Deep learning-based time-varying channel estimation with basis expansion model for MIMO-OFDM system

For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed to model the time-varying channel,which converts the channel estimation into the estimation of the basis coefficient.Specifically,the initial basis coefficients are firstly used to train the neural network in an offline manner,and then the high-precision channel estimation can be obtained by small number of inputs.Moreover,the linear minimum mean square error(LMMSE) estimated channel is considered for the loss function in training phase,which makes the proposed method more practical.Simulation results show that the proposed method has a better performance and lower computational complexity compared with the available schemes,and it is robust to the fast time-varying channel in the high-speed mobile scenarios.

Over-sampling basis expansion model aided channel estimation for OFDM systems with ICI

The rapid variation of channel can induce the intercarrier interference in orthogonal frequency-division multiplexing （OFDM） systems. Intercarrier interference will significantly increase the difficulty of OFDM channel estimation because too many channel coefficients need be estimated. In this article, a novel channel estimator is proposed to resolve the above problem. This estimator consists of two parts： the channel parameter estimation unit （CPEU）, which is used to estimate the number of channel taps and the multipath time delays, and the channel coefficient estimation unit （CCEU）, which is used to estimate the channel coefficients by using the estimated channel parameters provided by CPEU. In CCEU, the over-sampling basis expansion model is resorted to solve the problem that a large number of channel coefficients need to be estimated. Finally, simulation results are given to scale the performance of the proposed scheme.

The Observable Universe in a Simplified Cosmic Dynamic Model

This paper introduces a cosmic expansion model with constant speed of cosmic spatial expansion via derivation and simulations, where the speed of cosmic spatial expansion equals the speed of light c. Simulation results show that the earliest observable universe time is t = 5.084 Gyrs where the current universe time T = 13.82 Gyrs, and the furthest observable distance at the earliest observable universe time t is S = 0.632R, where R is the cosmic radius at current universe time T. The above constant cosmic expansion model does not consider the inflation period in the early universe according to the Big Bang model, nor does it considered the cosmic acceleration in recent universe time. However, this simplified cosmic expansion model could be a benchmark that will be helpful to understand the cosmic expansion and the observable universe. Based on the derivation and simulation of the constant cosmic expansion model, the threshold of observable universe for the accelerated cosmic expansion model can also be calculated similarly, as far as the speed of cosmic spatial expansion at any universe time t can be provided.

An experimental study of salt expansion in sodium saline soils under transient conditions

Salt expansion in sulfate saline soils that are widely distributed in northwestern China causes serious infrastructural damages under low-temperature conditions. However, the mechanism of salt expansion under low temperatures is not clear. In this study, we conducted a series of cooling experiments combined with salt crystallization to study this mechanism, and employed an ionic model to calculate the supersaturation ratio of the solution. During the experiments, the strength and the process of salt expansion were examined under different cooling rates and various crystal morphologies. The relationship between temperature and supersaturation ratio under transient conditions was also considered. Results indicate that the initial supersaturation ratio of a sodium sulfate solution is closely related to environmental conditions, and that this ratio decreases with slowing the cooling rates and stabilizing the crystal forms. Higher initial supersaturation ratios lead to an increased non-steady-state zone, resulting in less salt expansion. On the other hand, chloride ion content has a distinct influence on the crystallization supersaturation ratio of the sodium sulfate solution, and higher chloride ion content can inhibit salt expansion in sodium saline soils. These findings help explain salt expansion mechanisms in complex conditions such as seasonally frozen soils, and thus help search for improved methods of preventing salt expansion in sulfate saline soils.

