FSK Signals Research Articles

Modeling and Research on Railway Balise Transmission System for Underwater Debris

The balise transmission system (BTS) is essential for train position sensing and safe operation. Transmission loss is a key parameter particularly required for the evaluation of systems. The eddy current loss (ECL), caused by the conductivity of debris, affects the transmission performance of the BTS when the balise is immersed in water. This study proposes an effective modeling for the BTS using S-parameters. Utilizing the electromagnetic coupling analysis in the near-field region, we derived an equivalent circuit with the frequency and conductivity of water taken into consideration. The S21 can be predicted accurately by using the proposed equivalent circuit. For validation, a BTS system was implemented and measured to compare with theoretically calculated results and electromagnetic simulation results in the main lobe zone. The measurement results, simulation, and calculation were in good agreement. Moreover, the modeling was used to predict the I/O characteristics of the balise. The power of the balise uplink FSK signal was measured in the water debris and found to be approximately 0.62 dB less than in air. These findings aligned well with theoretical predictions.

Frequency Modulation Recognition for Radar Signal based on Resnet-LSTM Network

In order to satisfy the modulation recognition requirements for radar signal with large scale changes in pulse-width and bandwidth, the Resnet-LSTM network is proposed in this paper. First, the waveform is preprocessed by self-correlation, and then the I/Q waveform and self-correlation result are as the network input. Secondly, the local characteristics were extracted by Resnet network; and lastly the LSTM network is adopted to extract the serialization representation. The proposed algorithm avoids the flaw of CNN network cannot adapt to variable length, and problem of memory forgetting of the LSTM network for long sequence is reduced. The simulation shows that the modulation recognition accuracy is more than 96.1% over the detection sensitivity for LFM, Parabolic-NLFM, Triangular-NLFM, Sine-NLFM, Sawtooth-NLFM and FSK signals.

Microwave FSK Signal Generation Based on Optoelectronic Oscillator and PolM

Microwave FSK Signal Generation Based on Optoelectronic Oscillator and PolM

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.

A Modulation Recognition System for Underwater Acoustic Communication Signals Based on Higher-Order Cumulants and Deep Learning

Underwater acoustic channels, influenced by time-varying, space-varying, frequency-varying, and multipath effects, pose significant interference challenges to underwater acoustic communication (UWAC) signals, especially in non-cooperative scenarios. The task of modulating and identifying distorted signals faces huge challenges. Although traditional modulation recognition methods can be useful in the radio field, they often prove inadequate in underwater environments. This paper introduces a modulation recognition system for recognizing UWAC signals based on higher-order cumulants and deep learning. The system achieves blind recognition of received UWAC signals even under non-cooperative conditions. Higher-order cumulants are employed due to their excellent noise resistance, enabling the differentiation of OFDM signals from PSK and FSK signals. Additionally, the high-order spectra differences among signals are utilized for the intra-class recognition of PSK and FSK signals. Both simulation and lake test results substantiate the effectiveness of the proposed method.

Non-coherent turbo coded frequency shift keying for reliable covert underwater acoustic communications

This paper presented efficient receiver structure of non-coherent turbo coded FSK signals for maintaining covertness and performance in underwater communication. In aspect to covertness, direct sequence spread spectrum method, which used to hide the transmitted signal by transmitting it at low power and, thus, making it difficult for an unintended listener to detect the signal in the presence of background noise. In aspect to performance improvement in the underwater acoustic environment with multipath and Doppler spreading, non-coherent FSK which is not required phase information, weighted multiband technology, and turbo equalization model with rate of 1/3 were suggested. In order to analyze the performance by applying four bands and spreading chips with 8 and 32, the experiment was conducted on a lake by moving in the range of 300m to 500m. Through the experimental results, we confirmed the performance was improved as increasing number of bands, turbo iterations, and spreading chips. Furthermore, weighted multiband technology which allocates lower weight to inferior bands based on preamble error rates were applied for some failed packets, all packets were decoded successfully. [This research was funded by Agency for Defense Development, South Korea, Grant No. UD200010DD.]

