Rate Vector Research Articles

A Study of BER and EVM Degradation in Digital Modulation Schemes Due to PLL Jitter and Communication-Link Noise

A phase-locked-based frequency synthesizer – ubiquitously used to generate local oscillation in a communication transceiver – exhibits phase noise and jitter which considerably degrades bit-error rate (BER) and error vector magnitude (EVM) of a digital communication link. This paper presents an analytical study of EVM and BER degradation for a variety of widely used digital modulation schemes. Phase noise and jitter of a generic integer-N phase-locked loop (PLL) as a local oscillator feeding an RF mixer are derived, while accounting for the reference spurs and cyclo-stationarity of the mixer operation as well as the additive noise of the communication link. This jitter model is then utilized to directly study its impact on digital modulation constellations. Specifically, the EVM and BER degradation due to the PLL jitter in communication systems incorporating M-ary phase-shift keying (M-PSK) and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${4^{M}}$ </tex-math></inline-formula> quadrature amplitude modulation ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${4^{M}}$ </tex-math></inline-formula> QAM) are analyzed. Comparison between analytical models and system-level simulations verifies an excellent accuracy of these models.

Prediction and Analysis of the Force and Shape Parameters in Variable Gauge Rolling

Variable gauge rolling is a new process to obtain a plate for which the thickness changes continuously by continuously and dynamically adjusting the roll gap upward and downward in the rolling process. This technology is an effective method for producing lightweight, low-cost, and economical plates. However, variable gauge rolling is an unsteady process, and the changes in the force and deformation parameters are complex. In this research, based on the minimum energy theory of the variational principle and considering the characteristics of the roll movement and workpiece deformation comprehensively, the internal plastic deformation, friction, shear and tension powers, and the minimum result of the total power functional in upward and downward rolling are obtained with the first integral and then with a variation of adopting the specific plastic power and strain rate vector inner product. The analytical results of the deformation and force parameters are also established using the variational method. Then the precision of this model is certified using the measured values in a medium plate hot rolling plant and the experimental data for Tailor Rolled Blank rolling. Good agreement is found. Additionally, the variation rule of bite angle, neutral angle, and location neutral points are shown, and the change mechanism of the friction parameter on the stress state effect coefficient is given in variable gauge rolling. This research proposes a new mathematical model for rolling process control that provides a scientific basis and technical support for obtaining an accurate section shape in variable gauge rolling production.

Blood Flow Turbulence Quantification of Carotid Artery With a High-Frame Rate Vector Flow Imaging.

To assess the feasibility and performance of Turbulence (Tur) index as a quantitative tool for carotid artery flow turbulence; to detect and compare the blood flow patterns of common carotid artery (CCA) and carotid bulb (CB) at different ages and cardiac phases in healthy adults, and thus interpret the evolvement of etiology difference between CCA and CB. Carotid flow characteristics of 40 healthy volunteers were evaluated quantitatively by a high-frame rate vector flow imaging. Three types of flow patterns were defined depending on the distributive range of complex flow during systole in CB. Comparison of mean Tur value in CCA and CB at different age groups and cardiac phases was performed. And the correlation between Tur value and the diameter ratio of proximal internal carotid artery to common carotid artery (DRpro-ica/cca) was tested. Mean Tur values in CB were remarkably higher than that in CCA, whether during systole or diastole (P < .001). Meanwhile Tur values in CB during systole were significantly higher than that during diastole (P < .001). Flow complexity of CB showed variations among 40 participants especially in systole, whereas the flow pattern of CCA was relatively consistent. Mean Tur values were positively correlated with DRpro-ica/cca in CB (ρ=0.69, P < .05). V Flow imaging provided a reliable method-Tur, for quantitative analysis of carotid blood flow. It had potential to be further applied in distinguishing complex hemodynamic characteristics in high-risk people of carotid diseases for the risk stratification of cardiovascular events.

