Inverse Fast Fourier Research Articles

Simplified ICF and smart MIR for PAPR reduction in OFDM systems

One of the biggest problems for orthogonal frequency division multiplexing (OFDM) systems is the high peak-to-average power ratio (PAPR), which breaks the orthogonality among subcarriers and leads to the nonlinear distortion of transmitted signals after being processed by the power amplifier (PA). The iterative clipping and filtering (ICF) method is one of the well known and applied existing PAPR reduction techniques at the transmitter and the modified iterative receiver (MIR) is an effective existing method for signal recovery with the ICF method in its iterative process at the receiver. However, the ICF method, as well as the MIR, suffers from the high computational complexity due to the oversampling and high-order inverse fast Fourier transform/fast Fourier transform (IFFT/FFT) operators. Besides, the performance of MIR is limited by the number of iterations. In this paper, to reduce the computational complexity of ICF method, the phase rotation iterative clipping and filtering (PRICF) method is proposed, which performs padding, phase rotation and low-order IFFT/FFT operators. Meanwhile, the computational complexity of MIR is also reduced because the ICF method is replaced by the PRICF method in its iterative process. Furthermore, to accelerate the iteration or improve the performance, the modified iterative network receiver (MIR-Net) is proposed by introducing trainable parameters based on the method of model-driven deep learning. Comparing with the combination of ICF and MIR, the simulation results demonstrate the advantages of our proposed methods, which is the combination of PRICF and MIR-Net, in terms of the computational complexity and performance.

Low hardware-complexity IQ skew tolerant finite field and time domain hybrid adaptive equalization for 400G/800G-ZR coherent transmission

In 400G/800G-ZR transmission systems afflicted by substantial inter-symbol interference (ISI) stemming from chromatic dispersion (CD), frequency-domain adaptive equalizers (FD-AEQs) are preferred to time-domain AEQs (TD-AEQs) as the former have relatively lower computation load. However, the reliance of FD-AEQs on computationally expensive fast Fourier transform (FFT)/inverse fast Fourier transform (IFFT) operations poses a major obstacle in the development of low-power 400G/800G-ZR digital coherent transceivers. Furthermore, to mitigate the significant performance degradation due to receiver in-phase and quadrature (IQ) skew, the employment of twice the number of filters becomes imperative to enable individual adjustments of the I and Q tributaries, nearly doubling the number of necessary FFT/IFFT operations and computation load. This prohibitively high computation load poses a formidable obstacle to the realization of low-power and cost-effective transceivers. To address this issue, we introduce a novel low hardware-complexity IQ skew tolerant finite field (FF) and TD hybrid AEQ for 400G/800G-ZR coherent transmission. By optimizing the AEQ design and the Fermat number transform (FNT) based linear convolution scheme, the proposed hybrid AEQ can achieve a remarkable reduction in hardware complexity by more than 70%, compared with the existing IQ skew tolerant FD-AEQ, while preserving the same receiver sensitivity. Both numerical simulations and experiments demonstrate that the performance of the low complexity hybrid AEQ is the same as the FD-AEQ with much higher complexity. The proposed comprehensive and hardware efficient hybrid AEQ scheme is very appealing for 400G/800G-ZR coherent receivers which need to compensate for large ISI and IQ skew under stringent power constraints.

Signal Fusion of Multi-Frequency Continuous Wave Ground Penetrating Radar

Abstract Carrier-less pulse radar, with its short pulse duration, low average power, and weak anti-interference capability, poses significant limitations to the application of ground penetrating radar (GPR). Fusing continuous wave signals from multiple frequency components forms the basis for the design and data interpretation of continuous wave radar. We firstly introduce two fusion methods: the application of the Inverse Fast Fourier Transform (IFFT) to multi-frequency signals and direct superposition. And we demonstrate these methods by synthesizing three basic sinusoidal signals and analyse their time-frequency relationship. Furthermore, we perform Fast Fourier Transform (FFT) on the transmit waveform of pulse radar to obtain a set of frequency components. By superimposing three sets of frequency components with different numbers of frequency points, we obtain the fused waveform and compare it with the original Ricker wavelet. The results show that while reducing the number of frequency points may increase the error in the synthesized signal slightly, it remains capable of accurately synthesizing the Ricker wavelet. However, this reduction also decreases the time window of the synthesized signal and may result in temporal overlapping. These findings offer insights into selecting parameters for frequency components in multi-frequency continuous wave radar and lay a foundation for signal fusion in such radar systems.

