A Novel Resource Allocation Algorithm based on Downlink and Uplink Decouple Access Scheme in Heterogeneous Networks

Traditional cellular network requires that a user equipment(UE) should associate to the same base station(BS) in both the downlink(DL) and the uplink(UL). Based on dual connectivity(DC) introduced in LTE-Advanced R12, DL/UL decouple access scheme has been proposed, which is especially suitable for heterogeneous networks(Het Nets). This paper is the pioneer to take the DL/UL decouple access scheme into consideration and develop a novel resource allocation algorithm in a two-tier Het Net to improve the total system throughput in the UL and ease the load imbalance between macro base stations(MBSs) and pico base stations(PBSs). A model is formulated as a nonlinear integer programming, and the proposed algorithm is a sub-optimal algorithm based on the graph theory. First, an undirected and weighted interference graph is obtained. Next, the users are grouped to let users with large mutual interferences to be assigned to different clusters. Then, the users in different clusters are allocated to different resource blocks(RBs) by using the Hungarian algorithm. Simulation results show that the proposed algorithm can provide great promotions for both the total system throughput and the average cell edge user throughput and successfully ease the load imbalance between MBSs and PBSs.

Efficient fully-decoupled and fully-discrete explicit-IEQ numerical algorithm for the two-phase incompressible flow-coupled Cahn-Hilliard phase-field model

In this paper,an efficient fully-decoupled and fully-discrete numerical scheme with second-order temporal accuracy is developed to solve the incompressible hydrodynamically coupled Cahn-Hilliard model for simulating the two-phase fluid flow system.The scheme is developed by combining the finite element method for spatial discretization and several effective time marching approaches,including the pressure-correction projection method for dealing with fluid equations and the explicit-invariant energy quadratization(explicit-IEQ)approach for dealing with coupled nonlinear terms.The obtained scheme is very efficient since it only needs to solve several decoupled,linear elliptic equations with constant coefficients at each time step.We also strictly prove the solvability and unconditional energy stability of the scheme,and verify the accuracy and stability of the scheme through plenty of numerical examples.

Decoupling Scheme for Virtual Synchronous Generator Controlled Wind Farms Participating in Inertial Response

In this paper,the dynamic coupling between the wind turbine rotor speed recovery(WTRSR)and inertial response of the conventional virtual synchronous generator(VSG)controlled wind farms(WFs)is analyzed.Three distinguishing features are revealed.Firstly,the inertial response characteristics of VSG controlled WFs(VSG-WFs)are impaired by the dynamic coupling.Secondly,when the influence of WTRSR is dominant,the inertial response characteristics of VSG-WFs are even worse than the condition under which WFs do not participate in the response of grid frequency.Thirdly,this phenomenon cannot be eliminated by only enlarging the inertia parameter of VSG-WFs,because the influence of WTRSR would also increase with the enhancement of inertial response.A decoupling scheme to eliminate the negative influence is then proposed in this paper.By starting the WTRSR process after inertial response period,the dynamic coupling is eliminated and the inertial response characteristics of WFs are improved.Finally,the effectiveness of the analysis and the proposed scheme are verified by simulation results.

Convergence of a Linearized and Conservative Difference Scheme for the Klein-Gordon-Zakharov Equation

A linearized and conservative finite difference scheme is presented for the initial-boundary value problem of the Klein-Gordon-Zakharov （KGZ） equation. The new scheme is also decoupled in computation, which means that no iteration is needed and parallel computation can be used, so it is expected to be more efficient in imple- mentation. The existence of the difference solution is proved by Browder fixed point theorem. Besides the standard energy method, in order to overcome the difficulty in obtaining a priori estimate, an induction argument is used to prove that the new scheme is uniquely solvable and second order convergent for U in the discrete L∞- norm, and for N in the discrete L2-norm, respectively, where U and N are the numeri- cal solutions of the KGZ equation. Numerical results verify the theoretical analysis.

Calibration-free and model-independent method for high-DOF image-based visual servoing

This paper presents a novel method to improve the performance of high-DOF image base visual servoing （IBVS） with an uncalibrated camera. Firstly, analysis and comparison between point-based and moment-based features are carried out with respect to a 4-DOF positioning task. Then, an extended interaction matrix （IM） related to the digital image, and a Kalman filter （KF）-based estimation algorithm of the extended IM without calibration and IM model are proposed. Finally, the KF-based algorithm is extended to realize an approximation to decoupled control scheme. Experimental results conducted on an industrial robot show that our proposed methods can provide accurate estimation of IM, and achieve similar performance compared with traditional calibration-based method. Therefore, the proposed methods can be applied to any robot control system in variational environments, and can realize instant operation to planar object with complex and unknown shape at large displacement.

Poisson Image Restoration via Transformed Network

There is a Poisson inverse problem in biomedical imaging,fluorescence microscopy and so on.Since the observed measurements are damaged by a linear operator and further destroyed by Poisson noise,recovering the approximate original image is difficult.Motivated by the decouple scheme and the variance-stabilizing transformation(VST)strategy,we propose a method of transformed convolutional neural network(CNN)to restore the observed image.In the network,the Conv-layers play the role of a linear inverse filter and the distribution transformation simultaneously.Furthermore,there is no batch normalization(BN)layer in the residual block of the network,which is devoted to tackling with the non-Gaussian recovery procedure.The proposed method is compared with state-of-the-art Poisson deblurring algorithms,and the experimental results show the effectiveness of the method.