Search Results (430)

Visible Light Communication (VLC) systems commonly employ optical orthogonal frequency division multiplexing (O-OFDM) to achieve high data rates, benefiting from its robustness against multipath effects and intersymbol interference (ISI). However, a key limitation of asymmetrically clipped direct current biased optical–OFDM (ACO-OFDM) systems lies in their inherently high peak-to-average power ratio (PAPR), which significantly affects signal quality and system performance. This paper proposes a joint chaotic encryption and modified μ-non-linear logarithmic companding (μ-MLCT) scheme for ACO-OFDM–based VLC systems to simultaneously enhance security and reduce PAPR. First, image data is encrypted at the upper layer using a hybrid chaotic system (HCS) combined with Arnold’s cat map (ACM), mapped to quadrature amplitude modulation (QAM) symbols and further encrypted through chaos-based symbol scrambling to strengthen security. A μ-MLCT transformation is then applied to mitigate PAPR and enhance both peak signal-to-noise ratio (PSNR) and bit-error-ratio (BER) performance. A mathematical model of the proposed secured ACO-OFDM system is developed, and the corresponding BER expression is derived and validated through simulation. Simulation results and security analyses confirm the effectiveness of the proposed solution, showing gains of approximately 13 dB improvement in PSNR, 2 dB in BER performance, and a PAPR reduction of about 9.2 dB. The secured μ-MLCT-ACO-OFDM not only enhances transmission security but also effectively reduces PAPR without degrading PSNR and BER. As a result, it offers a robust and efficient solution for secure image transmission with low PAPR, making it well-suitable for emerging wireless networks such as cognitive and 5G/6G systems. Full article

We present an experimental demonstration of a daylight-capable Optical Amplify-and-Forward (OAF) relaying system designed to support flexible and high-capacity network topologies. The proposed architecture integrates fiber-based infrastructure with OAF Free Space Optics (FSO) relaying, enabling bidirectional optical communication over 460 m (x2) using SFP-compatible schemes, while addressing Non-Line-of-Sight (NLOS) constraints and fiber disruptions. This work achieves a Bit Error Rate (BER) below the Hard-Decision Forward Error Correction (HD-FEC) limit, validating the feasibility of high-speed urban FSO links. By leveraging low-cost fiber-coupled optical terminals, the system transmits single-carrier 120 Gbps Intensity Modulation/Direct Detection (IM/DD) signals using NRZ (Non-Return-to-Zero) and PAM4 (4-Pulse Amplitude Modulation) modulation formats. Operating entirely in the optical C-Band domain, this approach ensures compatibility with existing infrastructure, supporting scalable mesh FSO deployments and seamless integration with hybrid Radio Frequency (RF)/FSO systems. Full article

The multidimensional parameter measurement of microwave signals, including temporal, spatial, and frequency, is essential for electronic warfare and radar systems. In this article, we present a photonic scheme for real-time microwave frequency and angle-of-arrival (AOA) measurement based on stimulated Brillouin scattering (SBS). In the proposed system, the unknown signal under test (SUT) received by adjacent antennas is injected into a dual-drive Mach–Zehnder modulator (DDMZM). Two branches of the SUT with phase difference interfere in the optical domain, converting phase difference into the power of optical sidebands. These optical sidebands are scanned by combining SBS with frequency-to-time mapping (FTTM) to achieve simultaneous measurement of the AOA and frequency. Consequently, the frequency and AOA of the SUT are mapped to the time interval and normalized amplitude of the output electrical pulses, respectively. Results show that the system can achieve the frequency measurement of multiple RF signals in the range of 5–15 GHz and AOA measurement in the range of −70° to 70°, with measurement errors of ±5 MHz and ±2°, respectively. Furthermore, the frequency measurement range can be flexibly adjusted by tuning the pump optical driving signals. Full article

Radar coincidence imaging (RCI) is widely used in military reconnaissance, hovering unmanned aerial vehicles (UAVs), and non-local Earth observation due to its superior super-resolution imaging performance. However, in portable radar exploration or UAV remote sensing scenarios, the imaging resolution may be limited by the size constraints of the radar’s aperture. Moreover, although the resolution of RCI depends on the randomness of the signal, an excessively random signal setup may be difficult to implement in engineering applications due to rapid frequency jumps and related issues. Therefore, it is essential to achieve super-resolution imaging while maintaining a small aperture and an effectively random signal. In this paper, an amplitude-random linear frequency modulation (AR-LFM) waveform is employed in RCI using a dual-frequency, dual-phase-center, and dual-polarized antenna (DDPA). A multi-channel structure is introduced, and different frequencies and polarization modes are combined using the proposed method, which provides more independent signal information while maintaining a small aperture and effectively reducing signal coherence. This approach increases the singularity between grid points in the target area, thereby enhancing the effective rank of the reference matrix. The simulation results show that the angular resolution of the proposed imaging method is 15 times higher than that of conventional radar imaging. Furthermore, the proposed structure can improve the resolution improvement factor (RIF) by more than two times compared with the traditional RCI method using a conventional antenna and random signals. Full article

