APPLICATION OF FRF ESTIMATOR BASED ON ERRORS-IN-VARIABLES MODEL IN MULTI-INPUT MULTI-OUTPUT VIBRATION CONTROL SYSTEM

The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF. The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation. The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF （degree-of-freedom） hydraulic vibration table. The result shows that it is favorable to improve the control precision of the MIMO vibration control system.

A multi-input and multi-output design on automotive engine management system

Lookup table is widely used in automotive industry for the design of engine control units(ECU).Together with a proportional-integral controller,a feed-forward and feedback control scheme is often adopted for automotive engine management system(EMS).Usually,an ECU has a structure of multi-input and single-output(MISO).Therefore,if there are multiple objectives proposed in EMS,there would be corresponding numbers of ECUs that need to be designed.In this situation,huge efforts and time were spent on calibration.In this work,a multi-input and multi-out(MIMO) approach based on model predictive control(MPC) was presented for the automatic cruise system of automotive engine.The results show that the tracking of engine speed command and the regulation of air/fuel ratio(AFR) can be achieved simultaneously under the new scheme.The mean absolute error(MAE) for engine speed control is 0.037,and the MAE for air fuel ratio is 0.069.

Performance Improvement of Multi-User Multiple-Input Multiple-Output Protocol for WLAN

The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.

Input and output efficiency of urban agglomerations in China using DEA multi-stage model

In this study, we apply the data envelopment analysis(DEA) model to quantitatively measure the input and output efficiency of 19 urban agglomerations in China from 2011 to 2016. The results show that the input and output efficiency of urban agglomerations is relatively not high, only a small number of that reach the optimal DEA efficiency. It is clearly revealed that there are the regions from the east that presents the better performance, followed by regions from the central and the west. The peer counts show that Zhusanjiao is taken into account 12 times which shows the importance here of the Zhusanjiao model.Considering the values for radial movements and the slack movements, respective urban agglomeration has their improving orientation towards the capital slack, the labor slack or the land slack. It offers a scientific decision-making of for healthy urbanization and high quality development.

A Multi Input Multi Output Converter for Hybrid Energy Systems

Multi input and multi output converters are becoming popular because they are cost effective and compact. This paper proposes a multi input multi output converter for Grid-Solar power integration for uninterrupted power supply. The proposed converter uses four winding transformer with two primary windings and two secondary windings. The grid supply is connected to the first winding of transformer through rectifier-inverter for controlled power transfer. The solar energy is inverted and applied to the second winding of primary. Two output ports are considered. The circuit is designed to get zero current switching during turn-off and zero voltage switching during turn-on to alleviate the switching losses. The simulation results for the proposed configuration are presented in this paper.

A NOVEL ZERO-FORCING PRECODING METHOD FOR MULTI-CELL MIMO SYSTEMS

Precoding methods at the Base Station (BS) can be used to deal with the inter-cell interference and improve the signal quality of the user especially at the cell edge. In this paper, a novel Zero-Forcing (ZF) precoding method is proposed and investigated for multi-cell Multi-Input Multi-Output (MIMO) systems. We propose a relaxed ZF precoding method by relaxing the ZF criterion to some degree so that the inter-cell interference may not be zero. Complexity analysis shows that compared with the conventional ZF method, the additional computation complexity for the proposed method is trivial. Simulation results show that the proposed relaxed ZF method has better performance than the conventional ZF method in terms of the sum-rate, especially at low Signal to Noise Ratio (SNR).

MIMO-DCSK communication scheme and its performance analysis over multipath fading channels

The differential chaotic shift keying （DCSK） communication in multiple input multiple output （MIMO） multipath fading chan- nels is considered. A simple MIMO-DCSK communication scheme based on orthogonal multi-codes （OMCs） and equal gain combination （EGC） is proposed, in which OMCs are used to spread the same information bit at each transmitting antenna and the infor- mation bit is detected by EGC at receiving antenna. The OMCs are constructed from one chaotic sequence by means of othogo- nal space-time block coding （OSTBC）. The output signal-to-noise ratio （SNR） after EGC is given based on central limit theory （CLT）, and it can effectively exploit the spatial diversity of the underlying MIMO system. Simulation results show that the full spatial diversity gain is achieved without channel estimation in the MIMO-DCSK communication scheme and it performs better than MC-EGC for a large number of transmitting antennas.

Target estimation using MIMO radar with multiple subcarriers

This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.

Codebook selected beamforming algorithm for multiuser MIMO systems

For reducing the inter-user interference in multi-user multiple-input multiple-output（MU-MIMO） wireless communication systems,e.g.,MIMO-orthogonal frequency division multiplexing（MIMO-OFDM） systems,it is often desirable to the complex preprocessing at the transmitter.This paper proposes a multi-user beamforming algorithm with sub-codebook selection.Based on the minimal leakage criterion,the codebook selection,limited feed-forward and minimum mean square error（MMSE） detection are combined in the proposed algorithm.This avoids the complex channel matrix decomposition and inversion.Consequently,the computational complexity at the transmitter is significantly reduced.Simulation results show that the proposed algorithm performs better than existing beamforming algorithms.