Research on Ultra-Low-Frequency Communication Based on the Rotating Shutter Antenna

This paper proposes a rotating shutter antenna that can directly generate 2FSK signals in the ULF band and it is expected to be used as the transmitter for magnetic induction (MI) underground communication systems. The antenna was modeled using ANSYS Maxwell and the magnetic field distribution was simulated. The results show that the interaction between the high-permeability shutter and the mutual cancellation of magnets decreased the transmitting magnetic moment of the antenna. A prototype antenna was manufactured and the time and frequency properties of the measured Bz field were the same as the simulated results, while the magnitude of the measured signal was larger. The propagation characteristics of the antenna in air–soil–rock were simulated using FEKO and the results show that the signal strength was greater than 1 fT at a depth of 450 m from the antenna whose magnetic moment as 1 Am2. The relationship between different magnetic components and azimuth could be used to enhance the signal strength. The formula of the Bz field was derived using the measured magnitude versus distance and the path loss was also analyzed. Finally, the 2FSK modulation property of the antenna was verified by indoor communication experiments with a code rate of 12.5 bps in the ULF band.

Blind Separation for Wireless Communication Convolutive Mixtures Based on Denoising IVA

In wireless communication systems, signal transmission through a channel can not avoid the influence of noise. When it reaches the receiver, it is accompanied by time delay and attenuation. Therefore, the observed mixture signals at the receiver are convolutional mixed signals with noise contamination. To solve the problem of traditional frequency-domain based convolutive blind signal separation methods have poor separation performance for convolutional mixed signals with noise, this paper propose a denoise-FastIVA method to separate convolutional mixed signals with noise. The basic principle is to use a wavelet transform to denoise the observation signal, reduce the effect of noise on the separation effect of the algorithm, and enhance the robustness of the fast fixed-point independent vector analysis (FastIVA) separation algorithm to noise. Simulation experiments show the effectiveness of a denoise-FastIVA, under the condition that the baseband signal of binary phase shift keying (BPSK) and binary frequency shift keying (2FSK) signal modulation signal is 10 bits respectively,the separation accuracy of linear frequency modulization (LFM) has increased from 87% to more than 94%; BPSK has risen from 83% to over 97%; 2FSK has improved from 81% to over 95%. When the SNR is greater than 10 dB, the separation similarity of denoise-FastIVA for the communication mixed signals is more than 90%, and the demixing signal can demodulate the baseband signal completely and correctly. Baseband signals of experimental BPSK and 2FSK signal modulation signals are 100 bits respectively. When the signal-to-noise ratio is greater than 5dB, the signal separated by denoise-FastIVA method has the highest similarity coefficient with the source signal, and the bit error rate (BER) of the separated BPSK signal and the separated 2FSK signal are the lowest, compared with the traditional frequency domain demixing method and FastIVA algorithm.

Research on Permanent Magnet-Type Super-Low-Frequency Mechanical Antenna Communication

In the super-low-frequency ( 30 ∼ 300 Hz ) band communication, the traditional antenna covers a large area and has low radiation efficiency. The excitation of electromagnetic waves by the mechanical motion of permanent magnets enables miniaturized technology for super-low-frequency communication. For this miniaturization technique, this paper proposes a super-low-frequency communication architecture framework. Theoretical analysis and experimental verification of each unit module in the structural framework are carried out to achieve high-quality communication. For the radiation unit, permanent magnet parameters and communication distances are introduced to establish a rotating permanent magnet radiation power analysis model and to study the radiation characteristics of rotating permanent magnets. For the receiver unit, a sensitivity normalization characterization method based on the ratio of the coil thermal noise voltage to the induced voltage is proposed. Based on the sensitivity analysis model, a square coil was developed that meets the communication requirements of a mechanical antenna and an experimental platform was built. Experiments are conducted on the factors affecting radiated power and coil sensitivity, and 2FSK signal modulation communication experiments are conducted to verify the feasibility of the communication structure framework. The volume of the mechanical antenna permanent magnets in the experiment is all below 10 cm3, and the operating frequency is continuously adjustable from 0 to 250 Hz. The experimental results show that the near-field radiated power of a rotating permanent magnet is proportional to square of the volume of the rotating permanent magnet; the sensitivity of the coil is proportional to the number of turns and the area of the coil. By controlling the speed in real time, you can control the frequency of the signal and modulate it.