An Automated Sparse Channel Estimation Framework for MU‐MIMO‐OFDM System With Adaptive Extreme Learning and Heuristic Mechanism

ABSTRACTCompressed sensing is used for channel estimation in Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing (MIMO‐OFDM) systems, but large‐scale networks face challenges regarding the antenna elements and spatial non‐stationarities. To enhance spectral efficiency in Multi User‐MIMO (MU‐MIMO) systems, essential signals are collected by Quadrature Phase Shift Keying (QPSK) in the transformer phase. Further, the modulated signals are provided to the “Pulse Shaping Algorithm (PSA)” for neglecting the inter‐symbol interference rate along with inter‐carrier interference. Subsequently, in the transmitter phase, the “Inverse Fast Fourier Transforms (IFFT)” technique is performed to map the symbols and then provide the signal to the receiver side. The spare channel is validated using a semi‐blind sparse algorithm, with parameters tuned using the Opposition Mud Ring Algorithm (OMRA). Then, the estimated sparse channel values are used for generating the new data, and the Adaptive Extreme Learning Model (AELM) is trained to predict the spare channel outcome. The main objective is to reduce the Minimum Mean Square Error (MMSE) in the channel. Thus, the spare channel outcome is predicted automatically using the AELM. Then, diverse evaluations are executed in the suggested spare channel estimation approach over the different mechanisms to observe their effectualness rate.

Oxidation behavior of β-Nb formed in Zr-1Nb under neutron irradiation in PWR conditions

This work focuses on neutron irradiated Zr-1Nb alloy, using High Resolution Transmission Electron Microscopy (HRTEM) to investigate the oxidation behavior of β-Nb at different distances from the Oxide /Metal (O/M) interface within the oxide film. Results show that β-Nb was initially oxidized to T-NbO2 at 0 nm at O/M interface, then into a complex morphology of T-NbO2, M-Nb2O5, and O-Nb2O5 within 600 nm. Finally, it was completely oxidized to M-Nb2O5 within 800 nm. β-Nb in this study did not exhibit amorphous morphology within observed distances. In addition, Inverse Fast Fourier Transformation (IFFT) and Weak Beam Dark Field (WBDF) techniques are employed to characterize the dislocation density and distribution in the oxide film, results indicate that the distribution of dislocations generated by neutron irradiation in the oxide film is relatively uniform and neutron irradiation is not the primary reason affecting the oxidation behavior of β-Nb.

A tail probability density distribution model of stress amplitude under band-limited stochastic vibration loadings

Resonance of engineering structures under stochastic vibration loadings is a primary cause of fatigue failure. Considering that cyclic loadings below the fatigue limit of the material contribute little to fatigue damage, the portion of the stress amplitude distribution that exceeds the fatigue limit is in focus in this paper, and a tail probability density distribution model of stress amplitude under band-limited stochastic vibration loadings is proposed. First, the response stress power spectral density functions under band-limited loadings are simulated by using the normal distribution and the Weibull distribution, respectively, and then the frequency domain signals are converted into time domain signals by adopting the inverse fast Fourier transform method. A two-parameter Weibull model of tail probability density distribution of stress amplitude is proposed, and the relationship between model parameters and power spectral moment parameters is given. Finally, the comparative analysis of the model accuracy and the vibration fatigue test of aluminum alloy notch specimen are carried out. It is demonstrated that the fatigue life predicted by the presented model is highly coincident with the results of tests and the time domain method.

