Search Results (231)

We demonstrate an 80 MHz, 350 mW, 120 fs, 770 nm femtosecond laser based on a nonlinear compressed 1540 nm femtosecond fiber laser. The home-built 1540 nm fiber laser, delivering 80 MHz, 2.69 W, 269 fs laser pulses, was realized by employing spectral pre-modulation and pre-chirp management inside an Er/Yb co-doped fiber power amplifier. The subsequent nonlinear fiber pulse compression stage was utilized to further nonlinearly compress the pulse duration to 128 fs based on the Gaussian assumption. Detailed numerical simulation was also implemented to investigate the optical dynamics of the nonlinear compression process. Finally, a 0.5 mm thick fan-out periodically poled lithium niobate (PPLN) crystal was utilized to generate the frequency-doubled, 350 mW, 770 nm laser pulses with a 120 fs pulse duration based on the Gaussian assumption. Full article

A low-latency, low-complexity digital demodulator is presented for chirp spread spectrum (CSS)-modulated RF packets targeting low-power IoT wireless systems operating in spectrally congested environments. Conventional CSS receivers rely on fast-fourier transform (FFT)-based synchronization and long preamble sequences, resulting in increased latency and computational complexity. To address these limitations, the proposed receiver employs amplitude-domain synchronization using oversampled sub-chirp windows and maximum likelihood estimation without requiring FFT processing. A digital demodulator co-designed with receiver’s fractional-N phase-locked loop (PLL) architecture enables rapid sub-chirp generation and fast frequency settling, while compensation techniques mitigate symbol boundary offset (SBO) error due to PLL non-idealities during synchronization. The proposed system achieves packet synchronization within 17.5 preamble symbol cycles while maintaining symbol boundary offset estimation error below ±1%. Simulation results demonstrate a syncword misdetection probability below 10⁻³ at SNRs of 9 dB and 1 dB without and with 8× repetition, respectively. In the presence of interferences, the receiver tolerates worst-case in-band signal-to-noise ratio (SIR) levels down to −16.2 dB while consuming 877 µW and 830 µW average power at the digital demodulator, and fractional-N PLL, respectively. Implemented in 65 nm CMOS, the proposed architecture occupies 0.195 mm² active area. Full article

High-resolution soil moisture monitoring in a lysimeter requires precise Ground-Penetrating Radar (GPR) systems that can provide clean time-domain data for a Full-Waveform Inversion (FWI) algorithm. Using high-speed Radio Frequency System-on-Module (RFSoM) devices provides flexibility in signal generation. To optimize such a system, an appropriate transmit waveform and processing pipeline need to be selected. This paper presents a performance evaluation of three GPR waveforms—impulse, Stepped-Frequency Continuous Wave (SFCW) and non-linear Frequency-Modulated Continuous Wave (FMCW/chirp)—on the same hardware setup. To ensure a fair comparison, all waveforms were tested under an identical total measurement time. Numerical simulations were performed using an electromagnetic model of the system. Physical validation was conducted in an anechoic chamber using a 4 GS/s RFSoM setup and planar elliptical dipole antennas. Simulations showed that both sinewave-based methods provide better signal-to-noise ratios (SNRs) than the impulse GPR, with the non-linear chirp achieving the best results (20.7 dB improvement compared to impulse). Experimental measurements supported these results, showing better SNR across the frequency band for the SFCW and chirp waveforms. Because of its high SNR and simple hardware implementation, the non-linear chirp was identified as the most suitable waveform for this RFSoM-based GPR system. Full article

Fiber dispersion causes pulse broadening and signal distortion. Existing dispersion compensation approaches depend on standardized dispersion parameters at specific wavelengths (e.g., 1550 nm), which often mismatch actual fiber dispersion, leading to residual dispersion. We develop a Sagnac ring interferometry and electro-optic modulation system, combined with machine learning, to accurately characterize the C-band dispersion curve of a G.652D fiber, and inversely design a chirped fiber Bragg grating (CFBG) for tailored compensation. However, when attempting to quantify the residual dispersion numerically, conventional differentiation methods yield physically implausible results. Monte Carlo simulations confirm this fundamental unreliability, yielding a 95% confidence interval of 319,605 ps/(nm·km). To circumvent this limitation, we propose a joint evaluation method based on refractive index flatness and group delay uniformity. Within 1545–1555 nm, both indicators fluctuate by no more than 0.015% relative to their means, confirming that residual dispersion has been effectively suppressed. This approach provides a precise, personalized compensation mechanism applicable to optical fibers with individual dispersion characteristics, offering a controllable path for adaptive dispersion compensation in high-speed communication systems. Full article