Joint Multi-Domain Channel Estimation Based on Sparse Bayesian Learning for OTFS System

Since orthogonal time-frequency space(OTFS)can effectively handle the problems caused by Doppler effect in high-mobility environment,it has gradually become a promising candidate for modulation scheme in the next generation of mobile communication.However,the inter-Doppler interference(IDI)problem caused by fractional Doppler poses great challenges to channel estimation.To avoid this problem,this paper proposes a joint time and delayDoppler(DD)domain based on sparse Bayesian learning(SBL)channel estimation algorithm.Firstly,we derive the original channel response(OCR)from the time domain channel impulse response(CIR),which can reflect the channel variation during one OTFS symbol.Compare with the traditional channel model,the OCR can avoid the IDI problem.After that,the dimension of OCR is reduced by using the basis expansion model(BEM)and the relationship between the time and DD domain channel model,so that we have turned the underdetermined problem into an overdetermined problem.Finally,in terms of sparsity of channel in delay domain,SBL algorithm is used to estimate the basis coefficients in the BEM without any priori information of channel.The simulation results show the effectiveness and superiority of the proposed channel estimation algorithm.

Equatorial Wave Expansion of Instantaneous Flows for Diagnosis of Equatorial Waves from Data:Formulation and Illustration

This paper presents a method for expanding horizontal flow variables in data using the free solutions to the shallow-water system as a basis set. This method for equatorial wave expansion of instantaneous flows（EWEIF） uses dynamic constraints in conjunction with projections of data onto parabolic cylinder functions to determine the amplitude of all equatorial waves.EWEIF allows us to decompose an instantaneous wave flow into individual equatorial waves with a presumed equivalent depth without using temporal or spatial filtering a priori.Three sets of EWEIF analyses are presented. The first set is to confirm that EWEIF is capable of recovering the individual waves constructed from theoretical equatorial wave solutions under various scenarios. The other two sets demonstrate the ability of the EWEIF method to derive time series of individual equatorial waves from instantaneous wave fields without knowing a priori exactly which waves exist in the data as well as their spatial and temporal scales using outputs of an equatorial β-channel shallow-water model and ERA-Interim data. The third set of demonstrations shows, for the first time, the continuous evolutions of individual equatorial waves in the stratosphere whose amplitude is synchronized with the background zonal wind as predicted by quasi-biennial oscillation theory.

SOME ASYMPTOTIC INFERENCE IN QUASI-LIKELIHOOD NONLINEAR MODELS:A GEOMETRIC APPROACH

A modified Bates and Watts geometric framework is proposed for quasi\|likelihood nonlinear models in Euclidean inner product space.Based on the modified geometric framework,some asymptotic inference in terms of curvatures for quasi\|likelihood nonlinear models is studied.Several previous results for nonlinear regression models and exponential family nonlinear models etc.are extended to quasi\|likelihood nonlinear models.

一种新型钻孔采样数据管理方案

论述了在进行工程勘察软件设计中实际存在的一些问题。针对这些问题在对钻孔采样数据管理时,通过进行科学的数据空间的划分和结构重组提出了一种新型的钻孔数据管理方案,并成功地利用了的维数据处理功能解决了实际存在的困难。文章就该方案实现MAPGIS2.5的数据模型以及模型中使用的关键性技术分别进行了阐述。最后讨论了该模型可能存在的问题以及相应的解决方法。

LAI scale effect research based on compact airborne spectrographic imager data in the Heihe Oasis

As one of the key parameters for characterizing crop canopy structure, Leaf Area Index(LAI) has great significance in monitoring the crop growth and estimating the yield. However, due to the nonlinearity and spatial heterogeneity of LAI inversion model, there exists scale error in LAI inversion result, which limits the application of LAI product from different remote sensing data. Therefore, it is necessary to conduct studies on scale effect. This study was based on the Heihe Oasis, Zhangye city, Gansu province, China and the following works were carried out: Airborne hyperspectral CASI(Compact Airborne Spectrographic Imager) image and LAI statistic models were adopted in muti-scale LAI inversion. The overall difference of muti-scale LAI inversion was analyzed in an all-round way. This was based on two aspects, "first inversion and then integration" and "first integration and then inversion", and on scale difference characteristics of three scale transformation methods. The generation mechanism of scale effect was refined, and the optimal LAI inversion model was expanded by Taylor expansion. By doing so, it quantitatively analyzed the contribution of various inversion processes to scale effect. It was found that the cubic polynomial regression model based on NDVI(940.7 nm, 712 nm) was the optimal model, where its coefficient of determination R2 and the correlation coefficient of test samples R reached 0.72 and 0.936, respectively. Combined with Taylor expansion, it analyzed the scale error generated by LAI inversion model. After the scale effect correction of one-dimensional and twodimensional variables, the correlation coefficient of CCD-LAI(China Environment Satellite HJ/CCD images) and CASI-LAI products(Compact Airborne Spectro graphic Imager products) increased from 0.793 to 0.875 and 0.901, respectively. The mean value, standard deviation, and relative true value of the two went consistent. Compared with onedimensional variable correction method, the twodimensional method had a better correction result. This research used the effective information in hyperspectral data as sub-pixels and adopted Taylor expansion to correct the scale error in large-scale and low-resolution LAI product, achieving large-scale and high-precision LAI monitoring.

