Frequency Offsets Research Articles

A Low Spur 5.9-GHz CMOS Frequency Synthesizer with Loop Sampling Filter for C-V2X Applications

In this paper, a very low spur 5.9-GHz integer-N frequency synthesizer designed for a Cellular Vehicle-to-Everything (C-V2X) receiver is presented. The PLL is referenced to a 10-MHz crystal oscillator and the design is implemented in a 65-nm CMOS process. The output of the synthesizer has differential quadrature topology and provides the local oscillator signal to a downconverter mixer of C-V2X receiver. Post-layout simulations show that the reference spurs are better than −88[Formula: see text]dBc through loop sampling technique which was implemented in a 11.8-GHz VCO design for the first time to the best of our knowledge. The best spur level without the loop sampling technique applied is limited to −55[Formula: see text]dBc. Using the loop sampling technique provides a spur reduction of 33[Formula: see text]dB which is a significant improvement at this frequency. Based on post-layout simulations, the design has a phase noise of −97/−99/−114[Formula: see text]dBc for 10[Formula: see text]kHz/100[Formula: see text]kHz/1[Formula: see text]MHz frequency offsets, respectively, which presents competitive numbers with the designs in the literature. The design has 1.2-V nominal supply voltage for the analog and digital blocks. The total power dissipation of the synthesizer core is 6[Formula: see text]mW from a 1.2-V supply while the output buffers driving a 100-fF load consumes 18[Formula: see text]mW.

A high-temperature acoustic field measurement and analysis system for determining cavitation intensity in ultrasonically solidified metallic alloys

A high-temperature acoustic field measurement and analysis system (HTAFS) was self-designed and developed to achieve real-time acoustic field analysis and quantitative cavitation characterization within high-temperature liquids. The acoustic signal was acquired by a high-temperature resistant waveguide and calibrated by separate compensation of line and continuous spectra to eliminate frequency offsets. Moreover, a new method was proposed to derive from the continuous-spectrum sound intensity and line-spectrum sound intensity in the frequency band above 1.5 times the fundamental frequency to characterize the intensity of transient cavitation and stable cavitation. The acoustic field characteristics within solidifying liquid Al-7 %Si alloy were successfully determined by this system. With the increase of ultrasound amplitude, the acoustic pressure in the alloy melt increased to be stable, the transient cavitation intensity first rose and then declined, and the stable cavitation intensity remained unchanged. Combined with the structural evolution of the primary α(Al) phase, the transient cavitation intensity was determined to be the dominant factor for the ultrasound-induced grain refinement effect.

Synthesizing a σ̂z spin-dependent force for optical, metastable, and ground-state trapped-ion qubits

A single bichromatic field near-resonant to a qubit transition is typically used for $\hat{\sigma}_x$ or $\hat{\sigma}_y$ M{\o}lmer-S{\o}rensen type interactions in trapped ion systems. Using this field configuration, it is also possible to synthesize a $\hat{\sigma}_z$ spin-dependent force by merely adjusting the beat-note frequency. Here, we expand on previous work and present a comprehensive theoretical and experimental investigation of this scheme with a laser near-resonant to a quadrupole transition in $^{88}$Sr$^+$. Further, we characterise its robustness to optical phase and qubit frequency offsets, and demonstrate its versatility by entangling optical, metastable, and ground state qubits.

Radio fingerprinting for anomaly detection using federated learning in LoRa-enabled Industrial Internet of Things