GNSS signals are extremely weak at the Earth’s surface and are highly vulnerable to in-band interference, particularly high-dynamic linear frequency-modulated (LFM) jamming, which may lead to receiver loss of lock. Existing anti-jamming techniques struggle to balance real-time constraints with high-precision frequency estimation. This paper proposes a Newton-iteration-enhanced three-spectral-line RIFE algorithm implemented on a heterogeneous FPGA platform (Zynq-7000 SoC). The method performs coarse frequency estimation using the three-spectral-line RIFE to mitigate FFT fence effects, followed by Newton-based quadratic refinement, enabling high estimation accuracy with reduced FFT size. A fast–slow loop architecture is adopted, where the FPGA (PL) performs real-time interference suppression and the ARM (PS) handles system control and parameter updates. Experimental results show that, under static interference, the proposed method achieves a 10.9 dB improvement over direct estimation algorithms. Under chirp interference, it significantly outperforms both direct estimation and conventional iterative methods. In GNSS closed-loop tests, the proposed approach extends the anti-jamming margin to 82 dB J/S. Overall, the proposed method effectively balances estimation accuracy and processing latency, providing a practical solution for GNSS anti-jamming in high-dynamic environments. Full article

In underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems, the orthogonality among subcarriers is highly susceptible to Doppler-induced scaling, leading to severe inter-carrier interference (ICI). This paper proposes a coarse-to-fine Doppler estimation approach for coded orthogonal frequency division multiplexing (OFDM) systems operating in underwater acoustic (UWA) channels. The proposed method first employs the fractional Fourier transform (FRFT) to obtain an initial Doppler factor estimate from a linear frequency modulation (LFM) probe, exploiting the energy concentration property of chirp signals in the fractional domain. This coarse estimate then guides a refinement stage that leverages the cyclic prefix (CP) inherent to each OFDM symbol, enabling symbol-by-symbol Doppler tracking without waiting for the entire packet. As a result, the required memory and processing latency are substantially lower than with full-packet resampling or iterative gradient-descent alternatives. Numerical simulations conducted under both time-invariant and time-variant Doppler conditions demonstrate that the proposed scheme achieves a mean squared error (MSE) below 0.5% at signal-to-noise ratios (SNR) of 5 dB and above. Moreover, the bit error rate (BER) remains within 0.2 dB of an ideal Doppler-free system at a BER of 10⁻³. The combination of low storage demand, symbol-level operation, and robust performance makes the proposed method well-suited for real-time underwater acoustic communication. Full article

Magnetic hysteresis strongly influences energy dissipation and efficiency in power magnetic components under time-varying excitation. This work proposes a compact dynamic hysteresis model using a Hammerstein structure, consisting of a closed-form arctangent static operator followed by a first-order relaxation dynamic stage. The formulation enables direct datasheet-based parameterization and avoids iterative differential solvers or distributed hysteron representations, resulting in low calibration effort and computational cost. The static hysteresis behavior is characterized using four static parameters directly identified from manufacturer B-H datasheets, while dynamic effects are captured using two global calibration parameters derived from datasheet loss curves. This formulation enables accurate reconstruction of major and minor hysteresis loops, while introducing frequency-dependent phase lag and dynamic loop opening. Model performance is evaluated under diverse excitations, including sinusoidal, amplitude-modulated, FORC and chirp signals, showing waveform deviations below 7.2% peak-to-peak NRMSE relative to classical hysteresis models. Energy-loss predictions are validated against manufacturer datasheet curves for ferrite material 3C90 across multiple frequencies, yielding a root-mean-square relative error of 8.3% with 89% of operating points within ±20% deviation. The proposed model provides a datasheet-driven framework for hysteresis and energy-loss prediction in power magnetic components. Full article

The growth of Internet of Things (IoT) applications is driving demand for Low-Power Wide-Area Networks (LPWANs) to support higher data rates with the same energy efficiency. While Long Range (LoRa) provides excellent noise immunity and receiver sensitivity, its data rate might be insufficient for some applications, including those real-time applications in which LoRa is required to have infrequent transmissions to maintain low power consumption. In this paper, a novel modulation is introduced to address these limitations by utilizing narrowband chirp to represent a data symbol with chirp slopes, called a multi-slope chirp signal. At the receiver, a new blind non-coherent detection technique is also presented to recover the proposed signal. The simulation results confirm that the proposed scheme can successfully transmit information at 2 to 4 bits per symbol, and when compared to LoRa SF 6, it reduces the Time-on-Air (ToA) by half and also achieves an improvement in spectral efficiency in the frequency domain. Full article

