An improved wind retrieval algorithm for the HY-2A scatterometer

Since January 2012,the National Satellite Ocean Application Service has released operational wind products from the HY-2A scatterometer(HY2-SCAT),using the maximum-likelihood estimation(MLE) method with a median filter. However,the quality of the winds retrieved from HY2-SCAT depends on the sub-satellite cross-track location,and poor azimuth separation in the nadir region causes particularly low-quality wind products in this region. However,an improved scheme,i.e.,a multiple solution scheme(MSS) with a two-dimensional variational analysis method(2DVAR),has been proposed by the Royal Netherlands Meteorological Institute to overcome such problems. The present study used the MSS in combination with a 2DVAR technique to retrieve wind data from HY2-SCAT observations. The parameter of the empirical probability function,used to indicate the probability of each ambiguous solution being the "true" wind,was estimated based on HY2-SCAT data,and the 2DVAR method used to remove ambiguity in the wind direction. A comparison between MSS and ECMWF winds showed larger deviations at both low wind speeds(below 4 m/s) and high wind speeds(above 17 m/s),whereas the wind direction exhibited lower bias and good stability,even at high wind speeds greater than 24 m/s. The two HY2-SCAT wind data sets,retrieved by the standard MLE and the MSS procedures were compared with buoy observations. The RMS error of wind speed and direction were 1.3 m/s and 17.4°,and 1.3 m/s and 24.0° for the MSS and MLE wind data,respectively,indicating that MSS wind data had better agreement with the buoy data. Furthermore,the distributions of wind fields for a case study of typhoon Soulik were compared,which showed that MSS winds were spatially more consistent and meteorologically better balanced than MLE winds.

Energy Efficient Transmission in Underlay CR-NOMA Networks Enabled by Reinforcement Learning

In order to improve the energy efficiency(EE)in the underlay cognitive radio(CR)networks,a power allocation strategy based on an actor-critic reinforcement learning is proposed,where a cluster of cognitive users(CUs)can simultaneously access to the same primary spectrum band under the interference constraints of the primary user(PU),by employing the non-orthogonal multiple access(NOMA)technique.In the proposed scheme,the optimization of the power allocation is formulated as a non-convex optimization problem.Additionally,the power allocation for different CUs is based on the actor-critic reinforcement learning model,in which the weighted data rate is set as the reward function,and the generated action strategy(i.e.the power allocation)is iteratively criticized and updated.Both the CU’s spectral efficiency and the PU’s interference constrains are considered in the training of the actor-critic reinforcement learning.Furthermore,the first order Taylor approximation as well as other manipulations are adopted to solve the power allocation optimization problem for the sake of considering the conventional channel conditions.According to the simulation results,we find that our scheme could achieve a higher spectral efficiency for the CUs compared to a benchmark scheme without learning process as well as the existing Q-learning based method,while the resultant interference affecting the PU transmission can be maintained at a given tolerated limit.

Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks

Non-orthogonal multiple access(NOMA)is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner.NOMA allows multiple terminals to share the same resource unit at the same time.The receiver usually needs to configure successive interference cancellation(SIC).The receiver eliminates co-channel interference(CCI)between users and it can significantly improve the system throughput.In order to meet the demands of users and improve fairness among them,this paper proposes a new power allocation scheme.The objective is to maximize user fairness by deploying the least fairness in multiplexed users.However,the objective function obtained is non-convex which is converted into convex form by utilizing the optimal Karush-Kuhn-Tucker(KKT)constraints.Simulation results show that the proposed power allocation scheme gives better performance than the existing schemes which indicates the effectiveness of the proposed scheme.

Seismic Ground Motion Zoning Maps of the Pangxi Region

The seismotectonic environment and seismic activity in Southwest China region were studied based on new data and new results obtained during the Eighth and Ninth Five-Year Plans, the seismic areas and zones and potential seismic source zones were determined, and the relation between seismic activity parameters and ground motion attenuation was determined. Finally the seismic ground motion zoning maps of the Pangxi region was compiled by using the multi-parameter and multi-scheme method.

Cells grouping scheme against pilot contamination in large scale antennas system

The influence of cells groupings factor to the performance of the cells groupings time-shift pilot scheme is researched for the multiple cells large scale antennas systems（LSAS）. The former researches have confirmed that the cells groupings time-shift pilots scheme is effective to reduce inter-cell interference, especially pilot contamination, which results from the pilot reuse in adjacent cells. However, they have not specified reasonable cells groupings factor, which plays a critical role in the general performance of the LSAS. Therefore, this problem is researched in details. The time for reverse-link data transmission will be compressed, when the groupings factor surpasses a certain range. Thus it is not always beneficial to increase the cells groupings factor without limitation. Furthermore,a reasonable cells groupings factor is deduced from the perspective of optimization to enhance the system performance. Simulations verify the proposed cell grouping factor.

MULTIPLICATIVE EXTRAPOLATION METHOD FOR CONSTRUCTING HIGHER ORDER SCHEMES FOR ORDINARY DIFFERENTIAL EQUATIONS

In this paper, we develop a new technique called multiplicative extrapolation method which is used to construct higher order schemes for ordinary differential equations. We call it a new method because we only see additive extrapolation method before. This new method has a great advantage over additive extrapolation method because it keeps group property. If this method is used to construct higher order schemes from lower symplectic schemes, the higher order ones are also symplectic. First we introduce the concept of adjoint methods and some of their properties. We show that there is a self-adjoint scheme corresponding to every method. With this self-adjoint scheme of lower order, we can construct higher order schemes by multiplicative extrapolation method, which can be used to construct even much higher order schemes. Obviously this constructing process can be continued to get methods of arbitrary even order.

An all-optical matrix multiplication scheme with non-linear material based switching system

Optics is a potential candidate in information, data, and image processing. In all-optical data and information processing, optics has been used as information carrying signal because of its inherent advantages of parallelism. Several optical methods are proposed in support of the above processing. In many algebraic, arithmetic, and image processing schemes fundamental logic and memory operations are conducted exploring all-optical devices. In this communication we report an all-optical matrix multiplication operation with non-linear material based switching circuit.

Multi-Product Expansion with Suzuki’s Method: Generalization

In this paper we discuss the extension to exponential splitting methods withrespect to time-dependent operators. We concentrate on the Suzuki’s method, whichincorporates ideas to the time-ordered exponential of [3, 11, 12, 34]. We formulate themethods with respect to higher order by using kernels for an extrapolation scheme. Theadvantages include more accurate and less computational intensive schemes to specialtime-dependent harmonic oscillator problems. The benefits of the higher order kernelsare given on different numerical examples.