Variational cold-start resistant recommendation

Conventionally, cold-start limitations are managed by leveraging side information such as social-trust relationships. However, the relationships between users in social networks are complex, uncertain, and sparse. Therefore, it is necessary to extract beneficial social connections to make the recommendation models cold-start resistant. Towards this end, we propose a novel recommendation model called Variational Cold-start Resistant Recommendation (CORE-VAE). More concretely, we employ a social-aware similarity function and a graph convolutional network (GCN) to generate robust social-aware user representations that account for the complexities, uncertainties, and sparse nature of the social-trust network. Subsequently, these powerful social-aware representations aid us in producing cold-start resistant rating vectors for all users. To explore the rich user rating information, we propose an expressive variational autoencoder (VAE) model. Unlike earlier VAE-based CF models, CORE-VAE utilizes a novel prior distribution and a well-designed skip-generative network to alleviate the posterior collapse issue considerably. Besides, CORE-VAE can also capture the latent space’s uncertainty and ensure that observations and their accompanying latent variables have high mutual information. Overall, these novel techniques dramatically help produce better latent representations for generating more accurate recommendations. We show that CORE-VAE outperforms numerous competitive baseline models on real-world datasets through comprehensive empirical evaluation and analysis.

A Forward-Looking Approach to Compare Ranking Methods for Sports

In this paper, we provide a simple forward-looking approach to compare rating methods with respect to their stability over time. Given a rating vector of entities involved in the comparison and a ranking indicated by the rating, the stability of the methods is measured by the change in rating vector and ranks of the entities over time from a forward-looking perspective. We investigate various linear algebraic rating methods and use the Euclidean distance and Kendall tau rank correlation to measure their stability in rating and ranking, respectively. The investigations are based on both rolling and expanding window approaches. We apply the methodology to sports as a widely known ranking and rating environment. The results suggest that PageRank and Massey rating methods provide better rating and ranking stability than simple methods, such as winning percentage, and more advanced ones, such as Colley’s least square and Keener’s eigenvector-based method. Finally, a simple way to examine the potential predictive power of the rating methods is also provided.

Reconfigurable photonics-based millimeter wave signal aggregation for non-orthogonal multiple access.

A reconfigurable optical-to-electrical signal aggregation is proposed, for the first time, using optical signal processing and photo-mixing technology. Two optically modulated quadrature phase-shift keying (QPSK) signals are aggregated into a single 16-quadrature amplitude modulation (16-QAM) signal and, simultaneously, carried over a 28-GHz millimeter wave (MMW) carrier using an optimized heterodyne beating process through a single photodiode. To demonstrate the system reconfigurability, aggregation of two optical binary phase-shift keying signals is mapped into MMW QPSK or four-level pulse amplitude modulation signals by controlling the relative phases and amplitudes, respectively, of the input signals. In addition, the aggregation of two 16-QAM signals into a 256-QAM signal and the aggregation of three QPSK signals into a 64-QAM format are achieved. Besides, we report the effect of laser phase noise on signal aggregation performance. The de-aggregation of the aggregated MMW signals is performed electrically using a successive interference cancellation algorithm. Moreover, a proof-of-concept experiment is conducted to validate the numerical simulations. Two 1-Gbaud BPSK (1 Gbps) and QPSK (2 Gbps) optical signals are optically transmitted over a 20-km single-mode fiber as MMW over fiber signals. Then, the signals are aggregated into QPSK (2 Gbps) and 16-QAM (4 Gbps) 28-GHz MMW signals, respectively. The aggregated signal is further transmitted over a 1-m wireless channel. The performance of the proposed system is evaluated using bit error rate and error vector magnitude metrics.

Simultaneous Transmission of 5G MMW and Sub-THz Signals Through a Fiber-FSO-5G NR Converged System

Simultaneous transmission of fifth-generation (5G) millimeter-wave (MMW) and sub-THz signals through a fiber-free-space optical (FSO)-5G new radio (NR) converged system is successfully achieved. It is an inventive demonstration that utilizes a cross medium of optical fiber, optical wireless, and RF wireless to enhance the aggregate transmission rate to 60 Gb&#x002F;s. We transmitted 20 Gb&#x002F;s in the 50-GHz MMW, 100-GHz sub-THz, and 150-GHz sub-THz bands at the same time through the seamless fiber-FSO-5G NR convergence, comprising 20-km single-mode fiber (SMF), 500-m optical wireless, and 2-m (50-GHz MMW)&#x002F;1-m (100-GHz sub-THz)&#x002F;0.5-m (150-GHz sub-THz) 5G wireless transmissions. Sufficiently low bit error rate (&lt; forward error correction criterion of 3.8&#x00D7;10^&#x2212;3) and error vector magnitude (&lt;third-generation partnership project limit of 12.5&#x0025;) are attained to satisfy the requirements of 5G NR communications in MMW and sub-THz bands. This newly-built fiber-FSO-5G NR converged system shows promise for the development of long-haul wired-wireless transmissions with wider service areas and higher access data rates.