Extraction of Iris Characteristics Using a Combination Transform for Biometric Any individual Identification

The iris of the eye is used as an identifying and affirmative biometric in many vital applications such as banking and airports.And iris identification is one of the most reliable and accurate biometric identification systems available due to its stability and lack of sensitivity to longevity. In this article, authorized standard processes such as iris segmentation, normalization, and feature extraction were utilized to examine the iris of the eye. The circular hough transform is used for iris segmentation, while the daughman rubber-sheet model is used for iris picture normalization. Using a combination transform consisting of four consecutive transforms, feature encoding was employed to restore the most distinguishing aspects of irises. The 2-D fast fourier transform (FFT), radon transform, 1-D inverse fast fourier transform (IFFT), and 1-D discrete multi-wavelet transform are all examples of transforms. For pattern clustering, the kohonen self-organizing feature map (SOFM) was employe to the group that distinguished information vectors of the iris image features extracted using the combination transforms in order to visualize the close proximity of comparable irises features and scatter dissimilar ones. The matching process is carried out between test iris images and target iris photos of 224 people from the IITD database, with the similarity measured using the euclidian distance metric A part investigates the change of the parameters: FRR, FAR, TSR) of different collections of the PID and POD with the threshold levels (90:10,80:20,70:30,60:40,50:50) that resulted EER for the various thresholds are 0.070,0.070,0.080,0.090 and 0.095 respectively. The suggested approach yielded a TSR of 98% when compared to conventional methods.

SARDIMM: High-Speed Near-Memory Processing Architecture for Synthetic Aperture Radar Imaging

The range-Doppler algorithm (RDA), a key technique for generating synthetic aperture radar (SAR) images, offers high-resolution images but requires significant memory resources and involves complex signal processing. Moreover, the multitude of fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT) operations in RDA necessitates high bandwidth and lacks data reuse, leading to bottlenecks. This paper introduces a synthetic aperture radar dual in-line memory module (SARDIMM), which executes RDA operations near memory via near-memory processing (NMP), thereby effectively reducing memory accesses, execution time, and energy consumption. The embedded NMP module in SARDIMM optionally supports a combination of FFT, IFFT, and matched filter operations of the RDA for range and azimuth compression. The operator within the NMP module accelerates the FFT by performing two radix-2 single butterfly operations in parallel. The NMP module was implemented and validated on a Xilinx UltraScale+ field-programmable gate array (FPGA) using Verilog-HDL. The acceleration performance of RDA for images of various sizes was evaluated through a simulator modified with gem5 and DRAMSim3 and achieved a 6.34–6.93× speedup and 41.9–48.2% energy savings.

Enhanced 4D-OFDM optical communication systems with color-coded constellations and probability constellation shaping.

The present work introduces a four-dimensional probability constellation mapping OFDM optical transmission system based on a two-dimensional inverse fast Fourier transform (2D-IFFT). A four-dimensional constellation structure employing color coding is designed, amalgamating geometric shaping with probability shaping to enhance the constellation figure of merit (CFM). Successful transmission of OFDM signals at 51.49 Gb/s is achieved over a 2 km seven-core optical fiber, validating the performance of the proposed constellation diagram. Under the conditions of multicore multiplexing and a bit error rate of 3.8 × 10-3, the receiver sensitivity of the OFDM signals mapped with the proposed color-coded four-dimensional constellation exhibits gains of 0.8 dB, 1.33 dB, and 1.83 dB compared to traditional four-dimensional constellations, 3D-OFDM, and 2D-OFDM modulation, respectively. Furthermore, under an entropy value of 4.4 bits/symbol, a receiver sensitivity gain of 1.36 dB is attained compared to a uniform distribution constellation, indicating the favorable error performance of this scheme with promising prospects for short-distance communication in the future.

Defect-Rich CuZn Nanoparticles for Model Catalysis Produced by Femtosecond Laser Ablation.

Femtosecond laser ablation of Cu0.70Zn0.30 targets in ethanol led to the formation of periodic surface nanostructures and crystalline CuZn alloy nanoparticles with defects, low-coordinated surface sites, and, controlled by the applied laser fluence, different sizes and elemental composition. The Cu/Zn ratio of the nanoparticles was determined by energy dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and selected area electron diffraction. The CuZn nanoparticles were about 2-3 nm in size, and Cu-rich, varying between 70 and 95%. Increasing the laser fluence from 1.6 to 3.2 J cm-2 yielded larger particles, more stacking fault defects, and repeated nanotwinning, as evident from high-resolution transmission electron microscopy, aided by (inverse) fast Fourier transform analysis. This is due to the higher plasma temperature, leading to increased random collisions/diffusion of primary nanoparticles and their incomplete ordering due to immediate solidification typical of ultrashort pulses. The femtosecond laser-synthesized often nanotwinned CuZn nanoparticles were supported on highly oriented pyrolytic graphite and applied for ethylene hydrogenation, demonstrating their promising potential as model catalysts. Nanoparticles produced at 3.2 J cm-2 exhibited lower catalytic activity than those made at 2.7 J cm-2. Presumably, agglomeration/aggregation of especially 2-3 nm sized nanoparticles, as observed by postreaction analysis, resulted in a decrease in the surface area to volume ratio and thus in the number of low-coordinated active sites.