Deep Learning-Based Symbol Detection for Time-Varying Nonstationary Channels

The highly dynamic channel(HDC)in an extremely dynamic environment mainly has fast timevarying nonstationary characteristics.In this article,we focus on the most difficult HDC case,where the channel coherence time is less than the symbol period.To this end,we propose a symbol detector based on a long short-term memory(LSTM)neural network.Taking the sampling sequence of each received symbol as the LSTM unit's input data has the advantage of making full use of received information to obtain better performance.In addition,using the basic expansion model(BEM)as the preprocessing unit significantly reduces the number of neural network parameters.Finally,the simulation part uses the highly dynamic plasma sheath channel(HDPSC)data measured from shock tube experiments.The results show that the proposed BEM-LSTM-based detector has better performance and does not require channel estimation or channel model information.

The Cosmic Radius of Observable Universe

This paper introduces three cosmic expansion models with constant, decelerating and accelerating speed of expansion respectively. Then characters of these cosmic expansion models are compared. Based on these cosmic expansion models, the thresholds of observable universe are calculated via simulations, where the earliest observable cosmic radius R(tearliest) is always 0.368R (R is cosmic radius at current universe time) for any cosmic expansion models.

WRF/CHEM modeling of impacts of weather conditions modified by urban expansion on secondary organic aerosol formation over Pearl River Delta

In this paper, the online Weather Research and Forecasting and Chemistry （WRF/CHEM） model, coupled with urban canopy （UCM） and biogenic-emission models, is used to explore impacts of urban expansion on secondary organic aerosols （SOA） formation. Two scenarios of urban maps are used in WRF/CHEM to represent early 1990s （pre-urbanization） and current urban distribution in the Pearl River Delta （PRD）. Month-long simulation results using the above land-use scenarios for March 2001 show： （1） urbanization can increase monthly averaged temperatures by about 0.63 ℃, decrease monthly averaged 10-m wind speeds by 38%, increase monthly averaged boundary-layer depths by 80 m, and decrease monthly aver- aged water mixing ratio by 0.2g/kg. （2） Changes in meteorological conditions can result in detectable concentration changes of NOx, VOC, O3 and NO3 radicals. Urbanization decreases surface NOx and VOC concentrations by a maximum of 4 ppbv and 1.5 ppbv, respectively. Surface O3 and NO3 radical concentrations over major cities increase by about 2-4 ppbv and 4-12 pptv, respectively; areas with increasing O3 and NO3 radical concentrations generally coincide with the areas of temperature increase and wind speed reduction where NOx and VOC decrease. （3） Urbanization can induce 9% increase of SOA in Foshan, Zhongshan and west Guangzhou and 3% decrease in Shenzhen and Dongguan. Over PRD major cities, SOA from Aitken mode reduces by 30% but with more than 70% SOA from accumulate mode. Urbanization has stronger influence on SOA formation from Aitken mode. （4） Over the PRD, 55-65% SOA comes from aromatics precursors. Urbanization has strongest influence on aromatics precursors to produce SOA （14% increase）, while there is less influence on alkane precursors. Alkene precursors have negative contribution to SOA formation under urbanization situation.