Long Range (LoRa) communications are gaining popularity in the Industrial Internet of Things (IIoT) domain due to their large coverage and high energy efficiency. However, LoRa-enabled IIoT networks are susceptible to cyberattacks mainly due to their wide transmission window and freely operated frequency band. This has led to several categories of cyberattacks. However, existing anomaly detection systems are inefficient in detecting particularly impersonation attacks due to the dense deployment, heterogeneous IIoT devices and manufacturers involved.In this work, we introduce Hawk, a distributed anomaly detection system for detecting compromised devices in LoRa-enabled IIoT. Hawk first measures a device-type specific physical layer feature, Carrier Frequency Offset (CFO) and then leverages the CFO for fingerprinting the device, and consequently detecting anomalous deviations in the device’s CFO behavior, potentially caused by adversaries. To aggregate the device-type specific CFO behavior profile efficiently, Hawk uses federated learning, a distributed machine learning approach. To the best of our knowledge, Hawk is the first to utilise a federated learning method for anomaly-based intrusion detection in LoRa-enabled IIoT. We perform extensive experiments on a real-world dataset collected using 60 LoRa devices, primarily to assess the effectiveness of Hawk against emerging new and unknown attacks. The results show that Hawk improves the detection accuracy by more than 8% compared to the state-of-the-art solutions. Additionally, Hawk reduces the storage overhead by more than 40%, and exhibits significant robustness against cyberattack.

Efficient Space-Time Signal Processing Scheme of Frequency Synchronization and Positioning for Sensor Networks.

The orthogonal frequency division multiple access (OFDMA) technique has been widely employed in sensor networks as the data modulation scheme. This study presents a one-dimensional (1D) space-time signal processing scheme for the joint estimation of direction of arrival (DOA) and carrier frequency offsets (CFOs) in OFDMA uplink systems. The proposed approach, initiated by a one-dimensional ESPRIT algorithm, involves estimating the DOAs of the received signal to identify subscriber positions. Spatial beamformers are then used to suppress multiple access interference and separate each subscriber's signal from the received signal. The outputs of the spatial beamformer are decimated to estimate the CFO of each subscriber. Compared with conventional two-dimensional parameter estimation algorithms, the proposed one-dimensional algorithm has a higher estimation accuracy and significantly lower computational complexity.

Radar Cross Section Characterization of Frequency Diverse Array Radar

In this article, we develop a frequency diverse array (FDA) radar echo signal model for general complex targets including dumbbell and multiple scatterers. Moreover, we expose the reflectivity characterization, i.e., the radar cross section (RCS) for an FDA radar as a function of fast time, frequency offset, and angle. Note that, previously the RCS is not time dependent for the conventional radars including phased-array radar. Since statistical analysis is not, merely, enough for a fair FDA radar RCS investigations, we further derive the probability distribution function (PDF) of an FDA radar-based RCS by exploiting the statistical distribution characterization with randomly distributed scatterers. Finally, it has been proved that the PDF of an FDA radar RCS is related to both time and frequency offsets. All conclusions are validated by numerical results.

A dual-stage partially interpretable neural network for joint suppression of bSSFP banding and flow artifacts in non-phase-cycled cine imaging

PurposeTo develop a partially interpretable neural network for joint suppression of banding and flow artifacts in non-phase-cycled bSSFP cine imaging. MethodsA dual-stage neural network consisting of a voxel-identification (VI) sub-network and artifact-suppression (AS) sub-network is proposed. The VI sub-network provides identification of artifacts, which guides artifact suppression and improves interpretability. The AS sub-network reduces banding and flow artifacts. Short-axis cine images of 12 frequency offsets from 28 healthy subjects were used to train and test the dual-stage network. An additional 77 patients were retrospectively enrolled to evaluate its clinical generalizability. For healthy subjects, artifact suppression performance was analyzed by comparison with traditional phase cycling. The partial interpretability provided by the VI sub-network was analyzed via correlation analysis. Generalizability was evaluated for cine obtained with different sequence parameters and scanners. For patients, artifact suppression performance and partial interpretability of the network were qualitatively evaluated by 3 clinicians. Cardiac function before and after artifact suppression was assessed via left ventricular ejection fraction (LVEF). ResultsFor the healthy subjects, visual inspection and quantitative analysis found a considerable reduction of banding and flow artifacts by the proposed network. Compared with traditional phase cycling, the proposed network improved flow artifact scores (4.57 ± 0.23 vs 3.40 ± 0.38, P = 0.002) and overall image quality (4.33 ± 0.22 vs 3.60 ± 0.38, P = 0.002). The VI sub-network well identified the location of banding and flow artifacts in the original movie and significantly correlated with the change of signal intensities in these regions. Changes of imaging parameters or the scanner did not cause a significant change of overall image quality relative to the baseline dataset, suggesting a good generalizability. For the patients, qualitative analysis showed a significant improvement of banding artifacts (4.01 ± 0.50 vs 2.77 ± 0.40, P < 0.001), flow artifacts (4.22 ± 0.38 vs 2.97 ± 0.57, P < 0.001), and image quality (3.91 ± 0.45 vs 2.60 ± 0.43, P < 0.001) relative to the original cine. The artifact suppression slightly reduced the LVEF (mean bias = -1.25%, P = 0.01). ConclusionsThe dual-stage network simultaneously reduces banding and flow artifacts in bSSFP cine imaging with a partial interpretability, sparing the need for sequence modification. The method can be easily deployed in a clinical setting to identify artifacts and improve cine image quality.