Background: Realistic simulation of ECG signals is essential for validating signal-processing algorithms and training artificial intelligence models in cardiology. Many existing approaches model either waveform morphology or heart rate variability (HRV), but few achieve both with high accuracy. This study proposes a hybrid method that combines morphological accuracy with physiological variability. Methods: We developed a mathematical model that integrates Gaussian mesa functions (GMF) for waveform generation and a chaotic Rössler attractor to simulate RR-interval variability. The GMF approach allows fine control over the amplitude, width, and slope of each ECG component (P, Q, R, S, T), while the Rössler system introduces dynamic modulation through the use of seven parameters. Spectral and statistical analyses were applied, including power spectral density (PSD) computed via the Lomb–Scargle, STFT, CWT, and histogram analyses. Results: The synthesized signals demonstrated physiological realism in both the time and frequency domains. The LF/HF ratio was 1.5–2.0 when simulating a normal rhythm and outside these limits in a simulated stress rhythm, consistent with typical HRV patterns. PSD analysis captured clear VLF (0.003–0.04 Hz), LF (0.04–0.15 Hz), and HF (0.15–0.4 Hz) bands. Histogram distributions showed amplitude ranges consistent with real ECGs. Conclusions: The hybrid GMF–Rössler approach enables large-scale ECG synthesis with controllable morphology and realistic HRV. It is computationally efficient and suitable for artificial intelligence training, diagnostic testing, and digital twin modeling in cardiovascular applications. Full article

This paper presents a voltage-controlled phase shifter (VCPS) capable of 360° continuous adjustment, applied in laser frequency-locking systems to obtain maximum amplitude error signals with minimal dispersion. The phase-shifting unit is realized through CMOS integrated circuit design, utilizing comparators, logic gate control modules, and filters. Simulations verify the VCPS, composed of three cascaded units, achieves 360° continuous phase adjustment. A printed circuit board (PCB) was fabricated with the integration of electronic components. The test results demonstrate that the VCPS exhibits a continuous 360° phase shift in one direction with increasing control voltage. It operates from kHz to 50 MHz and maintains a peak-to-peak output amplitude of 5 V or 10 V. The proposed VCPS has been successfully applied in cold-atom interferometry, quantum memory experiments, and optical frequency standards. Full article

Lasers with external electrical modulation are widely used in optical systems, but the generation of well-defined pulses often suffers from distortions in duty cycle and top optical power at high frequencies. This work addresses this limitation by presenting an automated setup for optical pulse correction that combines standard instrumentation with a feedback-based adjustment strategy. The system integrates a continuous-wave laser, a signal generator, an optical analyzer, and a control routine implemented in MATLAB (R2024b Campus Wide). Two nested loops are employed; the inner loop varies the amplitude of a sinusoidal modulation signal to regulate the duty cycle at the desired reference; the outer loop sends commands to the laser to adjust optical power level to a specified reference. Experimental validation shows that the proposed approach significantly improves pulse fidelity over a frequency range up to 100 MHz. In particular, the relative normalized root mean square error (NRMSE) was reduced by more than 97% compared with the case without adjustment, both for duty cycle (1–30 MHz) and top optical power (10–30 MHz). These results demonstrate that precise optical pulse control can be implemented with common laboratory instrumentation, providing a practical and accessible solution for automated pulse conditioning in externally modulated laser setups. Full article