This paper presents a novel dual-mode memristor-based ring oscillator designed for energy-efficient, wireless biomedical signal conditioning systems. The proposed architecture leverages a compact DTMOS memristor emulator, consisting of only two transistors and one capacitor, to replace the conventional NMOS pull-down devices in a three-stage PMOS ring oscillator. This integration enables two distinct operating modes within a single compact core: a fixed-frequency mode for stable clock generation and carrier synthesis, and a programmable chirp mode for frequency-modulated signal generation. The fixed-frequency mode achieves continuous tuning from 3.142 GHz to 4.017 GHz via varactor control, with an ultra-low power consumption of only 111 µW at 4.017 GHz. The chirp mode generates linear frequency sweeps starting from 0.8 GHz, with the sweep range independently controllable through the state capacitor value and the pulse width of the control signal (SW_Chirp). Designed in a standard 0.18 µm CMOS process, the oscillator exhibits a low phase noise of −87.82 dBc/Hz at a 1 MHz offset for the three-stage configuration, improving to −94.3 dBc/Hz for the five-stage design. The overall frequency coverage spans 0.8–4.017 GHz, representing a 133.6% fractional range. The calculated figure of merit (FoM) is −169.45 dBc/Hz. Experimental validation using a discrete CD4007 prototype confirms the oscillation principle, while comprehensive simulations demonstrate robust performance across process corners and temperature variations. With its zero-static-power memristor core, wide tunability, and dual-mode reconfigurability, the proposed oscillator is ideally suited for multi-standard wireless biomedical applications, including implantable telemetry, neural stimulation, ultra-wideband (UWB) transmitters, and non-contact vital sign monitoring. Full article

The fractional Fourier transform (FRFT) serves as an effective tool for linear frequency modulated (LFM) signal parameter estimation, whose performance depends on the search efficiency for the optimal transform order. To address the issues of fixed inertia weight in the standard particle swarm optimization (PSO) algorithm, which tends to fall into local optima and suffers from insufficient convergence accuracy, this paper introduces a proportional-integral-derivative (PID) control strategy and proposes a PID-PSO-FRFT-based LFM signal parameter estimation method. This approach introduces a PID controller, which takes the deviation between the particle’s current position and the global best position as input and dynamically adjusts the inertia weight through proportional, integral, and derivative regulation, thereby achieving an adaptive balance between global exploration and local exploitation capabilities of the particles. Simulation results demonstrate that, compared with the basic PSO-FRFT algorithm, the proposed method significantly improves the estimation accuracy of the center frequency and chirp rate of LFM signals under SNR conditions ranging from −9 dB to −7 dB, while considerably reducing computation time, exhibiting superior noise resistance, and exhibiting superior robustness. Full article

We report the generation of sub-50 fs mid-infrared (MIR) pulses using a fiber-integrated system comprising a several-centimeters-long chalcogenide (As₂S₃) fiber and a fluoride (ZBLAN) fiber. Initially, 127 fs pulses at 2.8 µm are generated via the soliton self-frequency shift in the fluoride fiber. These pulses are then coupled into the As₂S₃ fiber, which provides substantial normal dispersion at this wavelength, enabling temporal stretching to achieve pulse durations of 1.02 ps (8 cm), 2.06 ps (15 cm), and 4.45 ps (24 cm), corresponding to a maximum stretch factor of approximately 35. Simultaneously, the pulses undergo significant spectral broadening via self-phase modulation during this process. Subsequent nonlinear compression within an optimized ZBLAN fiber yields compressed pulses as short as 46 fs, representing a compression ratio of approximately 63%. This work represents, for the first time, picosecond stretching and sub-50 fs nonlinear compression in a fiber-integrated architecture at 2.8 μm, establishing a critical component for future all-fiber MIR-chirped pulse amplification systems. Full article

Frequency-modulated continuous-wave (FMCW) radars are widely used for range and velocity estimation. However, conventional velocity measurement techniques based on 2D-FFT processing require a large number of chirps and suffer from a maximum unambiguous velocity limitation, which restricts their applicability to high-speed targets. This study addresses these challenges by proposing a hybrid FMCW chirp waveform that employs bandwidth variation between consecutive chirps while maintaining a constant chirp duration. The proposed method enables separation of range- and Doppler-dependent frequency components using only two chirps; thus, it improves the maximum velocity constraint by keeping intermediate-frequency bandwidth and sampling requirements low. In addition, spatial angle estimation is performed using an amplitude-comparison monopulse antenna configuration, allowing single-snapshot angle measurement with low computational complexity. To enhance measurement robustness, extended and unscented Kalman filters are integrated for target tracking. Simulation results demonstrate that the proposed waveform achieves accurate velocity estimation for very high-speed targets and that the unscented Kalman filter consistently outperforms the extended Kalman filter in terms of convergence speed and robustness, particularly under poor initialization and strong nonlinearities. The results confirm that the proposed framework provides an efficient solution for tracking a single, fast-moving, isolated target in a homogeneous environment using FMCW radar systems at short and medium ranges. Full article

