Group-Based Successive Interference Cancellation for Multi-Antenna NOMA System with Error Propagation

Non-orthogonal multiple access(NOMA)is viewed as a key technique to improve the spectrum efficiency and solve the issue of massive connectivity.However,for power domain NOMA,the required overall transmit power should be increased rapidly with the increasing number of users in order to ensure that the signal-to-interference-plus-noise ratio reaches a predefined threshold.In addition,since the successive interference cancellation(SIC)is adopted,the error propagation would become more serious as the order of SIC increases.Aiming at minimizing the total transmit power and satisfying each user’s service requirement,this paper proposes a novel framework with group-based SIC for the deep integration between power domain NOMA and multi-antenna technology.Based on the proposed framework,a joint optimization of power control and equalizer design is investigated to minimize transmit power consumption for uplink multi-antenna NOMA system with error propagations.Based on the relationship between the equalizer and the transmit power coefficients,the original problem is transformed to a transmit power optimization problem,which is further addressed by a parallel iteration algorithm.It is shown by simulations that,in terms of the total power consumption,the proposed scheme outperforms the conventional OMA and the existing cluster-based NOMA schemes.

Error Propagation in Geochemical Calculations of Groundwater-Mineral Interactions:A Case Study from the Pingdingshan Coalfield,Henan

The WATEQ4F-based 'multiple step method', or the method of running WATEQ4F repeatedly, was used to evaluate the error propagation in computations of water-mineral interactions under the circumstances of constant and varied temperatures due to the uncertainties of input variables. The results show the following: the errors of water chemistry analysis can strongly affect the modelling results of water-mineral reactions; different input variables (errors) have different effects on the saturation indices (S.I.) of different minerals; in many cases, the S.I. errors of minerals change with temperatures.

A SCR method for uncertainty estimation in geodesy non-linear error propagation: Comparisons and applications

We review three derivative-free methods developed for uncertainty estimation of non-linear error propagation, namely, MC(Monte Carlo), SUT(scaled unscented transformation), and SI(sterling interpolation). In order to avoid preset parameters like as these three methods need, we introduce a new method to uncertainty estimation for the first time, namely, SCR(spherical cubature rule), which is no need for setting parameters. By theoretical derivation, we prove that the precision of uncertainty obtained by SCR can reach second-order. We conduct four synthetic experiments, for the first two experiments, the results obtained by SCR are consistent with the other three methods with optimal setting parameters, but SCR is easier to operate than other three methods, which verifies the superiority of SCR in calculating the uncertainty. For the third experiment, real-time calculation is required, so the MC is hardly feasible. For the forth experiment, the SCR is applied to the inversion of seismic fault parameter which is a common problem in geophysics, and we study the sensitivity of surface displacements to fault parameters with errors. Our results show that the uncertainty of the surface displacements is the magnitude of ±10 mm when the fault length contains a variance of 0.01 km^(2).

Misclassification error propagation in land cover change categorization

It is important to describe misclassification errors in land cover maps and to quantify their propagation through geo-processing to resultant information products,such as land cover change maps.Geostatistical simulation is widely used in error modeling,as it can generate equal-probable realizations of the fields being considered,which can be summarized to facilitate error propagation analysis.To fix noninvariance in indicator simulation,discriminant space-based methods were proposed to enhance consistency in area-class mapping and replicability in uncertainty modeling,as the former is achieved by imposing means while the latter is ensured by projecting spatio-temporal correlated residuals in discriminant space to geographic space through a mapping process.This paper explores discriminant models for error propagation in land cover change detection,followed by experiments based on bi-temporal remote sensing images.It was found that misclassification error propagation is effectively characterized with discriminant covariate-based stochastic simulation,where spatio-temporal interdependence is taken into account.

Estimation and Prediction of Gas Chromatography Retention Indices of Hydrocarbons in Straight-run Gasoline by Using Artificial Neural Network and Structural Coding Method

The molecular structures of hydrocarbons in straight run gasoline were numerically coded. The nonlinear quantitative relationship(QSRR) between gas chromatography(GC) retention indices of the hydrocarbons and their molecular structures were established by using an error back propagation(BP) algorithm. The GC retention indices of 150 hydrocarbons were then predicted by removing 15 compounds(as a test set) and using the 135 remained molecules as a calibration set. Through this procedure, all the compounds in the whole data set were then predicted in groups of 15 compounds. The results obtained by BP with the correlation coefficient and the standard deviation 0 993 4 and 16 54, are satisfied.