It has recently been recognized that the ionosphere is highly sensitive to pre-seismic effects, and the detection of ionospheric perturbations associated with earthquakes (EQs) is one of the most promising candidates for short-term EQ prediction. In this review, we focus on a possible use of VLF/LF (very low frequency (3–30 kHz)/low frequency (30–300 kHz)) radio sounding of seismo-ionospheric perturbations to study seismogenic effects. Because an understanding of the early history in any area will provide a lot of crucial insights to the readers (especially to young scientists) working in the field of seismo-electromagnetics, we provide a brief history (mainly results reported by a Russian group of scientists) of the initial application of subionospheric VLF/LF propagation for the study of ionospheric perturbations associated with EQs, and then we present our first convincing evidence on the ionospheric perturbation for the disastrous Kobe EQ in 1995, with a new analysis method based on the shifts in terminator times in VLF/LF diurnal variations (minima in the diurnal variations in amplitude and phase). We then summarize our latest results on further evidence of seismo-ionospheric perturbations. Firstly, we present a few statistical studies on the correlation between VLF/LF propagation anomalies and EQs based on long-term data. Secondly, we showcase studies for a few large, recent EQs (including the 2011 Tohoku EQ). Building on those EQ precursor studies, we demonstrate scientific topics and the underlying physics that can be studied using VLF/LF data, highlighting recent achievements including the revolutionary perspective of lithosphere–atmosphere–ionosphere coupling (LAIC) (or how the ionosphere is perturbed due to the lithospheric pre-EQ activity), modulation in VLF/LF data by atmospheric gravity waves (AGWs), Doppler-shift observation, satellite observation of VLF/LF transmitter signals, etc., together with the recommendation of the application of new technologies such as artificial intelligence and critical analysis to VLF/LF analysis. Finally, we want to emphasize again the essential significance of the information on lower-ionospheric perturbations within LAIC studies. Full article

The 6G era necessitates advanced multiplexing techniques that fully utilize various physical dimensions, including time, frequency, polarization, and space to enhance the achievable bitrate per wavelength and satisfy growing demands for capacity and spectral efficiency. Power domain hybrid modulation (PDHM) emerges as a viable technology to overcome the orthogonal limitations inherent in existing multiplexing schemes. In this paper, we introduce an iterative successive interference cancelation (SIC) algorithm for coherent optical transmission systems employing PDHM. The proposed system multiplexes a 16-ary quadrature amplitude modulation (16-QAM) signal with a quadrature phase shift keying (QPSK) signal at distinct power ratios. With the proposed iterative SIC, the system performance is improved by about one order of magnitude. Full article

The Bell–Bloom magnetometer is promising for mobile applications, but its accuracy is limited by heading errors. A recently identified source of such error is a phase shift in the magnetic resonance, which arises from the superposition of two signals, i.e., the primary resonance from synchronous pumping and a secondary resonance, 90° out-of-phase, driven by the AC light shift of the pump laser. Through Bloch equation modeling and experiment, we uncover a counter-intuitive mechanism: although initiated by the AC light shift, the phase shift’s magnitude is determined solely by the pump light’s average power (DC component) and is independent of its AC modulation. This occurs because the amplitude ratio of the two resonances depends exclusively on the DC-power-induced atomic polarization. Based on this insight, we propose a novel DC compensation scheme by adding a continuous counter-polarized beam to cancel the net DC pumping. Theoretically, this simultaneously suppresses both the AC-light-shift-induced phase shift and the DC-light-shift-induced frequency shift. The scheme’s advantage is its simplified approach to polarization control, avoiding the need for high-speed polarization modulation or major hardware changes as the beams share the same optical path. This makes it highly suitable for demanding mobile applications like aerial magnetic surveying and wearable bio-magnetic sensing in unshielded environments. Full article

Piezoelectric synthetic jet actuators typically struggle to generate high-speed jets at low driving frequencies due to the coupling effect between jet frequency and jet intensity. This limitation to some extent restricts their application in flow control within low-speed flow fields. To address this issue, this study presents two methods of signal modulation. The effects of driving signal modulation on dual synthetic jet actuator (DSJA) characteristics were experimentally investigated. A laser displacement meter was used to measure the central point amplitude of the piezoelectric diaphragm, while the velocity at the exit of the DSJAs was measured using a hot-wire anemometer. The effects of signal modulation on the amplitude of the piezoelectric diaphragm, the maximum jet velocity, and the frequency domain characteristics of the dual synthetic jet (DSJ) were thoroughly analyzed. Experimental results demonstrate that driving signal modulation can enhance jet velocity at relatively low driving frequencies. The modulated DSJ exhibits low-frequency characteristics, rendering it suitable for flow control applications that require low-frequency jets. Furthermore, the coupling effect between jet frequency and jet intensity in the piezoelectric DSJA is significantly alleviated. Starting from the vibration displacement of the piezoelectric transducer (PZT), this paper systematically elaborates on the corresponding relationship between PZT displacement and the peak velocity at the jet outlet, and the “low-frequency and high-momentum jet generation method based on signal modulation” proposed herein is expected to break through the momentum–frequency coupling limitation of traditional piezoelectric dual-stenosis jet actuators (DSJAs) and enhance their application potential in low-speed flow control. Full article