This paper proposes a distributed vibration sensing system based on dual-chirped pulses and weak fiber Bragg gratings. Compared with conventional dual-pulse heterodyne detection techniques, the proposed approach utilizes the time-frequency characteristics of chirp signals, effectively relaxing the stringent requirements on the signal pulse width. In addition, when chirp signals with different chirp rates are adopted, frequency-division multiplexing technology can be realized to enhance the system’s response bandwidth. Last but not least, the sensing probe signal is generated in the optical domain using microwave photonic technology, which theoretically helps alleviate the dependence on arbitrary waveform generators. A simulation study on the system was conducted. Using a chirp signal of 200 MHz/μs and with a grating spacing of 50 m, the desired vibration signal is phased modulated onto a beat signal with a frequency of 100 MHz, and the allowable pulse width can be up to 500 ns. To verify frequency-division multiplexing capability further, an additional pair of chirped pulses with a chirp rate of 400 MHz/μs was introduced into the system, which was generated by frequency multiplication. The results demonstrate that the system response bandwidth is increased to twice the original bandwidth. The proposed scheme provides a new solution for performance enhancement in a distributed fiber optic vibration sensing system. Full article

Integrating Joint Source–Channel Coding (JSCC) with the LoRa Chirp Spread Spectrum (CSS) physical layer (PHY) presents a significant challenge due to the complexity of joint optimization, which remains underexplored despite the known advantages of JSCC. Traditional LoRa systems rely on decoupled source and channel coding, resulting in redundant overhead and limited adaptability under dynamic Wireless Body Area Network (WBAN) conditions. To address these limitations, we propose a novel LoRa–JSCC framework: a fully learned, end-to-end differentiable architecture that jointly optimizes source compression and channel redundancy. The proposed system integrates a Denoising Autoencoder (DAE) for non-linear source compression with learned neural channel encoder and decoder modules, trained via backpropagation to minimize reconstruction distortion under noisy channel conditions. Rigorous Monte Carlo simulations conducted under unified and reproducible channel conditions demonstrate consistent performance improvements across LoRa configurations. The proposed approach achieves an average 25–30% improvement in goodput across moderate-to-high SNR regimes, with gains exceeding 100% under noise-limited conditions. It further reduces Time on Air (ToA) by approximately 30–35%, enhancing spectral efficiency and lowering effective energy cost per delivered bit. In the transitional Bit Error Rate (BER) region, the proposed LoRa–JSCC framework exhibits an effective SNR gain of approximately 18–20 dB relative to conventional LoRa, corresponding to multiple orders-of-magnitude reduction in BER. These results indicate substantial improvements in reliability, coverage robustness, and energy efficiency for WBAN and IoT deployments. Full article

With the evolution of smart grids, power communication networks are increasingly required to support high-bandwidth and diversified services such as high-definition video, real-time control, and positioning—services that impose dual challenges of communication capacity and spectrum constraints—under severe resource limitations. Conventional orthogonal modulation schemes exhibit significant limitations in spectral efficiency and concurrent access capabilities, particularly in supporting high-density user environments. To address this, we propose a communication system based on non-orthogonal overlapped chirp modulation, in which the intrinsic symmetry properties of chirp waveforms are utilized to enhance system design and performance. We first construct the system architecture with a multi-symbol concurrent transmission scheme and introduce continuous orthogonal phase modulation to improve symbol distinguishability and mitigate inter-symbol interference—an approach that effectively harnesses signal symmetry for interference suppression. At the receiver, a low-complexity demodulation algorithm based on correlation matrix computation is developed, further improved through oversampling techniques that exploit temporal and spectral symmetry in signal design. Monte Carlo simulations confirm that the proposed system outperforms traditional orthogonal chirp and orthogonal frequency division multiplexing systems in bit error rate performance and spectral efficiency across varying signal-to-noise ratios and modulation schemes. The proposed NOOC system achieves spectral efficiency scaling linearly with concurrency level K, reaching up to 16 bits/s/Hz for K = 16 with BPSK, compared to 1 bit/s/Hz in orthogonal systems. The study provides both a theoretical foundation and practical insights for developing symmetry-aware, efficient, and reliable air interface technologies suitable for future power-private networks. Full article