Optimization-based self-alignment method for stationary SINS with geographical latitude uncertainty

To solve the self-alignment problem of strapdown inertial navigation system (SINS) with geographical latitude uncertainty, an optimization-based self-alignment (OSA) method and its improvement for stationary SINS without using the latitude information are proposed. We use only the accelerometer and gyroscope measurements, without the aid of the external latitude information, to determine the Earth rate in the navigation frame. Then we formulate the SINS self-alignment process as a Wahba problem to overcome the disturbances of random noise, and use the estimated Earth rate vector and multiple measurements from the accelerometer and gyroscope to formulate the nonlinear objective function. Moreover, the alignment errors of the OSA method are also presented, based on which we propose a two-position OSA to estimate and compensate the horizontal accelerometer biases to further improve the alignment accuracy. The results of simulation and experiments demonstrate that the proposed OSA method and its improvement perform robust to the noise disturbances and achieve better alignment accuracy than conventional self-alignment methods.

Attitude propagation using slewing and rotational transformations of a single axis

• An analytical attitude transformation for an axis that slews along a conical trajectory was derived. • Error free attitude propagation was achieved using the slewing and rotational transformation of a single axis. • Attitude was propagated without error for an axisymmetric vehicle with time dependent angular rate magnitude. A new analytical method to compute the slewing transformation of an axis that moves along a conical trajectory centered on a fixed axis was derived. The result was used to increase the attitude propagation accuracy using a single axis by incorporating the slewing motion of the angular rate vector into the attitude propagation algorithm. It was shown that when the slew rate of the angular rate vector has a fixed orientation in the body frame and has a magnitude proportional to the angular rate vector magnitude, the attitude can be propagated with only numerical roundoff error. The findings not only agree with previously published results, but provide an additional new solution due to the commutative property of the associated slewing and rotational transformations. The algorithm was applied to pure coning motion having time dependent angular rate magnitude and the coning motion of axisymmetric vehicles with time dependent angular rate magnitude. Numerical examples that demonstrate the improvement in accuracy are included.

Circular RNA as a Potential Biomarker for Forensic Age Prediction

In forensic science, accurate estimation of the age of a victim or suspect can facilitate the investigators to narrow a search and aid in solving a crime. Aging is a complex process associated with various molecular regulations on DNA or RNA levels. Recent studies have shown that circular RNAs (circRNAs) upregulate globally during aging in multiple organisms such as mice and C.elegans because of their ability to resist degradation by exoribonucleases. In the current study, we attempted to investigate circRNAs’ potential capability of age prediction. Here, we identified more than 40,000 circRNAs in the blood of thirteen Chinese unrelated healthy individuals with ages of 20–62 years according to their circRNA-seq profiles. Three methods were applied to select age-related circRNA candidates including the false discovery rate, lasso regression, and support vector machine. The analysis uncovered a strong bias for circRNA upregulation during aging in human blood. A total of 28 circRNAs were chosen for further validation in 30 healthy unrelated subjects by RT-qPCR, and finally, 5 age-related circRNAs were chosen for final age prediction models using 100 samples of 19–73 years old. Several different algorithms including multivariate linear regression (MLR), regression tree, bagging regression, random forest regression (RFR), and support vector regression (SVR) were compared based on root mean square error (RMSE) and mean average error (MAE) values. Among five modeling methods, regression tree and RFR performed better than the others with MAE values of 8.767 years (S.rho = 0.6983) and 9.126 years (S.rho = 0.660), respectively. Sex effect analysis showed age prediction models significantly yielded smaller prediction MAE values for males than females (MAE = 6.133 years for males, while 10.923 years for females in the regression tree model). In the current study, we first used circRNAs as additional novel age-related biomarkers for developing forensic age estimation models. We propose that the use of circRNAs to obtain additional clues for forensic investigations and serve as aging indicators for age prediction would become a promising field of interest.