Evaluation of Linear Precoding Schemes for Cooperative Multi-Cell MU MIMO in Future Mobile Communication Systems

In Mobile Communication Systems, inter-cell interference becomes one of the challenges that degrade the system’s performance, especially in the region with massive mobile users. The linear precoding schemes were proposed to mitigate interferences between the base stations (inter-cell). These schemes are categorized into linear and non-linear;this study focused on linear precoding schemes, which are grounded into three types, namely Zero Forcing (ZF), Block Diagonalization (BD), and Signal Leakage Noise Ratio (SLNR). The study included the Cooperative Multi-cell Multi Input Multi Output (MIMO) System, whereby each Base Station serves more than one mobile station and all Base Stations on the system are assisted by each other by shared the Channel State Information (CSI). Based on the Multi-Cell Multiuser MIMO system, each Base Station on the cell is intended to maximize the data transmission rate by its mobile users by increasing the Signal Interference to Noise Ratio after the interference has been mitigated due to the usefully of linear precoding schemes on the transmitter. Moreover, these schemes used different approaches to mitigate interference. This study mainly concentrates on evaluating the performance of these schemes through the channel distribution models such as Ray-leigh and Rician included in the presence of noise errors. The results show that the SLNR scheme outperforms ZF and BD schemes overall scenario. This implied that when the value of SNR increased the performance of SLNR increased by 21.4% and 45.7% for ZF and BD respectively.

Input series out putparallel based multi-modular boost half bridge DC-DC converter with a dynamic control scheme

Multi-modular system plays an important role in power system architecture because low voltage and low power converters can be connected in any combination parallel or series at input/ output side in order to obtained any given power system specifications. Multi-modular boost haft bridge DC-DC converter in the configuration of input series output parallel has been investigated in this paper. The boost half bridge DC-DC converters are connected in input series output parallel con- figuration in order to achieve equal input voltage sharing and output current sharing between the con- verters. This can be achieved with the help of dynamic control scheme which consists of two loops, a voltage loop and a current loop, for each module. Dynamic behavior of multi-modular converter configuration has been observe by varying the load condition. Moreover, the results obtained through multi-modular converter describe that the system has good dynamic and steady state response. Al- though two converter modules are focused in this paper but it can be modified to any number of modules.

Auxiliary Model Based Multi-innovation Stochastic Gradient Identification Methods for Hammerstein Output-Error System

Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to realize the identification and separation of the Hammerstein model.As a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable parameters.The auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein model.The auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation length.The simulation results show the efficiency of the proposed method.

Triple-Polarized Multi-User Mimo-Idma System under Correlated Fading Channel

A multiple-input multiple-output interleave division multiple access (MIMO-IDMA) system with Triple Polarized Division Multiplexing (TPDM) is presented in this paper. The present methodology replaces three independent linearly polarized antennas with a single triple polarized antenna at both the transmitter and receiver. The users in the communication link are accommodated and separated using a user-specific interleaver combined with low rate spreading sequence. To eliminate the effects of multi-stream interference (MSI), minimum mean square error (MMSE) algorithm based on successive interference cancellation (SIC) Multi-user detection (MUD) technique is employed at the receiver. Furthermore, log-maximum a posteriori probability (MAPP) decoding algorithm is implemented at the mobile stations (MSs) to overcome the effects of multi-user interference (MUI) effects. The paper also evaluates the effects of coded MIMO-IDMA in the downlink communication by adopting the Stanford University Interim (SUI) and Long-term Evolution (LTE)channel model specifications. In comparison with the traditional uncoded system, the present solution considering turbo coded triple-polarized MIMO-IDMA system with iterative decoding algorithm provides better bit error rate (BER) with reduced signal to noise ratio (SNR). The simulation results also show that though the SNR requirement is higher for the proposed technique compared to the conventional uni-polarized antenna based MIMO-IDMA system, it gives the advantages of achieving higher data rate with reduced cost and space requirements in the context of a downlink (DL).

重叠阵元时分复用MIMO雷达多目标参数估计方法研究

针对多普勒-角度耦合和速度模糊问题,该文提出一种基于重叠阵元MIMO阵列的多目标参数估计方法。该方法基于虚拟孔径原理,在传统MIMO天线阵列中引入重叠阵元,构建重叠阵元MIMO天线阵列。通过在角度快速傅里叶变换(FFT)算法中引入循环迭代的方法估计阵列位置参数,利用重叠阵元回波信号的相位差值进行频率估计。同时,引入频谱搬移方法对速度区间进行转换,实现多目标的距离和速度估计。通过蒙特卡罗仿真实验,信噪比15 dB的条件下,解模糊正确率为100%,速度误差为0.1 m/s,角度误差为0.1°。基于城市交通场景采集的车辆数据集进行测试,测试结果表明,该方法能够实现对车辆目标的速度和角度精确估计,可满足交通雷达对车辆信息监测的实时性和准确性需求。

