Amplitude Fluctuations Of Signals Research Articles

A new approach for GNSS spoofing detection using power and signal quality monitoring

Abstract Global Navigation Satellite System (GNSS) signals are highly susceptible to spoofing attacks. Signal Quality Monitoring (SQM) methods are simple and easy to detect spoofing. However, traditional SQM methods are only effective for matched-power cases and exhibit high detection probability only for a short time. This study introduces a new approach, exploiting anomalies in receiver correlation outputs during spoofing. It efficiently detects signal amplitude fluctuations and correlation peak distortions. The Texas Spoofing Test Battery (TEXBAT) dataset is used to evaluate the detection performance of the proposed approach. The results show that the proposed approach has excellent detection performance in various spoofing cases, including matched-power, overpowered, static, and dynamic cases. This approach surpasses traditional SQM metrics in detection probability and sensitivity to spoofing stages. Importantly, the proposed approach detects spoofing early.

PAPR reduction using polynomial based compressing with Rapp model in GFDM

Generalized Frequency Division Multiplexing (GFDM) has been considered as an attractive candidate to replace Orthogonal Frequency Division Multiplexing (OFDM) for the fifth generation (5 G) mobile networks. GFDM system has better spectral characteristics compared to the OFDM system due to the usage of properly selected pulse shaping filters. Non-causal ideal filters, such as the raised cosine (RC), are commonly used in the GFDM systems. Here, Generalized frequency division multiplexing is a promising candidate to deploy. However, as an intrinsic property of multi-carrier modulation, the high signal amplitude fluctuation can cause several degradation effects when the signal is affected by nonlinearities. The pulse shaping filters are designed using the computationally efficient quadratic programming (QP) approach. Therefore, the aim of this paper is to evaluate the performance of Generalized frequency division multiplexing systems undergoing nonlinear amplification. We evaluate the bit error ratio using high power amplifier, namely the Rapp model. The results show that the fault rate is apparently affected according to the particular high power amplifier model and its transmission parameters.

Threshold distribution of equal states for quantitative amplitude fluctuations

Objective. The distribution of equal states (DES) quantifies amplitude fluctuations in biomedical signals. However, under certain conditions, such as a high resolution of data collection or special signal processing techniques, equal states may be very rare, whereupon the DES fails to measure the amplitude fluctuations. Approach. To address this problem, we develop a novel threshold DES (tDES) that measures the distribution of differential states within a threshold. To evaluate the proposed tDES, we first analyze five sets of synthetic signals generated in different frequency bands. We then analyze sleep electroencephalography (EEG) datasets taken from the public PhysioNet. Main results. Synthetic signals and detrend-filtered sleep EEGs have no neighboring equal values; however, tDES can effectively measure the amplitude fluctuations within these data. The tDES of EEG data increases significantly as the sleep stage increases, even with datasets covering very short periods, indicating decreased amplitude fluctuations in sleep EEGs. Generally speaking, the presence of more low-frequency components in a physiological series reflects smaller amplitude fluctuations and larger DES. Significance. The tDES provides a reliable computing method for quantifying amplitude fluctuations, exhibiting the characteristics of conceptual simplicity and computational robustness. Our findings broaden the application of quantitative amplitude fluctuations and contribute to the classification of sleep stages based on EEG data.

The parameters of internal gravity waves in the atmosphere from the amplitude fluctuations of radio occultation signals

We develop a method for the reconstruction of the statistical parameters of internal gravity wave (IGW) in the atmosphere from the amplitude fluctuations of signals acquired in radio occultation observations. We discuss the choice of the model of the IGW spatial spectrum, derive the relationships between the IGW spectra and the amplitude fluctuation spectra, develop the reconstruction algorithm and estimate its uncertainties. The IGW spectrum parameters to be retrieved are the outer (dominant) scale and the structure characteristic, the latter determining the power of saturated IGW. The method was tested on the COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) observations acquired in the winter and summer seasons 2011. The IGW parameters were reconstructed in the height range from the upper boundary of the tropopause to 28 km. We show the altitude-latitudinal distributions of the IGW parameters and two integral characteristics: the variances of the temperature fluctuations and the IGW potential energy. We perform a detailed comparison of our results with those obtained from radiosonde and radio occultation observations. The developed method can be applied for the global monitoring of IGW parameters and activity in the middle atmosphere.