A glimpse at team composition and intention to grow in academic spin-offs

ABSTRACT Starting from the description of the main traits of the academic environment within which this peculiar form of new venture is born, the authors question—in light of the presented results about the growth rates of a national sample of academic spin-offs—whether and how the intention to grow expressed by the academic entrepreneur influences the composition of the team, and more specifically the integration of nonacademic knowledge and experience—as a vector of a higher growth rate within the target market. In particular, the research question to be answered is: Does the integration of nonacademic team members in the early stages tie with a higher intention to grow of the academic entrepreneur? The contribution is configured as a work in progress, and it introduces an advancement about team formation process. Implications for practitioners relate to the key role of team composition in fostering growth of academic spin-offs.

Investigation of the partially premixed turbulent combustion through the PRECCINSTA burner by large eddy simulation

The turbulent combustion processes within full annular PRECCINSTA combustor were investigated numerically in the present study. Dynamic thickened flame model was implemented to simulate the partially premixed turbulent methane-air combustion processes. The governing equations considering wall heat loss were solved by using the large eddy simulation method. In order to validate the implemented model, the temperature and main species distribution profiles within the burner were compared to the experimental data and good agreement was observed. The vortex motion characteristics of the cold flow field, the characteristics of the flame surface area, heat release rate and velocity vector changes with time during the circumferential cross-fire process were studied. Results showed that considering the wall heat loss significantly improved the prediction accuracy of the temperature and intermediate species distributions causing flame structure change from “M-shaped” to “V-shaped”. Numerical analysis proved that the circumferential velocity in different direction induced by the swirling flow near the inner and outer walls of the annular combustor are coupled with the combustion heat expansion, causing difference gain effects to the flame propagation on two sides of the combustor.

Attaining Fairness in Communication for Omniscience.

This paper studies how to attain fairness in communication for omniscience that models the multi-terminal compress sensing problem and the coded cooperative data exchange problem where a set of users exchange their observations of a discrete multiple random source to attain omniscience—the state that all users recover the entire source. The optimal rate region containing all source coding rate vectors that achieve omniscience with the minimum sum rate is shown to coincide with the core (the solution set) of a coalitional game. Two game-theoretic fairness solutions are studied: the Shapley value and the egalitarian solution. It is shown that the Shapley value assigns each user the source coding rate measured by their remaining information of the multiple source given the common randomness that is shared by all users, while the egalitarian solution simply distributes the rates as evenly as possible in the core. To avoid the exponentially growing complexity of obtaining the Shapley value, a polynomial-time approximation method is proposed which utilizes the fact that the Shapley value is the mean value over all extreme points in the core. In addition, a steepest descent algorithm is proposed that converges in polynomial time on the fractional egalitarian solution in the core, which can be implemented by network coding schemes. Finally, it is shown that the game can be decomposed into subgames so that both the Shapley value and the egalitarian solution can be obtained within each subgame in a distributed manner with reduced complexity.

Hybrid recommendation algorithm based on real-valued RBM and CNN.

With the unprecedented development of big data, it is becoming hard to get the valuable information hence, the recommendation system is becoming more and more popular. When the limited Boltzmann machine is used for collaborative filtering, only the scoring matrix is considered, and the influence of the item content, the user characteristics and the user evaluation content on the predicted score is not considered. To solve this problem, the modified hybrid recommendation algorithm based on Gaussian restricted Boltzmann machine is proposed in the paper. The user text information and the item text information are input to the embedding layer to change the text information into numerical vector. The convolutional neural network is used to get the latent feature vector of the text information. The latent vector is connected to rating vector to get the item and the user vector. The user vector and the item vector are fused together to get the user-item matrix which is input to the visual layer of Gaussian restricted Boltzmann Machine to predict the ratings. Some simulation experiments have been performed on the algorithm, and the results of the experiments proved that the algorithm is feasible.