5G-R高铁车站场景MIMO天线阵列结构与传输性能研究

面向5G-R高铁车站应用场景,在2155~2165 MHz频段采用射线跟踪仿真技术,对4种不同天线阵列排布方式的MIMO系统多层传输性能进行对比研究。通过研究采取不同收发端天线阵列排布方式时的信道相关性,计算每个接收点位所能达到的MIMO系统最大传输层数,获取各层数对应的信噪比,计算在不同调制方式、不同天线排布方式下每个接收点位的下行峰值传输速率,确定面向5G-R高铁车站场景的MIMO系统最佳传输层数。仿真验证结果表明,面向5G-R频段高铁车站应用场景,基站端采用线阵、车载端采用方阵排列,可取得最佳峰值传输速率。研究结果可为5G-R专网建设中高铁车站部署MIMO系统提供技术积累和理论依据。

Strategies for multi-step-ahead available parking spaces forecasting based on wavelet transform

A new methodology for multi-step-ahead forecasting was proposed herein which combined the wavelet transform(WT), artificial neural network(ANN) and forecasting strategies based on the changing characteristics of available parking spaces(APS). First, several APS time series were decomposed and reconstituted by the wavelet transform. Then, using an artificial neural network, the following five strategies for multi-step-ahead time series forecasting were used to forecast the reconstructed time series: recursive strategy, direct strategy, multi-input multi-output(MIMO) strategy, DIRMO strategy(a combination of the direct and MIMO strategies), and newly proposed recursive multi-input multi-output(RECMO) strategy which is a combination of the recursive and MIMO strategies. Finally, integrating the predicted results with the reconstructed time series produced the final forecasted available parking spaces. Three findings appear to be consistently supported by the experimental results. First, applying the wavelet transform to multi-step ahead available parking spaces forecasting can effectively improve the forecasting accuracy. Second, the forecasting resulted from the DIRMO and RECMO strategies is more accurate than that of the other strategies. Finally, the RECMO strategy requires less model training time than the DIRMO strategy and consumes the least amount of training time among five forecasting strategies.

Multi-dimensional blind separation method for STBC systems

Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by using the ordinary independent component analysis （ICA）. This method cannot work when specific complex modulations are employed since the assumption of mutual independence cannot be satisfied. The analysis shows that source signals, which are group-wise independent and use multi-dimensional ICA （MICA） instead of ordinary ICA, can be applied in this case. Utilizing the block-diagonal structure of the cumulant matrices, the JADE algorithm is generalized to the multidimensional case to separate the received data into mutually independent groups. Compared with ordinary ICA algorithms, the proposed method does not introduce additional ambiguities. Simulations show that the proposed method overcomes the drawback and achieves a better performance without utilizing coding information than channel estimation based algorithms.

Web Tension Regulation of Multispan Roll-to-Roll System using Integrated Active Dancer and Load Cells for Printed Electronics Applications

The mass production of primed electronics can be achieved by roll-to-roll（R2R） printing system, so highly accurate web tension is required that can minimize the register error and keep the thickness and roughness of printed devices in limits. The web tension of a R2R system is regulated by the use of integrated load cells and active dancer system for printed electronics applications using decentralized multi-input-single-output（MISO） regularized variable learning rate backpropagation artificial neural networks. The active dancer system is used before printing system to reduce disturbances in the web tension of process span. The classical PID control result in tension spikes with the change in roll diameter of winder and unwinder rolls. The presence of dancer in R2R system shows that improved web tension control in printing span and the web tension can be enhanced from 3.75 N to 4.75 N. The overshoot of system is less than ±2.5 N and steady state error is within ± 1 N where load cells have a signal noise of ±0.7 N. The integration of load cells and active dancer with self-adapting neural network control provide a solution to the web tension control of multispan roll-to-roll system.

基于降维变换的低复杂度双基地EMVS-MIMO雷达高分辨多维参数估计

针对当前算法在实现双基地电磁矢量传感器多输入多输出(electromagnetic vector sensors multiple input multiple output,EMVS-MIMO)雷达的多维参数估计时计算代价较高的问题,通过利用降维变换技术来实现低复杂度的角度参数和极化参数求解。针对阵列接收数据维度较大问题,通过设计相应的波束空间变换矩阵来实现对阵列接收数据的降维处理。针对算法本身的较高计算复杂度问题,采用低计算复杂度的平行因子分解算法。所提算法能够精确地实现对发射因子矩阵和接收因子矩阵的求解。同时,通过新的旋转不变关系构建新的估计信号参数,可以实现对发射/接收俯仰角的求解。进一步,发射/接收方位角、发射/接收极化角和发射/接收极化相位差的估计可以通过发射/接收空间响应矩阵的重构来实现。仿真实验结果表明,所提算法在降低计算复杂度的同时能够保持优越的多维参数估计性能。

双频段MIMO印刷偶极子天线设计

该文设计一款双频段MIMO印刷偶极子天线系统,由2个天线单元组成,每个辐射单元由2个不同尺寸的微带开口环组成。通过在地板上开方形栅格,减少了2个天线单元之间的耦合,提高天线端口间的隔离度,在2个工作频段内隔离度均高于25 dB。