Statistical Shape Mapping Pre-Processing of Metal Oxide Gas Sensor Response for Machine Learning Detection Improvement

IntroductionModulation of metal oxide (MOX) gas sensors working temperature offers possibilities of highly selective detection of various gases, when coupled with signal processing and machine learning [1]. However, stability of response is still a major issue [2], hampering widespread practical application of MOX sensors in the fields of industrial safety, public security, ecological control, non-invasive medical diagnostics etc. Most of the modern approaches of signal pre-processing, aimed at elimination of baseline drift effects, signal amplitude fluctuations due to sensor aging or background variations of analyzed air, act through selection of the most significant features of the response, leading to the loss of some useful part of the signal [3]. This may lead to the unstable system performance in variable ambience conditions, which are characteristic to urban air or air at industrial facilities.The present work introduces shape-space mapping pre-processing of MOX gas sensor response for further application of machine learning in order to improve the identification and quantification of common flammable and pollutant gases.ExperimentalThree different gas detection tasks were studied. First - identification of propane vs hydrogen in the flow of real urban air; second – identification of methane vs propane in same conditions, third – determination of CO concentration in clean humid air. Laboratory made SnO2-based MOX gas sensors [4] were used for the solution of the first and second tasks. Sensors were linearly thermally modulated between 100 and 500 oC in the constant flow of outdoor air, to which gases were admixed. Statistical analysis of response curve shape (statistical shape mapping - SSM - in 2D space of sensing element electrical resistance and temperature) was performed as a pre-processing procedure prior to machine learning algorithm use. The performance of the obtained ML model was evaluated with the use of completely independent set of data, obtained in separate days of experiment [5]. The ability of SSM to improve the gas identification accuracy of the ML model was compared to raw sensor response, normalized response as well as response, pre-processed via principal component analysis (PCA), discrete wavelet transform (DWT) and polynomial curve fitting (PCF) approach. Same comparison has been made during the solution of the third task with the use of publicly available database of response of thermally modulated commercially available MOX gas sensors [6,7].Results and discussionThe results of the ML model testing in the case of methane vs propane discrimination task (Table 1) shows that improvement of sensitivity (AuPd/SnO2 sensor [4]) improves the accuracy of detection. Normalization of sensor response doers not necessary lead to the reduced error of model answer and other pre-processing techniques lead to the decreased accuracy of detection compared to the raw sensor response, used for the machine learning. The only exception is SSM pre-processing approach, improving the accuracy of identification in the case of all three used sensors. The day-to day error variation does not correlate with the atmospheric pressure, air temperature, humidity or regional air quality index (AQI), indicating local uncontrolled pollution as a source of erroneous gas identification [8]. Similar results are obtained in the case of hydrogen vs propane identification task [9]. For CO quantification task by commercial sensors with rectangular impulse type working temperature modulation much better performance of ML model is observed in the case of SSM pre-processed response of TGS 3870-A04 gas sensor type (Figaro), than in case of SB-500-12 (FIS) sensors compared to other pre-processing technique [8].ConclusionsThe application of statistical shape space pre-processing to the signal of temperature modulated metal oxide gas sensors improves the selectivity of gases identification with the use of ANN based machine learning algorithm in comparison to other methods – PCA, DWT, PCF, data normalization. It helps to eliminate effects of sensor response drift, amplitude fluctuations, while the major source of erroneous gas identification may rise from the lack of shape features in the original sensor response and the uncontrolled local background air pollution. Improvement in general sensitivity of sensor, is favorable for shape space signal pre-processing in order to enhance the selectivity of chemically similar gases detection at low concentrations in realistic air conditions. The proposed approach can be considered as versatile as its performance is successfully tested on different type of sensors and gases in different range of concentrations in air with different types of working temperature modulation.AcknowledgementsThe reported study was funded by RFBR according to the research project № 18-33-20220.

Vertical and slanted sound propagation in the near-ground atmosphere: Amplitude and phase fluctuations.