Virtual information core optimization for collaborative filtering recommendation based on clustering and evolutionary algorithms

Collaborative filtering (CF), the most widely used recommendation algorithm, has to face the sparsity and scalability problem. Some researchers proposed to select a representative set of real users called information core (IC) from all the real users, which is used as the candidate neighbor set in the CF to alleviate the scalability problem. However, the rating vectors of these real users that compose IC are usually sparse, which will negatively affect the recommendation accuracy. In this paper, a virtual information core (VIC) optimization algorithm is proposed based on clustering and evolutionary algorithms for CF recommendation (VICO-CEA). The problem of searching for VIC is modeled as a combinatorial optimization problem, and is solved offline by the proposed evolutionary algorithm. The VIC is a set of virtual core users, each of which is constructed by averaging out multiple real users. These virtual core users in the VIC are no longer sparse and are found by the evolutionary optimization, which will improve the recommendation accuracy and reduce the online recommendation time as the VIC is used as the candidate neighbor set in the CF. Meanwhile, to make offline optimization more efficient, two strategies are proposed. One is to design a simple similarity measure based on dimensionality reduction and clustering to save time in calculating similarities by reducing the dimensionality of users’ rating vectors. The other is to use dimensionality reduction and clustering to construct a smaller training set and validation set by reducing the dimensionality of items’ rating vectors. The experimental results show that VICO-CEA can not only significantly reduce the online recommendation time further but also improve the recommendation accuracy greatly compared to traditional CF and other information-core-based methods.

Vibratory Gyroscope Scale Factor and Bias on-Run Self-calibration

А new method for on-run periodic scale factor and bias self-calibration of vibratory gyroscopes in an inertial measurement unit with a redundant number of sensors is proposed. Self-calibration uses predefined virtual positive and negative angle rates to calibrate the SF, and the bias of the gyroscope that is in calibration mode, while the others, at least three gyroscopes of an inertial measurement unit, whose sensitivity axes do not lie in the same plane, operate in the measurement mode to measure the real angle rate of a vehicle. The projection of the current angle rate onto the sensitivity axis of the gyroscope being calibrated is computed from the results of measuring the full angle rate vector by the other three gyroscopes, creating conditions for the calibration procedure. In contrast to known methods, such as single-axis or multi-axis rotation of an inertial measurement unit and vibration modes reversal, the proposed method does not use mechanical rotation, which requires additional devices, and does not require a reorientation of the vibrating wave, which entails the need to align the parameters of the two measuring channels. The scale factor and bias calibration procedure using this method is the same for any gyroscope of an inertial measurement unit and can be applied to several gyroscopes at the same time. Therefore, the proposed method has great potential for an application not only for small-sized 4-gyro inertial measurement unit based on vibratory gyroscopes but also for multi-gyro inertial measurement unit based on micro-electro-mechanical gyroscopes. Experimentally shown that using the proposed method a gyro requirements mitigation coefficient can be substantially increased and can provide high accuracy for autonomous navigation systems based on low-cost, small-sized, and micro-electro-mechanical gyroscopes.

Ellipsoidal equilibrium figure and Cassini states of rotating planets and satellites deformed by a tidal potential in the spatial case

The equilibrium figure of an inviscid tidally deformed body is the starting point for the construction of many tidal theories such as Darwinian tidal theories or the hydrodynamical Creep tide theory. This paper presents the ellipsoidal equilibrium figure when the spin rate vector of the deformed body is not perpendicular to the plane of motion of the companion. We obtain the equatorial and the polar flattenings as functions of the Jeans and the Maclaurin flattenings, and of the angle $\theta$ between the spin rate vector and the radius vector. The equatorial vertex of the equilibrium ellipsoid does not point toward the companion, which produces a torque perpendicular to the rotation vector, which introduces terms of precession and nutation. We find that the direction of spin may differ significantly from the direction of the principal axis of inertia $C$, so the classical approximation $\mathsf{I}\vec{\omega}\approx C\vec{\omega}$ only makes sense in the neighborhood of the planar problem. We also study the so-called Cassini states. Neglecting the short-period terms in the differential equation for the spin direction and assuming a uniform precession of the line of the orbital ascending node, we obtain the same differential equation as that found by Colombo (1966). That is, a tidally deformed inviscid body has exactly the same Cassini states as a rotating axisymmetric rigid body, the tidal bulge having no secular effect at first order.