Novel Wide-Range Frequency Offset Estimation and Compensation for Burst-mode CPFSK Upstream Signaling in TDM-Based Digital Coherent PON

The burst-mode continuous phase frequency shift-keying (CPFSK) transmitter that combines a directly modulated laser diode, an electro absorption modulator and a semiconductor optical amplifier is attractive as a cost-effective transmitter for phase modulation formats for digital signal processing (DSP)-based coherent passive optical network (PON) upstream signaling. However, since highly accurate wavelength controllers for the transmitters in optical network units (ONUs) create excessive cost burdens, large carrier frequency offsets (CFOs) must be expected. Thus, a CFO compensation method with wide compensation range is required. This paper proposes a novel CFO estimation and compensation method for burst-mode CPFSK signals in upstream PON signaling. The proposed method is based on a simple blind algorithm and does not require any training symbols. We demonstrate wide CFO compensation range, from −12 to 14 GHz, with high receiver sensitivity, less than −42.5 dBm for 10 Gbit/s binary CPFSK signals. This range far exceeds that of the conventional CFO compensation method using a blind algorithm. Moreover, the proposed method can enhance the convergence of finite impulse response (FIR) filters. The feasibility of the proposed CFO compensation technique is successfully demonstrated for burst-mode CPFSK signals.

Protecting Bluetooth User Privacy Through Obfuscation of Carrier Frequency Offset

This brief presents the analysis, design, and measurement results of an integrated circuit designed to prevent tracking the location of Bluetooth Low Energy (BLE) transmitters. Conventional BLE transmitters have unique RF fingerprints due to variation-induced imperfections in the underlying circuits. Coupled with BLE’s wide adoption in mobile devices and tendency to transmit continuously, BLE has become a significant threat to the location privacy of individual users. The primary source of this privacy threat is that BLE transmitters have a unique Carrier Frequency Offset (CFO) that can be easily fingerprinted by passive adversaries. To combat this, a test chip is developed that pseudo-randomly changes its CFO by switching in a binary-weighted set of semi-identical MIM capacitors into the tank of an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$LC$ </tex-math></inline-formula> voltage controlled oscillator, all while maintaining compatibility with BLE standard specifications. Measurement results reveal that privacy preservation can be improved from only a few seconds with a conventional design, to over a day with the proposed design.

A turbo‐based encryption and coding scheme for multiple‐input multiple‐output orthogonal frequency division multiplexing wireless communication systems affected by Doppler frequency offset

AbstractMultiple‐Input Multiple‐Output Orthogonal Frequency Division Multiplexing (MIMO‐OFDM) is an essential technology in the wireless communication system. However, its performance is significantly affected by Carrier Frequency Offset (CFO), which leads to inter‐carrier interference (ICI). The CFO estimation and compensation techniques are used to mitigate the Doppler effect. In addition, the confidentiality of data is a key factor of the system. This paper proposes a Turbo‐based encryption and coding scheme to improve reliability and security for the MIMO‐OFDM wireless communication systems affected by the Doppler frequency offset. In our proposed scheme, the secret key is produced from channel parameters between legitimate users and it is used as a seed for generating a pseudo‐random bit sequence using an Advanced Encryption Standard (AES) generator with variable key lengths. The Turbo code's puncturing mechanism is controlled by this pseudo‐random bit sequence. The proposed method is applied to the system with different modulation schemes through the Rayleigh channel. The simulation results show that the system affected by the Doppler effect would obtain the best performance when using the highest key length of the AES generator, the BPSK, and a great number of receive antennas. Furthermore, the proposed solution outperforms several previous approaches for the MIMO‐OFDM systems.