Sound propagation along vertical and slanted paths through the near-ground atmosphere impacts detection and localization of low-altitude sound sources, such as small unmanned aerial vehicles, from ground-based microphone arrays. This article experimentally investigates the amplitude and phase fluctuations of acoustic signals propagating along such paths. The experiment involved nine microphones on three horizontal booms mounted at different heights to a 135-m meteorological tower at the National Wind Technology Center (Boulder, CO). A ground-based loudspeaker was placed at the base of the tower for vertical propagation or 56 m from the base of the tower for slanted propagation. Phasor scatterplots qualitatively characterize the amplitude and phase fluctuations of the received signals during different meteorological regimes. The measurements are also compared to a theory describing the log-amplitude and phase variances based on the spectrum of shear and buoyancy driven turbulence near the ground. Generally, the theory correctly predicts the measured log-amplitude variances, which are affected primarily by small-scale, isotropic turbulent eddies. However, the theory overpredicts the measured phase variances, which are affected primarily by large-scale, anisotropic, buoyantly driven eddies. Ground blocking of these large eddies likely explains the overprediction.

Improved step tracking algorithm based on gradient method

The basic principle of the satcom on the move antenna is to detect the error angle between the antenna beam pointing and the satellite direction according to the received satellite signal, and convert it into the corresponding error electrical signal. The controller uses the error electrical signal to control the antenna to make the antenna move in the direction where the error signal decreases. The tracking accuracy of traditional step tracking is not high, and the response speed is very slow, and the signal amplitude fluctuation affects the tracking accuracy. Since the gain graph of the antenna can be regarded as a non-linear stepped objective function, an improved step tracking algorithm based on the gradient method is proposed, which combines the step tracking with the optimization algorithm to achieve precise tracking. The algorithm optimizes the antenna gain pattern as the objective function to find the azimuth and elevation coordinates corresponding to the maximum point of the antenna gain function. The gain function maximization is transformed into the objective function minimization problem, and the minimum value of the objective function is found through the optimization algorithm, which corresponds to the direction of the antenna when the satellite is accurately aligned. The gradient method is selected for optimization, which is stable as a whole and simple iterative process. Theoretical analysis and simulation results show that the algorithm can obtain higher tracking accuracy while maintaining a lower program complexity.

Space-Ground Coherent Optical Links: Ground Receiver Performance With Adaptive Optics and Digital Phase-Locked Loop

In the framework of optical high data rate satellite-to-ground links, we investigate the performance of a coherent receiver which combines an adaptive optics system and a digital carrier synchronization technique. We propose a digital carrier synchronization system based on a phase-locked loop and use end-to-end simulations to characterize the impact of the atmospheric turbulence in the case of a representative low Earth orbit satellite-to-ground transmission link. The results show that classical digital phase-locked loop techniques can be a reliable solution to accurately compensate for the Doppler frequency shift between the incoming signal and the local oscillator at the ground station, in the presence of a preliminary coarse frequency estimation. Adaptive optics compensation enables the loop to lock after a few milliseconds and to accurately track the phase fluctuations. The bit-error-rate performance is not degraded by the digital loop but suffers from the residual signal amplitude fluctuations.

In vivo diffusion-weighted MRS using semi-LASER in the human brain at 3T: Methodological aspects and clinical feasibility.