Numerical analysis of UFMC and FBMC in wavelength conversion for radio over fiber systems using semiconductor optical amplifier

The 5G networks promise to use advanced access techniques and modulation formats to achieve new requirements of the huge number of users such as higher data, high speed, and low latency. Millimeter-wave (MMW) signal and new modulation schemes such as universal filtered multicarrier (UFMC) and filtered bank multicarrier (FBMC) are playing a fundamental role to accomplish these requirements. UFMC and FBMC are classified under multicarrier modulation formats which are considered as a suitable modulation scheme in 5G and replacing a well-known modulation format of filtered orthogonal frequency division multiplexing (OFDM) which was used in 4G. This interest in using UFMC and FBMC in 5G wireless systems is the reduction of out-of-band (OOB) spectrum in UFMC and reduction of sidelobe suppression in FBMC. The contribution of this paper is to propose a model of wavelength conversion using a semiconductor optical amplifier (SOA) for both schemes UFMC and FBMC- off-set quadrature amplitude (OQAM). In addition, we analyze and compare their performance in terms of bit error rate (BER) and error vector magnitude (EVM) for a wavelength conversion application. Finally, we investigate the main disadvantage of OFDM which is the high Peak to Average Power Ratio (PAPR) for both schemes, and compare between them. Photonic switching of a 4 Gbps 16-QAM UFMC and FBMC-OQAM signal centered at 50 GHz is performed. The optical single-sideband (OSSB) signal is generated with 18.85 dB of sideband suppression ratio (SSR). The results show that the best values of BER and EVM can be obtained when the injection current (IC) is 0.7–0.9A. For converted signal using FBMC-OQAM, it has power penalty ∼ 2.5 dB at BER threshold 1 × 10-3and has also ∼ 2 dB power penalty compared to the UFMC scheme at EVM threshold 5.6%. In addition, the wavelength switching system with FBMC and UFMC modulation schemes achieves the same PAPR.

Lindblad Dynamics and Disentanglement in Multi-Mode Bosonic Systems.

In this paper, we consider the thermal bath Lindblad master equation to describe the quantum nonunitary dynamics of quantum states in a multi-mode bosonic system. For the two-mode bosonic system interacting with an environment, we analyse how both the coupling between the modes and the coupling with the environment characterised by the frequency and the relaxation rate vectors affect dynamics of the entanglement. We discuss how the revivals of entanglement can be induced by the dynamic coupling between the different modes. For the system, initially prepared in a two-mode squeezed state, we find the logarithmic negativity as defined by the magnitude and orientation of the frequency and the relaxation rate vectors. We show that, in the regime of finite-time disentanglement, reorientation of the relaxation rate vector may significantly increase the time of disentanglement.

A Fuzzy based Pathfinder Optimization Technique for Performance-Effective Task Scheduling in Cloud

Cloud computing provides a shared pool of resources in a distributed environment. It supports the features of utility-based computing. Task scheduling is a largely studied research topic in cloud computing, which targets utilizing cloud resources for tasks by considering the objectives specified in QoS. Optimal task scheduling is an NP-hard problem, which is time-consuming to solve with precise methods and depends on many factors such as completion time, latency, cost, energy consumption, throughput, and load balance on the machines. Therefore, using meta-heuristic algorithms is a good selection. This paper uses the Pathfinder optimization Algorithm (PFA) for the task scheduling problem; but when the dimension of a problem is extremely increased, the performance of this algorithm decreases. In the last iterations, fluctuation rate (A) and vibration vector (e) converge to 0, and finding a new solution is impossible. We used fuzzy logic to overcome this shortcoming and named the new algorithm Fuzzy-PFA (FPFA). In this paper, makespan, energy consumption, throughput, tardiness, and degree of imbalance are considered as objective functions. Our goal is to minimize the makespan, energy consumption, tardiness, and degree of imbalance while maximizing throughput. Finally, different algorithms such as Firefly Algorithm (FA), Bat Algorithm (BA), Particle Swarm Optimization (PSO), and PFA are used for comparison. The experimental results indicate that the proposed scheduling algorithm can improve up to 34.2%, 16.2%, 15.9%, and 3.5% the objective function in comparison with FA, BA, PSO, and PFA, respectively.