This paper presents an orthogonal time–frequency space (OTFS)-based integrated sensing and communication (ISAC) framework for vehicular-to-base-station (V2B) scenarios, where a synthetic road environment models vehicular mobility and multipath propagation with explicit ground truth. In the sensing stage, OTFS probing signals with Gray-coded quadrature amplitude modulation (QAM) are processed via inverse symplectic finite Fourier transform (ISFFT) and cyclic prefix orthogonal frequency-division multiplexing (CP-OFDM). The receiver applies cyclic prefix (CP) removal, fast Fourier transform (FFT), and symplectic finite Fourier transform (SFFT) to extract delay–Doppler (DD) responses. Channel estimation uses time–frequency least squares (TF-LS), robust background suppression, constant false alarm rate (CFAR) detection, and non-maximum suppression (NMS), yielding Precision = 0.79, Recall = 0.84, and F1 = 0.82. Communication decoding employs per-bin least squares, minimum mean-squared error (MMSE) equalization, and Gray-mapped QAM demapping. Across ten frames at 20 dB SNR, the system decoded $1.887\times {10}^8$ bits with $1.575\times {10}^5$ errors, producing a bit error rate (BER) of $8.34\times {10}^{-4}$. Error vector magnitude (EVM) analysis reports mean = 0.30%, median = 0.06%, confirming constellation stability. Random Forest (RF) and imbalanced RF (IRF) classifiers trained on augmented DD payloads achieve Precision = 0.94, Recall = 0.87, and F1 = 0.92. Results validate OTFS-ISAC as a robust framework for V2B communication and sensing. Full article

Plant electrical signals are closely related to light conditions, and changes in light intensity lead to variations in the amplitude, frequency, and other characteristics of plant electrical signals. Therefore, real-time analysis of the relationship between plant electrical signals and light factors is crucial for monitoring plant growth status. In this study, Aloe Vera was chosen as the experimental subject, and electrical signal data were collected under different light intensities, followed by preprocessing including wavelet threshold denoising. Furthermore, a hybrid model architecture combining one-dimensional convolutional neural networks (1D-CNNs) and lightweight gated recurrent units (GRUs) was proposed to address the temporal signal characteristics of plant electrical signals and edge computing requirements. The 1D-CNN module extracts local spatial features, which are then modeled in time by the optimized GRU module with channel pruning. Model compression was achieved through parameter quantization. Finally, the computational and storage modules of the model were deployed on an FPGA development board using hardware description language for simulation verification. The results indicate that the system achieved a classification accuracy of 90.1%, a detection time of 43.2 ms, and a power consumption of 4.95 W, demonstrating the comprehensive advantages in terms of accuracy, response speed, and power consumption. This approach effectively improves data processing speed and reduces system power consumption while maintaining high classification accuracy, thereby providing technical support for the development of plant growth monitoring technologies. Full article

This paper focuses on the vibration analysis of a prototype helicopter rotor test stand, with particular attention to the dynamic response of its electric propulsion system. The stand is driven by an induction motor and equipped with composite rotor blades of various geometries, including blades with shape memory alloy (SMA)-based torsion actuators for angle of attack (AoA) adjustment. These variable geometries significantly influence the system’s dynamic behavior, where resonance phenomena may pose risks to structural integrity. The objective was to investigate how selected operational parameters specifically motor speed and AoA affect the vibration response of the propulsion system. Structural vibrations were measured using a tri-axial piezoelectric accelerometer system integrated with calibrated signal conditioning and high-resolution data acquisition modules. This setup enabled precise, time-synchronized recording of dynamic responses along all three axes. Fast Fourier Transform (FFT) and Power Spectral Density (PSD) methods were applied to identify dominant frequency components, including those associated with rotor harmonics and SMA activation. The highest vibration amplitudes were observed at an AoA of 16°, but all results remained within the vibration limits defined by MIL-STD-810H for rotorcraft drive systems. The study confirms the importance of sensor-based diagnostics in evaluating electromechanical propulsion systems operating under dynamic loading conditions. Full article

With increasingly scarce spectrum resources, frequency-domain signal overlap interference has become a critical issue, making multi-user modulation classification (MUMC) a significant challenge in wireless communications. Unlike single-user modulation classification (SUMC), MUMC suffers from feature degradation caused by signal aliasing, feature redundancy, and low inter-class discriminability. To address these challenges, this paper proposes a collaborative “separation–recognition” framework. The framework begins by separating overlapping signals via a band partitioning and FastICA module to alleviate feature degradation. For the recognition phase, we design a dual-branch network: one branch extracts prior knowledge features, including amplitude, phase, and frequency, from the I/Q sequence and models their temporal dependencies using a bidirectional LSTM; the other branch learns deep hierarchical representations directly from the raw signal through multi-scale convolutional layers. The features from both branches are then adaptively fused using a gated fusion module. Experimental results show that the proposed method achieves superior performance over several baseline models across various signal conditions, validating the efficacy of the dual-branch architecture and the overall framework. Full article