Reliable communication based on energy spreading transform and iterative detection in MIMO‐OFDM systems

AbstractThe challenge of ensuring reliability for high‐efficiency technology, multiple‐input‐multiple‐output orthogonal‐frequency‐division‐multiplexing (MIMO‐OFDM), in wireless frequency‐selective fading environments persists. In this article, the concept of spreading a symbol's energy is proposed as a viable solution to enhance transmission reliability for MIMO‐OFDM systems. And an energy‐spreading‐transform (EST)‐based MIMO‐OFDM transceiver is developed. Following the Inverse Fast Fourier Transform (IFFT) performed by the conventional MIMO‐OFDM transmitter, an orthogonal transformation called the EST is introduced. This transform spreads the energy of a symbol across the entire frequency domain and all time slots. The EST is coupled with the improved iterative detection algorithm named EST‐partial decision (PD)‐iterative‐interference‐cancellation (EST‐PD‐IIC) to maximize and leverage the potential diversity gain. Numerical simulation results demonstrate that the proposed scheme approaches the performance bound when signal‐to‐noise ratio (SNR) is about 21dB for 16‐ary quadrature amplitude modulation (16‐QAM). Complexity analysis illustrates that the computational complexity of the evolved EST‐PD‐IIC algorithm is lower than that of the famous vertically Bell laboratory layered space‐time detector (V‐BLAST) when the antenna array size is greater than . In summary, the proposed scheme is practical for providing high‐quality communication in multi‐path fading environments and can even enable a reliable communication without channel encoding when Eb/N0 exceeds a threshold in 5G‐Advanced.

Peak-to-average power ratio minimization and complexity reduction in MIMO-OFDM systems using spatial circular shifting and temporal interleaving method

Multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) technological support for the simultaneous and frequent access by a large number of users to radio resources. For 5G cellular systems, this exhaust is not enough to provide physical layer services. An appropriate Peak-to-average power ratio (PAPR) minimization principle, which maximizes data capacity and channel utility, has been used to address this issue. In this paper, mainly focus on minimize the high PAPR of the candidate sequence of the OFDM sub-block using modified enhancement asymmetric arithmetic coding scheme (M-EAAC). According to this, circular shifting of the candidate sequence is established in the spatial circular shifting and temporal interleaving (SCS-TI) form to generated different set of conjugated phases which is multiplied with candidate sequence. Then, the transmitting antenna is identified the best lowest PAPR of the candidate sequence is chosen for entire OFDM data transmission. The simulation results conveys that the proposed SCS-TI method provide acceptable improvement in the PAPR reduction as compared with conventional selective mapping(SLM)and pseudo-random SLM(PR-SLM). Moreover, the complexity evaluation which ensure the proposed method provides better improvement at three important stages includes inverse fast Fourier transform (IFFT) operation, optimization process, and PAPR calculation at each candidate sequence.

Implementing intelligent‐based sparse channel estimation in Multi User‐Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing system with hybridized optimization algorithm

