band-pass filtering is done, which indicates for multi-components, the method proposed here is more suitable since it realizes ideal band-pass filtering and avoids pass band selecting. In the end, it is applied to bearing and gearbox fault diagnosis, and the results reflect that it can effectively extract the fault features in the signal.

Generalized Demodulation Transform for Bearing Fault Diagnosis Under Nonstationary Conditions and Gear Noise Interferences

It is a challenging issue to detect bearing fault under nonstationary conditions and gear noise interferences. Meanwhile, the application of the traditional methods is limited by their deficiencies in the aspect of computational accuracy and e ciency, or dependence on the tachometer. Hence, a new fault diagnosis strategy is proposed to remove gear interferences and spectrum smearing phenomenon without the tachometer and angular resampling technique. In this method, the instantaneous dominant meshing multiple(IDMM) is firstly extracted from the time-frequency representation(TFR) of the raw signal, which can be used to calculate the phase functions(PF) and the frequency points(FP). Next, the resonance frequency band excited by the faulty bearing is obtained by the band-pass filter. Furthermore, based on the PFs, the generalized demodulation transform(GDT) is applied to the envelope of the filtered signal. Finally, the target bearing is diagnosed by matching the peaks in the spectra of demodulated signals with the theoretical FPs. The analysis results of simulated and experimental signal demonstrate that the proposed method is an e ective and reliable tool for bearing fault diagnosis without the tachometer and the angular resampling.

Research and test of the adaptive quadrature demodulation technology for silicon micro-machined gyroscope

A program of adaptive quadrature demodulation is proposed to supply the gaps in the traditional analog detection technology of a silicon micro-machined gyroscope (SMG). This program is suitable for digital phase locked loop (DPLL) drive technology that proposed in other papers. In addition the program adopts an adaptive filtering algorithm, which selects the in-phase and quadrature components that are outputs of the DPLL of the SMG's drive mode as reference signals to update the amplitude of the in-phase and quadrature components of the input signal by iteratively. An objective of the program is to minimize the mean square error of the accurate amplitudes and the estimated amplitudes of SMG's detection mode. The simulation and test results prove the feasibility of the program that lays the foundation for the further improvement of the SMG's system performance and the implementation of the SMG system's self-calibration and self-demarcation in future.

Demodulation of acoustic telemetry binary phase shift keying signal based on high-order Duffing system

In order to grasp the downhole situation immediately, logging while drilling(LWD) technology is adopted. One of the LWD technologies, called acoustic telemetry, can be successfully applied to modern drilling. It is critical for acoustic telemetry technology that the signal is successfully transmitted to the ground. In this paper, binary phase shift keying(BPSK) is used to modulate carrier waves for the transmission and a new BPSK demodulation scheme based on Duffing chaos is investigated. Firstly, a high-order system is given in order to enhance the signal detection capability and it is realized through building a virtual circuit using an electronic workbench(EWB). Secondly, a new BPSK demodulation scheme is proposed based on the intermittent chaos phenomena of the new Duffing system. Finally, a system variable crossing zero-point equidistance method is proposed to obtain the phase difference between the system and the BPSK signal. Then it is determined that the digital signal transmitted from the bottom of the well is ‘0’ or ‘1’. The simulation results show that the demodulation method is feasible.

Amplitude and Phase Analysis Based on Signed Demodulation for AM-FM Signal

This paper proposes a new amplitude and phase demodulation scheme different from the traditional method for AM-FM signals. The traditional amplitude demodulation assumes that the amplitude should be non-negative, and the phase is obtained under the case of non-negative amplitude, which approximates the true amplitude and phase but distorts the true amplitude and phase in some cases. In this paper we assume that the amplitude is signed (zero, positive or negative), and the phase is obtained under the case of signed amplitude by optimization, as is called signed demodulation. The main merit of the signed demodulation lies in the revelation of senseful physi- cal meaning on phase and frequency. Experiments on the real-world data show the efficiency of the method.