Diffusion-weighted (DW-) MRS investigates non-invasively microstructural properties of tissue by probing metabolite diffusion in vivo. Despite the growing interest in DW-MRS for clinical applications, little has been published on the reproducibility of this technique. In this study, we explored the optimization of a single-voxel DW-semi-LASER sequence for clinical applications at 3T, and evaluated the reproducibility of the method under different experimental conditions. DW-MRS measurements were carried out in 10 healthy participants and repeated across three sessions. Metabolite apparent diffusion coefficients (ADCs) were calculated from mono-exponential fits (ADCexp ) up to b=3300s/mm2 , and from the diffusional kurtosis approach (ADCK ) up to b=7300s/mm2 . The inter-subject variabilities of ADCs of N-acetylaspartate + N-acetylaspartylglutamate (tNAA), creatine + phosphocreatine, choline containing compounds, and myo-inositol were calculated in the posterior cingulate cortex (PCC) and in the corona radiata (CR). We explored the effect of physiological motion on the DW-MRS signal and the importance of cardiac gating and peak thresholding to account for signal amplitude fluctuations. Additionally, we investigated the dependence of the intra-subject variability on the acquisition scheme using a bootstrapping resampling method. Coefficients of variation were lower in PCC than CR, likely due to the different sensitivities to motion artifacts of the two regions. Finally, we computed coefficients of repeatability for ADCexp and performed power calculations needed for designing clinical studies. The power calculation for ADCexp of tNAA showed that in the PCC seven subjects per group are sufficient to detect a difference of 5% between two groups with an acquisition time of 4min, suggesting that ADCexp of tNAA is a suitable marker for disease-related intracellular alteration even in small case-control studies. In the CR, further work is needed to evaluate the voxel size and location that minimize the motion artifacts and variability of the ADC measurements.

Low-distortion diffusion tensor MRI with improved phaseless encoding.

Due to the motion-related instability of the signal phase, diffusion MRI is usually performed with single-shot techniques such as the echo-planar imaging (EPI), which are resolution-limited and suffer from distortions caused by resonance offsets. Multi-shot methods may improve the images but require time-consuming navigators or a trade-off of the sensitivity encoding to measure shot-dependent phase errors. We have recently introduced an alternative approach to multi-shot MRI called phaseless encoding, which, by analogy to optical super-resolution methods, relies on the magnitude value of images taken in different shots thus discarding the phase error without navigators, and demonstrated its capability to perform diffusion MRI at sub-millimeter scale on a standard 3T scanner. In this work, we apply phaseless encoding in a routine diffusion tensor imaging (DTI) protocol with a moderately high resolution that is still within reach of single-shot EPI with the same hardware, and compare both techniques with respect to image distortions. A qualitative comparison of the phaseless encoding with the established navigator-based readout-segmented EPI is also presented. Several technical improvements are proposed to make phaseless encoding compatible with the routine scanning mode. The tagging radiofrequency pulses used in the encoding sequence are made slice-selective to avoid artefacts caused by saturation effects in multi-slice scans and their flip angle is optimized to reduce the intrinsic SNR loss. The super-resolution reconstruction algorithm is also improved to better suppress Gibbs ringing and to correct for possible signal amplitude fluctuations. Our study shows that the phaseless encoding is a promising approach to diffusion weighted imaging. It can easily be implemented in multi-slice sequences and produces less distorted images than the single-shot EPI at the same resolution and hardware parameters. It provides similar results to readout-segmented EPI but without the need of navigators.

The NEFOCAST System for Detection and Estimation of Rainfall Fields by the Opportunistic Use of Broadcast Satellite Signals

In this paper, we present results from the NEFOCAST Project, funded by the Tuscany Region, aiming at detecting and estimating rainfall fields from the opportunistic use of the rain-induced excess attenuation incurred in the downlink channel by a commercial DVB satellite signal. The attenuation is estimated by reverse-engineering the effects of the various propagation phenomena affecting the received signal, among which, in first place, the perturbations factors affecting geostationary orbits, such as the gravitational attraction from the moon and the sun and the inhomogeneity in Earth mass distribution and, second, the small-scale irregularities in the atmospheric refractive index, causing rapid fluctuations in signal amplitude. The latter impairments, in particular, even if periodically counteracted by correction maneuvers, may give rise to significant departures of the actual satellite position from the nominal orbit. A further problem to deal with is the daily and seasonal random fluctuation of the rain height and altitude/size of the associated melting layer. All of the above issues lead to nonnegligible random deviations from the dry nominal downlink attenuation, that can be misinterpreted as rain events. In this paper, we show how to counteract these issues by employing two differentially configured Kalman filters designed to track slow and fast changes of the received signal-to-noise ratio, so that the rain events can be reliably detected and the relevant rainfall rate estimated.