SummaryThe channel plays a significant role as the multipath in Multiple Input Multiple Output‐Orthogonal Frequency Division Multiplexing (MIMO‐OFDM) systems. The precoding‐based channel estimation algorithms estimate the channel capacity at the receiver node and they provide efficient channel estimates under worst case channel scenarios. To estimate the channel capacity in the mobile node, semi‐blind scenario is a crucial task in Multi User (MU) MIMO systems. Therefore, a semi blind sparse channel estimation algorithm is demonstrated in the MU‐MIMO system to provide better performance. In the transmitter side, the signal modulation is performed with the help of Quadrature Phase Shift Keying (QPSK), and the modulated signal is given to Pulse Shaping Algorithm (PSA) to reduce the inter‐carrier interference as well as inter symbol interference. At each transmitter, the Inverse Fast Fourier Transforms (IFFT) technique is used for mapping the symbols and then the mapped signal is send to the receiver. In the receiver side, the FFT, pulse reshaping, and QPSK demodulation blocks are serially connected and perform inverse operations of the transmitter in the receiver. Then, the sparse channel is estimated at the receiver by using the semi blind sparse algorithm, where the parameters are optimized by using the Hybridized Drosophila with Virus Colony Search Optimization (HD‐VCSO). The objective function of the developed sparse channel estimation is the reduction of Minimum Mean Square Error (MMSE) in the channel. The performance of the developed sparse channel estimation algorithm is analyzed through different conventional algorithms to validate the effectiveness of the proposed algorithm.

Energy-Based Design of Buckling-Restrained Steel Braced Frames for Concurrent Occurrences of Earthquake and Wind

This paper describes the development of a dual hazard spectrum for use in the dynamic analysis of steel frames subject to the combined effects of earthquakes and wind. The proposed spectrum is obtained by combining the power spectra of earthquakes and wind using the square root of the sum of squares (SRSS) combination method. An equivalent time excitation function is then computed using an inverse fast Fourier transform (IFFT) and serves as input for the dynamic analysis. Using time-history analysis on the OpenSees platform, the dynamic responses expressed in terms of peak and residual inter-story and roof drifts for two multistory steel frames located in two US cities (Los Angeles and Charleston) are obtained to demonstrate that designing these buildings based on just one hazard may not be adequate. For frames that are considered under-designed, an energy-based design procedure that uses buckling-restrained braces (BRBs) to dissipate the excess energy imparted to these frames is proposed so they will satisfy the FEMA 356 recommended drift limits for the performance levels of immediate occupancy and life safety.

Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Domain Learning

This research addresses the challenge of developing a universal deepfake detector that can effectively identify unseen deepfake images despite limited training data. Existing frequency-based paradigms have relied on frequency-level artifacts introduced during the up-sampling in GAN pipelines to detect forgeries. However, the rapid advancements in synthesis technology have led to specific artifacts for each generation model. Consequently, these detectors have exhibited a lack of proficiency in learning the frequency domain and tend to overfit to the artifacts present in the training data, leading to suboptimal performance on unseen sources. To address this issue, we introduce a novel frequency-aware approach called FreqNet, centered around frequency domain learning, specifically designed to enhance the generalizability of deepfake detectors. Our method forces the detector to continuously focus on high-frequency information, exploiting high-frequency representation of features across spatial and channel dimensions. Additionally, we incorporate a straightforward frequency domain learning module to learn source-agnostic features. It involves convolutional layers applied to both the phase spectrum and amplitude spectrum between the Fast Fourier Transform (FFT) and Inverse Fast Fourier Transform (iFFT). Extensive experimentation involving 17 GANs demonstrates the effectiveness of our proposed method, showcasing state-of-the-art performance (+9.8\%) while requiring fewer parameters. The code is available at https://github.com/chuangchuangtan/FreqNet-DeepfakeDetection.

Enhancing spectral efficiency with low complexity filtered‐orthogonal frequency division multiplexing in visible light communication system

AbstractThe filtered‐orthogonal frequency division multiplexing (F‐OFDM) scheme has gained attention as a promising solution in the field of visible light communication (VLC) systems. One crucial aspect in VLC is the conversion of the complex F‐OFDM signal into a real signal that corresponds with direct detection and intensity modulation. Traditionally, achieving a real F‐OFDM signal has involved imposing Hermitian symmetry (HS) on the samples of the Inverse Fast Fourier transform (IFFT), which requires 2N‐point IFFT and obtains an N‐point FFT, thus adding complexity. In this study, a novel approach is presented and implemented, aiming to enhance spectral efficiency and reduce system complexity by generating a real F‐OFDM signal without relying on HS. This approach is then compared with HS‐free (HSF)‐OFDM, direct current biased optical OFDM, and asymmetrically clipped optical OFDM. The suggested method offers a remarkable improvement of ~50% in the required IFFT/FFT volume. Consequently, this method reduces hardware complexity and power usage compared with the traditional F‐OFDM method. Moreover, regarding error rates, the proposed method demonstrates better spectral efficiency than HSF‐OFDM.