A Frequency-Domain I/Q Imbalance Calibration Algorithm for Wideband Direct Conversion Receivers Using Low-Cost Compensator

The amplitude and phase imbalances of the in-phase (I) and quadrature (Q) branches inherent in the direct conversion receiver structure cause the generation of image frequency interference signals. In this paper, a frequency-domain I/Q imbalance calibration algorithm is proposed for wideband direct conversion receivers. The I/Q imbalance model is rebuilt by applying the infinitesimal method and FFT algorithm. The mathematical expressions for the exact computation of the I/Q imbalance parameters are derived based on the frequency-domain statistical properties of the baseband signal. The two phase parameters, frequency-dependent I/Q imbalance (FD-IQI) and frequency-independent I/Q imbalance (FI-IQI), are separated according to the parity properties of the imbalance parameter. To avoid the interference from the transmitter, the receiver impairment estimation is performed using a frequency offset (FO) DC training signal, and a low-cost real-valued compensation (RVC) filter is introduced to correct the impairments of the received signal. The performances of the proposed calibration model are evaluated through simulations and experiments. The simulation results show that the image rejection ratio (IRR) is improved to 80-120 dBc and can also exceed 40 dBc at high noise levels. The experimental results based on the CX9261A evaluation board show that the average IRR of the multi-tone signal is increased by 24.99 dB, and the IRR of the wideband signal is increased by 19.08 dB.

Range-angle-dependent beamforming for FDA radar with Hamming interelement spacing and sinusoidal multicarrier approach

By employing a tiny frequency offset across the array elements, a frequency diverse array (FDA) produces a beampattern with the property of being range-angle-dependent. However, the beampattern of a traditional FDA has many maxima at undesired range-angle couples, which is unfavorable for target localization and jamming suppression. In this paper, a novel FDA scheme with Hamming interelement spacing, namely, the HIS-FDA, is proposed. By adopting Hamming window weighted interelement spacing and frequency offsets optimized by the genetic algorithm, the HIS-FDA produces a dot-shaped well-performed beampattern, which has superior performance over the existing FDA systems, especially in the angle dimension. The multiple input multiple output technique and multiple matched filters are employed at the receiver to solve the time-varying problem. A new multicarrier (MC) technique termed the sinusoidal MC approach is also presented to improve the beampattern performance, especially in the range dimension. Our proposed scheme outperforms the existing FDA systems in terms of the mainlobe width in the range and angle profiles, the sidelobe level, and the range-angle spatial region of the mainlobe. Comparison results are provided to validate the superiority of the proposed scheme.

Reducing Bias for Multistatic Localization of a Moving Object by Transmitter At Unknown Position

Multistatic localization plays an important role in object localization. In this paper, we address the problem of multistatic localization of a moving object in the absence of transmitter position when the transmitter is not synchronized with the receivers. We propose to jointly estimate the unknowns, including the object position and velocity, the transmitter position, and the clock and frequency offsets, using both time delay and Doppler frequency shift measurements. To this end, we first formulate a constrained weighted least squares (CWLS) minimization problem, whose solution is found to have significant bias caused by approximations in transforming the model equations and solving the problem. To reduce the bias, we further formulate a non-convex bias reduced CWLS (BR-CWLS) problem by imposing a quadratic constraint, which is constructed by considering the second-order noise and errors of the matrices and vectors involved in the CWLS problem. One particular aspect of the proposed BR-CWLS method is that the errors in approximating the weighting matrix are taken into consideration for bias reduction. The non-convex BR-CWLS problem is solved by applying the semidefinite relaxation technique to relax it as a convex semidefinite program. In addition, we show through the mean square error (MSE) analysis that the performance of the BR-CWLS solution can approach the Cramer-Rao lower bound performance when the noise is not significant. We also derive the theoretical bias expression for evaluating the amount of bias. Simulation results demonstrate the good performance of the proposed method in terms of both MSE and bias.