New cooperative frequency domain differential modulation and demodulation

An innovative method of cooperative frequency domain differential modulation and demodulation is presented.This method applies the prior knowledge of channel propagation to selecting the variable differential length and carrying out frequency domain modulation.This strategy optimizes the design of system parameters to effectively improve the anti-interference ability of the differential system in time-varied multipath channel circumstance without making the execution more complicating.The simulations and comparisons demonstrate the proposed method is effective,and the results show that it is especially suitable for the fading channel with strong propagation and fast time-variation.

Design of Demodulation System of Interferometric Sensor Based on Labview

For the modified demodulation arithmetic of 3×3 coupler, the processing software built on the basis of Labview is able to demodulate asymmetric 3×3 coupler signal and do further spectrum analysis. It shows that the measured frequency ranges from 10 Hz to 1 000 Hz and phase range is covered by -10 rad^10 rad. The phase sensitivity is 0.5 V/rad. This system is proved to show high resolution and wide dynamic range.

Demodulation System for Fiber Bragg Grating Sensors Using Digital Filtering Technique

A discrimination measurement method and demodulation technique for fiber Bragg grating (FBG) sensors were presented using digital filtering technique. The system can control a tunable fiber Fabry-Perot filter with sawtooth wave voltage generated by digital clock to interrogate FBG sensors. Using the analogue digital converter (ADC), the reflected FBG signals were sampled with synchronous digital clock. With the aid of digital matched filtering technique, the sampled FBG signals were processed to obtain the maximum signal-to-noise ratio (SNR) and the Bragg wavelength shift from the FBG signals was recovered. The results demonstrate that this system has a scanning range of 1 520 nm-1 575 nm,and the wavelength detection accuracy is less than 2 pm with 1.5 Hz scanning frequency.

Robust Non-Coherent Demodulation Scheme for Bluetooth Voice Transmission Using Linear, Extended, and Unscented Kalman Filtering

This paper presents a novel and cost effective method to be used in the optimization of the Gaussian Frequency Shift Keying (GFSK) at the receiver of the Bluetooth communication system. The proposed method enhances the performance of the noncoherent demodulation schemes by improving the Bit Error Rate (BER) and Frame Error Rate (FER) outcomes. Linear, Extended, and Unscented Kalman Filters are utilized in this technique. A simulation model, using Simulink, has been created to simulate the Bluetooth voice transmission system with the integrated filters. Results have shown improvements in the BER and FER, and that the Unscented Kalman Filters (UKF) have shown superior performance in comparison to the linear Kalman Filter (KF) and the Extended Kalman Filter (EKF). To the best of our knowledge, this research is the first to propose the usage of the UKF in the optimization of the Bluetooth System receivers in the presence of additive white Gaussian noise (AWGN), as well as interferences.

A Fast π/4-DQPSK Demodulation Arithmetic and Realization

The modulated signals of π /4-DQPSK can be demodulated with the differenced method, and the technology has been used in the communication. The traditional demodulated method needs a lot of calculation. In this paper, a new method based on fast arithmetic digital demodulation of DQPSK is presented. The new method only uses the sign of the modulated signal instead of digital signal through the A/D in the traditional method. With the new method, the system has higher speed, and can save some hardware in the FPGA. An experiment of the new method with the DQPSK is given in this paper.

Research on the Comprehensive Demodulation of Gear Tooth Crack Early Fault

The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre- sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy to the gear mesh signal and the background noise.This paper presents a new comprehensive demodulation method which combined with amplitude envelop demodulation and phase demodulation to extract gear crack early fault.A mathematical model of gear vibration signal contain crack fault is put forward.Simulation results based on this model show that the new comprehensive demodulation method is more effective in finding fault and judging fault level then conventional single amplitude demodulation at present.

Phase-locked all-optical differential polarization demodulation

A novel scheme of differential polarization demodulation is presented and demonstrated based on a polarized asym- metrical Mach-Zehnder interferometer configuration with polarization control. To enhance the stability of the demodulator, a phase-lock device is designed, and it is composed of a symmetric 3 × 3 coupler and a feedback circuit. For further estab- lishing a differential polarization-shift keying （DPolSK） transmission system, we successfully carry out the demodulation experiments on 10-Gb/s DPolSK optical signals for the first time. Due to the all-optical structure with phase-lock, our scheme is available to realize the DPolSK optical communication in practical optical fiber systems.