Computing mean fields with known Reynolds stresses at steady state

With the rising of modern data science,data-driven turbulence modeling with the aid of machine learning algorithms is becoming a new promising field.Many approaches are able to achieve better Reynolds stress prediction,with much lower modeling error(∈_(M)),than traditional Reynolds-averaged Navier-Stokes(RANS)models,but they still suffer from numerical error and stability issues when the mean velocity fields are estimated by solving RANS equations with the predicted Reynolds stresses.This fact illustrates that the error of solving the RANS equations(∈_(P))is also very important for a RANS simulation.In the present work,the error∈_(P)is studied separately by using the Reynolds stresses obtained from direct numerical simulation(DNS)/highly resolved large-eddy simulation to minimize the modeling error∈_(M),and the sources of∈_(P)are derived mathematically.For the implementations with known Reynolds stresses solely,we suggest to run an auxiliary RANS simulation to make a first guess onν_(t)^(*)and S_(ij)^(0).With around 10 iterations,the error of the streamwise velocity component could be reduced by about one-order of magnitude in flow over periodic hills.The present work is not to develop a new RANS model,but to clarify the facts that obtaining mean field with known Reynolds stresses is nontrivial and that the nonlinear part of the Reynolds stresses is very important in flow problems with separations.The proposed approach to reduce∈_(P)may be very useful for the a posteriori applications of the data-driven turbulence models.

An error analysis and optimization method for combined measurement with binocular vision

The accurate measurement of surfaces of large aviation components is vital for the assessment of manufacturing and assembly quality of such components.To satisfy the measurement requirement of large-size components,most current researches pay more attention to combined measurement methods utilizing different measuring instruments,but the related researches on error analysis and optimization methods are not taken enough attention.This paper proposes a combined laser-assisted measurement method with feature enhancement techniques,and it also develops an error propagation model of the main factors affecting the overall measurement error in detail.Firstly,the surface of a large-size component is measured by the measurement system at multiple stations.Secondly,a control point coordinate system is established as a bridge to unify all local measurement data into the global coordinate system.To improve the overall measurement accuracy,the pixel extraction error as a key factor causing the overall measurement error is analyzed in detail.Next,the error propagation model is established,and some optimization strategies of layout for minimizing measurement error and transformation error are researched.Finally,experiments are carried out to verify the effectiveness of the proposed method.The results show that the measurement error of the proposed method reaches 0.073%and 0.14%with a 1 D standard ruler and a flat plate,respectively.

A tip clearance prediction model for multistage rotors and stators in aero-engines

Tip clearances of multistage rotors and stators greatly affect aero-engines’ aerodynamic efficiency, stability and safety. The inevitable machining and assembly errors, as well as the complicated error propagation mechanism, cause overproof or non-uniform tip clearances. However, it is generally accepted that tip clearances are difficult to predict, even under assembly state. In this paper, a tip clearance prediction model is proposed based on measured error data. Some 3 D error propagation sub-models, regarding rotors, supports and casings, are built and combined. The complex error coupling relationship is uncovered using mathematical methods. Rotor and stator tip clearances are predicted and analyzed in different phase angles. The maximum, minimum and average tip clearances can be calculated. The proposed model is implemented by a computer program,and a case study illustrates its performance and verifies its feasibility. The results can be referred by engineers in assembly quality judgement and decision-making.

Performance analysis of a low-complexity nonorthogonal multiple access scheme in visible light communication downlinks using pulse modulations

Although Successive Interference Cancellation(SIC)decoding is widely adopted in Nonorthogonal Multiple Access(NOMA)schemes for the recovery of user data at acceptable complexity,the imperfect SIC would cause Error Propagation(EP),which can severely degrade system performance.In this work,we propose an SIC-free NOMA scheme in pulse modulation based Visible Light Communication(VLC)downlinks,including two types of users with different data rate requirements.Low bit-rate users adopt on-off keying,whereas high bit-rate ones use Multiple Pulse Position Modulation(MPPM).The soft decision decoding scheme is exploited by high bit-rate users to decode MPPM signals,which could fundamentally eliminate the detrimental effect of EP;the scheme is also easier and faster to execute compared with the conventional SIC decoding scheme.Expressions of the symbol error rate and achievable data rate for two types of users are derived.Results of the Monte Carlo simulation are provided to confirm the correctness of theoretical results.

Semi-analytical assessment of the relative accuracy of the GNSS/INS in railway track irregularity measurements

An aided Inertial Navigation System(INS)is increasingly exploited in precise engineering surveying,such as railway track irregularity measurement,where a high relative measurement accuracy rather than absolute accuracy is emphasized.However,how to evaluate the relative measurement accuracy of the aided INS has rarely been studied.We address this problem with a semi-analytical method to analyze the relative measurement error propagation of the Global Navigation Satellite System(GNSS)and INS integrated system,specifically for the railway track irregularity measurement application.The GNSS/INS integration in this application is simplified as a linear time-invariant stochastic system driven only by white Gaussian noise,and an analytical solution for the navigation errors in the Laplace domain is obtained by analyzing the resulting steady-state Kalman filter.Then,a time series of the error is obtained through a subsequent Monte Carlo simulation based on the derived error propagation model.The proposed analysis method is then validated through data simulation and field tests.The results indicate that a 1 mm accuracy in measuring the track irregularity is achievable for the GNSS/INS integrated system.Meanwhile,the influences of the dominant inertial sensor errors on the final measurement accuracy are analyzed quantitatively and discussed comprehensively.