Resolving Doppler Ambiguity for Fast-moving Targets with FDA-MIMO Radar

Although the problem of range ambiguity is solved with the frequency diverse array (FDA)-multiple-input multiple-output (MIMO) radar by utilizing the degree-of-freedom (DOFs) in the range domain, the phenomenon of Doppler ambiguity occurs for fast-moving target. In this article, an offset frequency alignment (OFA) method is proposed to solve the problem of Doppler ambiguity in FDA-MIMO radar. At the design stage, the Doppler frequency offsets, corresponding to different transmit pulses, are aligned by eliminating the residual phases. In this regard, the point targets can be focused in the transmit spatial frequency domain. Furthermore, the Doppler ambiguity index is estimated after principal velocity compensation resorting to maximum likelihood (ML) criterion, where both the cases of known and unknown range ambiguity indexes are investigated respectively. Moreover, in order to ensure the estimation performance, the frequency offset across the transmit array elements is designed by enlarging the term related to the Doppler frequency offset. At the analysis stage, the performance of Doppler ambiguity index estimation in terms of root mean square error (RMSE) is assessed in comparison with the Cramer-Rao bound (CRB). Numerical results are provided to verify the effectiveness of the proposed method to resolve the Doppler ambiguity.

Estimating and Tracking Wireless Channels Under Carrier and Sampling Frequency Offsets

This article addresses the challenge of estimating and tracking wireless channels under carrier and sampling frequency offsets, which also incorporate phase noise and sampling time jitter. We propose a novel adaptive filter that explicitly estimates the channel impulse response, carrier frequency offset, and sampling frequency offset by minimizing the mean-square error (MSE) and, when the estimated parameters are time-varying, inherently performs tracking. The proposed filter does not have any requirements for the structure of the waveform, but the digital transmitted waveform must be known to the receiver in advance. To aid practical implementation, we derive upper bounds for the filter's step sizes. We also derive expressions for the filter's steady-state MSE performance, by extending the well-known energy conservation relation method to account for the self-induced nonstationarity and coupling of update equations that are inherent in the proposed filter. Theoretical findings are verified by comparison to simulated results. Proof-of-concept measurement results are also provided, which demonstrate that the proposed filter is able to estimate and track a practical wireless channel under carrier and sampling frequency offsets.

OFDM-CFO and Resource Scheduling Algorithm Using Fuzzy Linear-CFO

Orthogonal Frequency-Division Multiplexing (OFDM) is the form of a digital system and a way of encoding digital data across multiple frequency components that are used in telecommunication services. Carrier Frequency Offset (CFO) inaccuracy is a major disadvantage of OFDM. This paper proposed a feasible and elegant fuzzy-based resource allocation technique, that overcomes the constraints of the CFO. The suggested Fuzzy linear CFO estimation (FL-CFO) not only estimates the CFO with increased precision but also allocates resources effectively, and achieves maximum utilization of dynamic resources. The suggested FL-CFO error estimation algorithm in OFDM systems employing 1-bit Quadrate errors ADC (1-bit QE) is utilized to extract the precise CFO. Additionally, the base station (BS) manages the Resource Units (RU), which could be used to distribute resources in such a manner that the user requests are met. To assign resources to a certain job, fuzzy rules are devised. When the residence duration exceeds the resource requirement time then the particular resources are provided to the highest-priority jobs. As a result, the job performance will not be halted due to a lack of allocated resources. Performance metrics such as utilization, rate of failure, and life span, as well as energy consumption, are used to assess the proposed FL-CFO.