Rapid extraction of the phase shift of the cold-atom interferometer via phase demodulation

Generally, the phase of the cold-atom interferometer is extracted from the atomic interference fringe, which can be obtained by scanning the chirp rate of the Raman lasers at a given interrogation time T. If mapping the phase shift for each T with a series of measurements, the extraction time is limited by the protocol of each T measurement, and therefore increases dramatically when doing fine mapping with a small step of T. Here we present a new method for rapid extraction of the phase shift via phase demodulation. By using this method, the systematic shifts can be mapped though the whole interference area. This method enables quick diagnostics of the potential cause of the phase shift in specific time. We demonstrate experimentally that this method is effective for the evaluation of the systematic errors of the cold atomic gravimeter. The systematic phase error induced by the quadratic Zeeman effect in the free-falling region is extracted by this method. The measured results correspond well with the theoretic prediction and also agree with the results obtained by the fringe fitting method for each T.

Comparison between Cyclic Statistics and Envelope Demodulation

In this paper, demodulation performance of first-order cyclic statistics and second-order cyclic statistics for amplitude modulation signals is introduced. By theoretical research, it is proved that cyclic mean does not possess demodulation performance for amplitude modulation signals, but cyclic autocorrelation function can extract frequency components from amplitude modulation signals. Based on the above, both cyclic autocorrelation function and envelope demodulation based on Hilbert transform are compared. The results show that the two kinds of analysis methods have similar performance for demodulation, in the mean time it is pointed out that they also possess essential distinction, and cyclic autocorrelation function is better to demodulate amplitude modulation signals. Key words cyclic statistics - demodulation - feature extraction Project supported by the National Natural Science Foundation of China(Grant No. 50175068)

Improving the Angular Resolution of Coded-Mask Telescopes by Direct Demodulation

We develop a new procedure to improve the angular resolution of coded-mask telescopes by the Direct Demodulation Method （DDM）. DDM has been applied to both real and simulated data of INTEGRAL/IBIS. The angular resolution of IBIS/ISGRI has been improved from about 13＇ to 2＇.

Automatic Sleep Spindle Detection with EEG Based on Complex Demodulation Method and Decision Tree Model

Sleep spindle is the characteristic waveform of electroencephalogram (EEG) which is important for clinical diagnosis. In this study, an automatic sleep spindle detection method was developed. The EEG signals were recorded based on the standard polysomnogram (PSG) measurement. A preprocessing procedure is introduced to exclude the unnecessary data segments and normalized the necessary data segments. Complex demodulation method is adopted to detect the candidate sleep spindle waveforms and calculate the features. The sleep spindles are recognized based on a decision tree model. Finally, the detected sleep spindles were utilized to amend the sleep stage recognition results. The sleep EEG data from 3 patients with sleep disorders were analyzed. The obtained results showed that the detected sleep spindles in EEG signal improved the accuracy of sleep stage recognition.

Application of the Spectrum Peak Positioning Technology Based on BP Neural Network in Demodulation of Cavity Length of EFPI Fiber Optical Sensor

An Extrinsic Fabry-Perot Interferometric (EFPI) fiber optical sensor system is an online testing system for the gas density. The system achieves the measurement of gas density information mainly by demodulating the cavity length of EF- PI fiber optical sensor. There are many ways to achieve the demodulation of the cavity length. For shortcomings of the big intensity demodulation error and complex structure of phase demodulation, this paper proposes that BP neural net-work is used to locate the special peak points in normalized interference spectrum and combining the advantages of the unimodal and bimodal measurement achieves the demodulation of the cavity length. Through online simulation and actual measurement, the results show that the peak positioning technology based on BP neural network can not only achieve high-precision demodulation of the cavity length, but also achieve an absolute measurement of cavity length in large dynamic range.