Cycling fatigue evaluation using weighted-cumulated methodology

In this paper, the weighted-cumulated methodology designed for the objective muscle fatigue estimation using surface electromyography is improved and extended for cycling applications. An automatic signal burst segmentation is proposed for dynamic electromyography, which is robust to signal amplitude fluctuations and abrupt variation of the experimental protocol parameters. The developed algorithm is integrated into a single instrumental tool. To evaluate the proposed methodology, nine participants performed cycling exercise until muscular failure in three different experimental protocols. In the first protocol, angular velocity was kept constant and exercise power was increased. In the second protocol, power was kept constant and the angular velocity was increased. The third protocol is maintained constant in both power and angular velocity at relatively high values. During the tests, surface electromyography signal was acquired from vastus lateralis. Behavioral characteristics and performance comparison involving the proposed experimental protocols are shown. The interpretations associated with objective metric to estimate muscle fatigue are discussed. The experimental results, obtained using improved weighted-cumulated methodology, are shown to be sensitive enough to distinguish spectral signature changes in the cycling electromyographic signals associated with muscle fatigue. The weighted-cumulated methodology has been shown to be fully applicable in dynamic physical protocols such as cycling. However, the investigations point out that the specification of the experimental protocol is also very important for the results reliability.

Velocity of the Inner Solar Wind from Coronal Sounding Experiments with Spacecraft

Measurement results are presented for the velocity of density irregularities in solar wind plasma, which modulate the frequency of coherent radio signals from the Galileo spacecraft in the S-band. The measurements have been performed by the spaced receiving technique at ground monitoring stations. The data cover a range of heliocentric distances from 7 to 72 solar radii at low heliolatitudes near solar minimum. It is shown that acceleration of slow solar wind continues up to distances of about 30 solar radii. In the overlapping ranges of distances from the Sun, the results are qualitatively consistent with LASCO SOHO data for the same periods, with the previous results obtained by analyzing the amplitude fluctuations of signals from the Venera 15 and 16 spacecraft, and with the more recent measurements acquired using the Mars Express spacecraft.

The preliminary study on fluctuation of ocean sound field

The ocean environmental variation causes the amplitude and phase fluctuations of acoustic signals that travel in the ocean acoustic waveguide. Sound propagation fluctuation is studied based on the deep water fixed-point sound propagation experiment data acquired in the northern South China Sea in 2016. In this experiment, two sets of submerged buoy systems, which integrate the emission and receiving of sound wave, have continuously and steadily worked as long as three months. Considering the Doppler frequency shift, the amplitude and phase of acoustic signals are calculated after matched filtering. The sound intensity scintillation index computed for the entire record is 0.8, which is less than the saturation value of one. In contrast, the scintillation index computed for the 2001 ASIAEX South China Sea Experiment is 2.6 and 1.7. The ocean environmental variation and its relation with sound propagation fluctuation are analyzed.

Signal reshaping and noise suppression using photonic crystal Fano structures.

We experimentally demonstrate the use of photonic crystal Fano resonances for reshaping optical data signals. We show that the combination of an asymmetric Fano resonance and carrier-induced nonlinear effects in a nanocavity can be used to realize a nonlinear power transfer function, which is a key functionality for optical signal regeneration, particularly for suppression of amplitude fluctuations of data signals. The experimental results are explained using simulations based on coupled-mode theory and also compared to the case of using conventional Lorentzian-shaped resonances. Using indium phosphide photonic crystal membrane structures, we demonstrate reshaping of 2 Gbit/s and 10 Gbit/s return-to-zero on-off keying (RZ-OOK) data signals at telecom wavelengths around 1550 nm. Eye diagrams of the reshaped signals show that amplitude noise fluctuations can be significantly suppressed. The reshaped signals are quantitatively analyzed using bit-error ratio (BER) measurements, which show up to 2 dB receiver sensitivity improvement at a BER of 10-9 compared to a degraded input noisy signal. Due to efficient light-matter interaction in the high-quality factor and small mode-volume photonic crystal nanocavity, low energy consumption, down to 104 fJ/bit and 41 fJ/bit for 2 Gbit/s and 10 Gbit/s, respectively, has been achieved. Device perspectives and limitations are discussed.