A Flexible Multi-Format Signal Generation Method Based on Optically Coupled Selector Switch

An approach for microwave signal generation with adjustable formats including ASK, PSK, FSK and FPSK (FSK-PSK) is proposed and demonstrated in this paper. In the proposed scheme, a phase modulator (PM) and an optical coupler form optically coupled selector switch (OCSS), which transmit the optical signal on specified path by adjusting its driving signal. Two parallel-placed Dual-Drive Mach-Zehnder modulators (DD-MZM) and a followed photodetector (PD) are employed to generate the multi-format microwave signals. From a theoretical analysis, the microwave signals with tunable formats can be obtained by properly adjusting the amplitude of the coding signals. The simulation and experimental results show that the ASK, PSK, FSK and FPSK signals are successfully generated, and the modulation format can be switched simply by adjusting the system parameters. In addition, the frequency and bit rate of generated signal can be adjusted according to the demand, so flexible tunability can be realized easily.

Communication Signal Modulation Mechanism Based on Artificial Feature Engineering Deep Neural Network Modulation Identifier

Based on the characteristics of time domain and frequency domain recognition theory, a recognition scheme is designed to complete the modulation identification of communication signals including 16 analog and digital modulations, involving 10 different eigenvalues in total. In the in‐class recognition of FSK signal, feature extraction in frequency domain is carried out, and a statistical algorithm of spectral peak number is proposed. This paper presents a method to calculate the rotation degree of constellation image. By calculating the rotation degree and modifying the clustering radius, the recognition rate of QAM signal is improved significantly. Another commonly used method for calculating the rotation of constellations is based on Radon transform. Compared with the proposed algorithm, the proposed algorithm has lower computational complexity and higher accuracy under certain SNR conditions. In the modulation discriminator of the deep neural network, the spectral features and cumulative features are extracted as inputs, the modified linear elements are used as neuron activation functions, and the cross‐entropy is used as loss functions. In the modulation recognitor of deep neural network, deep neural network and cyclic neural network are constructed for modulation recognition of communication signals. The neural network automatic modulation recognizer is implemented on CPU and GPU, which verifies the recognition accuracy of communication signal modulation recognizer based on neural network. The experimental results show that the communication signal modulation recognizer based on artificial neural network has good classification accuracy in both the training set and the test set.

ПОВЫШЕНИЕ ПОМЕХОЗАЩИЩЕННОСТИ ПЕРЕДАЧ ДЕКАМЕТРОВЫХ РАДИОКАНАЛОВ В УСЛОВИЯХ НЕПРЕДНАМЕРЕННЫХ ПОМЕХ

The transmission of messages is a complex process, which is largely determined by the properties of the radio channel used. Decameter radio channels are the most difficult for organizing communication, since the ionospheric propagation of radio waves is associated with their significant attenuation, due to the significant length of the paths, as well as the presence of Rayleigh fading in the channel. However, the possibility of transmitting information over long distances without serious resource costs stimulates further research to improve the reliability of decameter radio communication. In this paper, we investigate the possibility of increasing the noise immunity of frequency-shift keying transmissions of decameter radio channels in conditions of unintentional interference due to the use of broadband signals. An analytical expression of the dependence of the probability of a bit error on the level of the ratio of the peak signal power to the peak interference power is considered; a graph of this dependence is presented. It is shown that the plot is consistent with the overall noise immunity estimate for Rayleigh fading channels using double FSK signals. The rationality of methods for obtaining the required reception quality in decameter radio channels is analyzed. It is shown that the most rational direction for increasing the noise immunity of FM-2 transmissions in decameter radio channels with Rayleigh fading in conditions of unintended interference is the use of broadband signals. In this case, for expansion, it is advisable to choose a value kf = 7, which makes it possible to increase the noise immunity by 9 dB. The conclusions are illustrated by graphs.