Noise-Canceling Channel Estimation Schemes Based on the CIR Length Estimation for IEEE 802.11p/OFDM Systems

This paper investigates methods for noise-canceling channel estimation (NC-CE) to track rapid time-varying channels in IEEE 802.11p/orthogonal frequency division multiplexing (OFDM) systems. To this end, we introduce a novel three-step channel estimation technique based on the estimated length of the channel impulse response (CIR). This approach aims to surpass the performance of conventional designs that rely on constructed data pilots (CDPs). In the first step, we not only eliminate noise components but also estimate the channel frequency responses (CFRs) of virtual subcarriers for long preamble parts. Moving on to the second step, we incorporate a modified CDP method without a frequency-domain reliability test and interpolation, taking into account the CFRs of virtual subcarriers obtained at the previous OFDM symbol time. The final step can be implemented as the operation of the inverse fast Fourier transform (IFFT)/nulling/FFT to reduce noise components from the CFRs obtained in the second step and generate CFRs for virtual subcarriers to be used in the next symbol time. The results of our simulations validate the effectiveness of our proposed channel estimation schemes.

Gas in scattering media absorption spectroscopy for time-resolved characterization of gas diffusion processes in porous materials

Signal denoising is a serious problem for in-situ laser diagnostics of gases dispersed in porous materials. An optical sensor system based on absorption spectroscopy of gases in a scattering environment was built using a 3D printed cell with reference samples of polystyrene foam. Selected A-band spectral lines of molecular oxygen were investigated using wavelength modulated spectroscopy with second harmonic detection. Quantitative information on the concentration of analyte dispersed in the porous medium was obtained at extremely low signal-to-noise ratio (SNR < 10). A spectral line shape fitting procedure based on the Gabor transform followed by a filtered inverse fast Fourier transform allowed to achieve a relatively high SNR with good linearity over a range of reduced oxygen concentrations in air. Finally, the applicability of the optical sensor system to monitor the diffusion of carbon dioxide into air dispersed in a Styrofoam sample and vice versa was successfully demonstrated.

Highly sensitive magnetic field sensor using magnetic fluid filled dual-core photonic crystal fiber

A high sensitivity fiber optic magnetic field sensor that utilizes a dual-core photonic crystal fiber (DC-PCF) filled with magnetic fluid (MF) has been proposed and validated to simultaneously detect magnetic field intensity and temperature. DC-PCF is a multimode fiber that supports various modes of light transmission and induces intermodal interference within fiber core. The numerical analysis of the mode characteristics of DC-PCF is conducted. The sensing structure relies on the use of a DC-PCF with air holes filled with a suitable material, such as MF substance. The analysis of the working principle of the DC-PCF for sensing and measurement is conducted by considering its structural characteristics and mode characteristics. The effective refractive index (ERI) of MF is affected by external magnetic field intensity and temperature. To extract the effective frequency points, the fast Fourier transform (FFT) method can be employed. Additionally, the inverse fast Fourier transform (IFFT) method can be utilized to determine the magnetic field sensitivity, which can reach up to 1.562 nm/mT. Furthermore, the temperature sensitivity can be as high as −1.043 nm/°C. The sensor demonstrates excellent repeatability and showcases low detection limits of 0.0128 mT and 0.0192 °C, respectively. Additionally, the proposed sensor exhibits substantial potential for further development in the field of high sensitivity magnetic field detection applications.

Waveform shaping in photonic time-crystals

This paper reports on the waveform shaped by a finite duration photonic time-crystal with its permittivity and permeability periodically varying in time. A Gaussian-modulated sinusoidal pulse is incident onto this photonic time-crystal to evaluate the backward- and forward-scattering waveforms. An analytical formulation, utilizing a cascade of temporal transfer matrices and the inverse fast Fourier transform, was employed to conduct time-domain waveform computations. Interestingly, the dispersion diagram of the temporal unit cell, which displays a momentum gap characterized by a complex effective angular frequency, plays a crucial role in shaping the incident waveform. Specifically, the presence of momentum gaps in the spectrum of the incident pulse determines the frequencies of the generated oscillation modes.