2-D Magnetic Resonance Tomography With an Inaccurately Known Larmor Frequency Based on Frequency Cycling

When using magnetic resonance tomography (MRT) for imaging 2-D or 3-D water-bearing structures in a subsurface, the transmitting frequency must be the same as the Larmor frequency. Due to the inhomogeneity and noise interference in a geomagnetic field, it is difficult to determine the precise Larmor frequency using a magnetometer, resulting in unknown frequency offsets and inaccurate estimations of water content and relaxation time ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{2}^{*}$ </tex-math></inline-formula> ). To solve the 2-D MRT imaging problem in the case of an unknown frequency offset, a frequency cycling method is proposed in this article. This method takes the estimated Larmor frequency as the center, uses two frequencies with the same offset for transmitting, then combines the acquired MRT signals to obtain frequency-cycled data, and finally uses the off-resonance kernel function for inversion. Based on MRT forward modeling and QT inversion, we conduct synthetic data experiments on a complex model with three water-bearing structures and test the 2-D imaging results of the frequency-cycled data. The results show that the water content and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{2}^{*}$ </tex-math></inline-formula> distribution obtained by the inversion of the frequency-cycled data can accurately reflect the water-bearing structure, which is better than the results of the assumed on-resonance case. In addition, the phase correction method presented in this article significantly improves the accuracy of 2-D MRT estimated aquifer properties under low resistivity conditions. Finally, the validity and accuracy of the frequency cycling method are verified by comparing the inversion results of the data with known drilling data collected in field measurements.

Carrier Frequency Offset Estimation in 5G NR: Introducing Gradient Boosting Machines

The Beyond fifth Generation (B5G) communication systems imposed several challenges on radio designers. For example, a machine is required to set up a call at a low Signal-to-Noise Ratio (SNR), as low as -10 dB, in the extended coverage mode. Moreover, only one receive antenna will be available, and virtually no frequency diversity. Such requirements present major challenges to maintaining timing and frequency synchronization. Carrier Frequency Offset (CFO) estimation is at the heart of these challenges. Different ways have been proposed for CFO estimation such as maximum likelihood based on a cyclic prefix. Nevertheless, these methods remain limited in various ways. At the same time, Machine Learning (ML) techniques showed outstanding performance in several wireless communication problems. In this work, we propose an ML-based approach for CFO estimation in OFDM systems. Specifically, we propose a Gradient-Boosting Machine (GBM)-based solution to predict the CFO given the received Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS). Furthermore, we make our dataset available for public access to encourage other researchers to pursue this promising direction. We compare our results with different baseline models (i.e., artificial neural networks and support vector machines). The experimental results show that our model outperforms other baseline models due to its ensemble nature which enables ensemble models to obtain a better generalization behavior.

New Preamble Sequence for WiMAX System with Improved Synchronization Accuracy

Worldwide Interoperability for Microwave Access (WiMAX) trusts Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) combination for the deployment of physical layer functions and for connecting the medium access control to the wireless media. Even though Orthogonal Frequency Division Multiplexing (OFDM) facilitates reliable digital broadband transmission in the fading wireless channels, the presence of synchronization errors in the form of Carrier Frequency Offset (CFO) and Time Offset (TO) adversely affect the performance of OFDM based physical layers. The objective of this work is to improve the accuracy of the frequency and the time offset estimation in the WiMAX physical layer. A method to enhance the synchronization accuracy by fine-tuning the merit factor of the preamble sequence is suggested in this paper. Also, a new preamble with improved synchronization accuracy is proposed for the WiMAX system. The performance of the proposed preamble is evaluated in a Rayleigh fading channel and the results of simulations show that the Mean Square Error (MSE) in offset estimation is significantly reduced and it outperforms the standard WiMAX preamble.

Frequency-Modulated OFDM: A New Waveform for High-Mobility Wireless Communications

This paper introduces a novel waveform for wireless communication, denoted as Frequency-Modulated Orthogonal Frequency-Division Multiplexing (FM-OFDM). By frequency-modulating an OFDM signal and further defining a suitable cutoff subcarrier, the resulting constant-envelope waveform (ensuring a low Peak to Average Power Ratio) exhibits strong robustness not only to Doppler, but also to phase noise and carrier frequency offsets. These impairments introduce an additive error term at the information-bearing subcarriers that is mostly concentrated at the lowest part of the spectrum. No inter-carrier interference is thus present, and impairments can be easily overcome by mapping the information above a cutoff subcarrier. Theoretical expressions and numerical results prove the superiority of FM-OFDM over the state of the art, particularly in high-speed Rayleigh channels and/or high phase noise.