Photonic Approach for Generation and Fast Switching of Binary Digitally Modulated RF Signals

A photonic method to generate hybrid binary digitally modulated radio frequency (RF) signals (i.e. ASK, PSK, and FSK) by using a polarization-division-multiplexed Mach-Zehnder modulator (PDM-MZM) is proposed. The PDM-MZM is driven by two RF signals with different carrier frequencies and two multiplied digital signals. By properly controlling the offsets and the amplitudes of the digital signals, ASK, PSK, and FSK signals can be generated and switched fastly. RF signals at 4/6 GHz and 10/15 GHz with switchable modulation formats are experimentally generated. Moreover, the performances of the generated signals are evaluated in a wireless transmission system and corresponding bit error rate (BER) curves of the signals are presented.

Blind Parameter Estimation of M-FSK Signals in the Presence of Alpha-Stable Noise

Blind estimation of parameters for ${M}$ -ary frequency-shift-keying ( ${M}$ -FSK) signals is great of importance in intelligent receivers. Many existing algorithms have assumed white Gaussian noise. However, their performance severely degrades when grossly corrupted data, i.e., outliers, exist. This article solves this issue by developing a novel approach for parameter estimation of ${M}$ -FSK signals in the presence of alpha-stable noise. Specifically, the proposed method exploits the generalized first- and second-order cyclostationarity of ${M}$ -FSK signals with alpha-stable noise, which results in closed-form solutions for unknown parameters in both time and frequency domains. As a merit, it is computationally efficient and thus can be used for signal preprocessing, symbol timing estimation, signal and noise power estimation. Furthermore, substantial theoretical analysis on the performance of the proposed approach is provided. Simulations demonstrate that the proposed method is robust to alpha-stable noise and that it outperforms the state-of-the-art algorithms in many challenging scenarios.

A blind separation algorithm for heterogeneous mixed signals

Aiming at the problem that the existing algorithms can only achieve single-channel blind separation (SCBS) for signals with co-frequency and co-modulated, the gravitational field resampling particle filter (GFR-PF) algorithm was proposed. The GFR-PF can realize SCBS of binary phase shift keying (BPSK) and binary frequency shift keying (2FSK) that overlap in both time and frequency domain and are mixed in a single-channel with environmental noise. The GFR-PF was used to jointly detect symbols and estimate unknown parameters of the BPSK and 2FSK signals. Besides, the blind separation of different frequencies and different modulations signals, which was called the mixed heterogeneous signal blind separation (HSBS). The proposed algorithm not only improved the global search performance and tracking accuracy of the blind separation of the same frequency and same modulation mixed signals but also realized the HSBS of BPSK and 2FSK. Thus, the blind separation of heterogeneous mixed signals containing BPSK and 2FSK with different amplitudes and bit rates were achieved by the proposed algorithm. Based on this heterogeneous mixed signal model, it was proposed by this paper that anti-interception capability was improved through mixed transmission of BPSK and 2FSK signals with different amplitudes.

A new method for improving the inductively coupled data transmission rate of mooring buoy based on carrier signal frequency selection

In the inductively coupled data transmission system of the mooring buoy, the carrier signal frequency of the transmission channel is limited due to the inherent characteristics of the system, resulting in limited channel bandwidth. The limited channel bandwidth limits the increase in inductively coupled data transmission rate. In order to improve the inductively coupled data transmission rate of mooring buoy as much as possible without damaging the data transmission performance, a new method was proposed in this paper. The method is proposed to improve the data transmission rate by selecting the appropriate carrier signal frequencies based on the principle of maximizing the amplitude value of amplitude-frequency characteristic curve of the system. Research has been done according to this method as follows. Firstly, according to the inductively coupled transmission mooring buoy structure, the inductively coupled data transmission circuit model was established. The binary frequency shift keying (2FSK) digital signal modulation mode was selected. Through theoretical analysis, the relation between the carrier signal frequency and the data transmission performance, the relation between the carrier signal frequency and the 2FSK signal bandwidth were obtained. Secondly, the performance and the bandwidth of the signal transmission were studied for the inherent characteristics of the actual inductively coupled data transmission system. The amplitude-frequency characteristic of the system was analyzed by experiments. By selecting the appropriate carrier signal frequency parameters, an excellent data transmission performance was guaranteed and a large 2FSK signal bandwidth was obtained. Finally, an inductively coupled data transmission rate optimization experiment and a bit error rate analysis experiment were designed and carried out. The results show that the high-speed and reliable data transmission of the system was realized and the rate can reach 100 kbps.