THE SHRINKAGE OF EXPANSIVE CONCRETE FILLED STEEL TUBE AND ITS IMPROVEMENT METHOD

The shrinkage characteristics tics of expansive concrete filled steel tube (CFST) are analyzed, Cold shrinkage, creep and autogenous shrinkage are considered as the main reasons of causing CFST contraction. In accordance with the shrinkage characteristics of expansive CFST, a kind of energy-stored delayed expansive agent is exploited, which can not only compensate the shrinkage of the core concrete in every stages, but also make CFST expand according to the delayed expansion mechanism. As the result, the prestress loss weill be reduced and expansive energy will be utilized effectively.

A model for expansion ratio in liquid-solid fluidized beds

Liquid-solid fluidized beds are used in mineral processing industries to separate particles based on parti- cle size, density, and shape. Understanding the expanded fluidized bed is vital for accurately assessing its performance. Expansion characteristics of the fluidized bed were studied by performing several experi- ments with iron ore, chromite, quartz, and coal samples. Using water as liquid medium, experiments were conducted to study the effects of particle size, particle density, and superficial velocity on fluidized bed expansion. The experimental data were utilized to develop an empirical mathematical model based on dimensional analysis to estimate the expansion ratio of the fluidized bed in terms of particle character- istics, operating and design parameters. The predicted expansion ratio obtained from the mathematical model is in good agreement with the experimental data.

Deformation characterization method of typical double-walled turbine blade structure during casting process

To address the complex structures,large out-of-tolerance issues,and inconsistent quality of double-walled turbine blades,a mapping relationship between the structure and deformation was established based on a structural correlation study.Numerical simulations and pouring experiments were carried out based on the designed double-walled model,and a reliable displacement field model of the double-walled blade was established.A decoupling method for the displacement field of the double-walled blade castings was proposed,which decoupled the displacement field into bending,torsion,and expansion/shrinkage deformation vectors.Based on the displacement field analysis of the theoretical and physical models,an expansion/shrinkage model of double-walled blade structure castings was established.Furthermore,an experiment to determine the mapping relationship between double-walled construction and deformation was designed,which included the characteristic distribution distance and designed angle as structural parameters.The functional relationship between the deformation and the structural parameters was established based on a nonlinear regression method.

Doubly selective fading channel estimation in MIMO OFDM systems

High data transmission rates and high mobility give rise to time- and frequency-selectivity in wireless communication channels. This paper investigated time and frequency doubly selective channel estimation using pilot tones among Multi-Input Multi-Output （MIMO） orthogonal frequency division multiplexing （OFDM）. Firstly, a complex exponential basis expansion channel model （BECM） was introduced to represent doubly selective channel during an OFDM symbol period; then, based on BECM, an effective MIMO-OFDM doubly selective channel estimation method was presented; finally, the optimality in designing pilot tones parameters was done according to the minimization of channel estimation MSE, mainly including the number, the placement and the structure of pilot tones. Simulation results show that the proposed estimation method has good performance in doubly selective channel scenarios and confirms the theoretical analysis findings.

The Coiling of Split Dandelion Scape Induced by Cell Hygroscopicity

It is of great significance to study the water absorption and expansion of cells,which are essential for the growth and life regulation of plants,not only for understanding the complex life phenomena of plants,but also for the manufacture of biomimetic materials.The main purpose of this study is to shed light on the mechanism of a novel coiling phenomenon of the split dandelion scape soaked in water and the high concentration mannitol solution.We discovered that the difference between water absorption/dehydration capacities of inner cells and lateral cells of the split dandelion scape generates asymmetric expansion/contraction between inner and lateral layers,resulting two opposite coiled patterns.Analogous to the deformable hypothesis of the thermal expansion model,the water absorption-induced cell expansion model was proposed to explain the coiling process of the split dandelion scape.Both the simulation and experimental results revealed that the coiling of dandelion scape is strongly depended on the response of cells to the stimulation of the solution environment.Showing considerable potential load bearing capacity of plants,the coiling phenomenon can be an inspiration to the designs of soft robots and bionic sensors for humidity control.