System validation of CO2-laser-based phase contrast imaging on HL-2A tokamak

System validation and density fluctuation calibration of phase contrast imaging (PCI) on an HL-2A tokamak are presented. Signals from different channels show not only a pronounced modulation of an incident laser beam induced by a sound wave, but also an excellent magnification and low image distortion of optics. The frequency-wavenumber spectrum is achieved by using two-dimensional Fourier transform of time series signals. The conversion coefficient between detected signal amplitude and chord integral plasma density fluctuation is 2.35 × 1013 m−2/mV, which promises a suitable signal level at the order of volts of the PCI in typical HL-2A discharges.

Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals.

Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity () and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity.

Joint Amplitude-Phase Compensation for Ionospheric Scintillation in GEO SAR Imaging

The ionospheric scintillation induced by local ionospheric plasma anomalies could lead to significant degradation for geosynchronous earth orbit synthetic aperture radar (SAR) imaging. As radar signals pass through the ionosphere with locally variational plasma density, the signal amplitude and phase fluctuations are induced, which principally affect the azimuthal pulse response function. In this paper, the compensation of signal amplitude and phase fluctuations is studied. First, space-variance problem of scintillation is addressed by image segmentation. Then, SPECAN imaging algorithm is adopted for each image segment, because it is computationally efficient for small imaging scene. Furthermore, an iterative algorithm based on entropy minimum is derived to jointly compensate the signal amplitude and phase fluctuations. Finally, a real SAR scene simulation is used to validate our proposed method, where both the simulated scintillation using phase screen technique and the real GPS-derived scintillation data are adopted to degrade the imaging quality.

Open-loop GPS signal tracking at low elevation angles from a ground-based observation site

Abstract. A 1-year data set of ground-based GPS signal observations aiming at geometric elevation angles below +2° is analysed. Within the "GLESER" measurement campaign about 2600 validated setting events were recorded by the "OpenGPS" open-loop tracking receiver at an observation site located at 52.3808° N, 13.0642° E between January and December 2014. The measurements confirm the feasibility of open-loop signal tracking down to geometric elevation angles of −1 to −1.5° extending the corresponding closed-loop tracking range by up to 1°. The study is based on the premise that observations of low-elevation events by a ground-based receiver may serve as test cases for space-based radio occultation measurements, even if the latter proceed at a significantly faster temporal scale. The results support the conclusion that the open-loop Doppler model has negligible influence on the derived carrier frequency profile for strong signal-to-noise density ratios above about 30 dB Hz. At lower signal levels, however, the OpenGPS receiver's dual-channel design, which tracks the same signal using two Doppler models differing by 10 Hz, uncovers a notable bias. The repeat patterns of the GPS orbit traces in terms of azimuth angle reveal characteristic signatures in both signal amplitude and Doppler frequency with respect to the topography close to the observation site. Mean vertical refractivity gradients, extracted from ECMWF meteorological fields, correlate weakly to moderately with observed signal amplitude fluctuations at geometric elevation angles between +1 and +2°. Results from multiple phase screen simulations support the interpretation that these fluctuations are at least partly produced by atmospheric multipath; at negative elevation angles diffraction at the ground surface seems to contribute.

Performance Enhancement of Discrete Multiwavelet Critical-Sampling Transform-Based OFDM System Using Hybrid Technique Under Different Channel Models

A hybrid technique, which is a combination of the Fast Fourier Transform (FFT) and Sliding Window (SW) technique, is proposed for the development of new structure for Discrete Multiwavelet Critical-Sampling Transform based Orthogonal Frequency Division Multiplexing (DMWCST-OFDM) system under multipath fading channels with the Doppler frequency effect. FFT is utilized to increase the orthogonality of subcarriers against the multipath frequency-selective fading channels. SW technique reduces the fluctuation of signal amplitude, thereby reducing the Doppler frequency effect. This hybrid technique offers a good tradeoff between performance and complexity, where this technique needs more computations. However, it performs better than the standard DMWCST-OFDM system. The performance of the proposed system, called SW-DMWCST-OFDM, was compared to that of the standard DMWCST-OFDM, SW-FFT-OFDM, and FFT-OFDM systems under three channels, namely, additive white Gaussian noise, flat fading, and frequency-selective fading. The simulation results show that the proposed model performs better than the three other models in all types of channels.