Generation of Encrypted FSK RF Signals for Secured Communication Inspired with High Frequency Technique

The paper describes a secret data transmission method using high-frequency techniques. The data security system consists of two inter-related parts. One deals with the encryption of binary data using the RSA algorithm on software platform. The other introduces an innovative conception of implementing encrypted FSK signal generation simulated with microwave techniques & technologies. Here, it requires the simultaneous generation of a pair of two independent high-frequency signals with the help of reflex klystron. In this scheme, the high-frequency generator is biased by the repeller voltage and superimposed on a series of RSA encrypted binary data. So the system creates two high frequencies, one representative to the positive and the other one to the negative portion of the data referring in an FSK signal. The new concept has been also verified with the help of simulation and experiment.

Parameter Optimization of Generalized S Transform Based on Improved Genetic Algorithm

Background: For the traditional Fourier Transform (FT), it cannot effectively detect the frequency of non-stationary signals with time. Analyzing the local characteristics of time-varying signal by using FT is hard to achieve. Therefore, many time-frequency analysis methods which can meet different needs have been proposed on the basis of the traditional Fourier transform, like the Short Time Fourier Transform (STFT), the widely used Continuous Wavelet Transform (CWT), Wigner-Ville Distribution (WVD) and so on. However, the best time and frequency resolution cannot be achieved at the same time due to the uncertainty criterion. Methods: From the point of view of optimizing time-frequency performance, a new Generalized S Transform (GST) window function optimization method is proposed by combining time frequency aggregation with an improved genetic algorithm in this paper. Results: In the noiseless condition, the Linear Frequency Modulation (LFM), Nonlinear Frequency Modulation (NLFM) and binary Frequency Shift Keying (2FSK) signals are simulated. The simulation results prove that the method can improve the time-frequency concentration and decreasing Rényi entropy effectively. Compared with other four traditional time-frequency analysis methods, the improved GST has more advantages. Conclusion: In this paper, a new method of optimizing the window function in GST based on improved GA is proposed in this paper. Experiments on LFM, NLFM and 2FSK signals show that the proposed method not only has the advantages of high resolution, but also determines the optimal parameters via the time frequency focusing criterion and the Rényi entropy. Compared with the other four kinds of time-frequency analysis methods, the optimized GST based on improved GA in this paper has the best time-frequency focusing.

Probabilities of False Alarm and Detection for the First-Order Cyclostationarity Test: Application to Modulation Classification

Automatic modulation classification is one of the most challenging problems of cognitive radio and has significant commercial and military application. This letter focuses on blind modulation classification of first-order cyclostationary signals under a Gaussian channel. A detailed theoretical analysis of the first-order cyclostationarity test has been performed. We present the theoretical expressions of the probability of false alarm $P_{fa}$ and the probability of detection $P_{d}$ as a function of the selected threshold for the first-order cyclostationarity test based constant false alarm rate detector. The $P_{d}$ is presented for only AM and $M$ -FSK signals, which are the only signals that possess first-order cyclostationary features. Theoretical formulations presented in this letter are validated by extensive simulation results.

Modified Cramér-Rao Bound for $M$-FSK Signal Parameter Estimation in Cauchy and Gaussian Noise

The Cramer-Rao bound (CRB) provides an efficient standard for evaluating the quality of standard parameter estimators. In this paper, a modified Cramer-Rao bounds (MCRB) for modulation parameter estimations of $\boldsymbol{M}$ -ary frequency-shift-keying ( $\boldsymbol{{M}}$ -FSK) signals is proposed under the condition of the Gaussian and non-Gaussian additive interference. We extend the MCRB to the estimation of a vector of non-random parameters in the presence of nuisance parameters. Moreover, the MCRB is applied to the joint estimation of phase offset, frequency offsets, frequency deviation, and symbol period of $\boldsymbol{M}$ -FSK signal with two important special cases of alpha stable distributions, namely, the Cauchy and the Gaussian. The extensive simulation studies are conducted to contrast the MCRB for the modulation parameter vector in different noise environments.