MIMO ARQ无线通信系统中发送天线选择的联合优化

为了获得MIMO系统的巨大容量,同时降低系统的实现代价,人们越来越重视天线选择技术.文章基于MIMO ARQ无线通信系统,针对发送天线选择和预编码技术的联合使用,依照系统容量,提出了一种次优的联合优化算法.这一算法把天线选择和预编码分成2个部分完成：在重发数据时,首先利用先前发送时的相关信息和当前的信道信息来选择发送天线;在完成天线选择后,再采用注水算法来优化预编码矩阵.仿真表明,这一算法所获得的信道容量十分接近穷举法所得到的最大信道容量.     

CARMA-model-based j-step-ahead prediction for MIMO systems

The single-input single-output (SISO) j-step-ahead predictor for generalized predictive control (GPC) controllers was traditionally derived using the polynomial approach through the Diophantine equations. An equivalent version of the predictor in a state-space form is available in the literature. In this paper, a z-domain analysis of the multiple input multiple output (MIMO) extension of the state-space predictor is carried out, and then an MIMO j-step-ahead predictor in polynomial form based on the controlled autoregressive moving average model is derived. The predictor enables us to simplify the GPC algorithm design for multivariable systems. In the SISO case the predictor is just the traditional GPC predictor, therefore this paper gives rigorous proof of the equivalence between the traditional GPC predictor and the state-space predictor. Translated from Control and Decision, 2006, 21 (9): 1050–1053 [译自: 控制与决策]     

弱场自解耦极近距离MIMO天线设计

为了抑制极近距离多输入多输出(MIMO)天线单元间的强耦合,提出了一种将MIMO天线单元的馈电位置邻近排布在激励天线单元电磁场弱场区的解耦方法。其中电磁场弱场区域主要通过改变微带天线的馈电结构产生。为了满足项目特殊需求,首先,设计了一款边到边距离为1 mm(0.011λ₀,λ₀为中心频率3.5 GHz时的自由空间波长)的二单元MIMO天线,仿真和实测结果表明,相比参考天线,利用该解耦方法使MIMO天线在工作频段内的隔离度最大改善了42 dB。进一步地,将改进天线单元沿120°分布构成一款三单元MIMO天线,该天线边到边最小距离仍然为1 mm。实验结果显示在工作频段3.45～3.55 GHz范围内,单元间的耦合抑制大于30 dB;在中心频率3.5 GHz处,测试的最大隔离度为52 dB,且各天线单元的反射系数不受影响。值得一提的是,所提出的解耦方法与传统方法相比,在减少互耦时不需要额外的解耦电路和结构,具有良好的应用前景。     

A micro-scaled graphene-based tree-shaped wideband printed MIMO antenna for terahertz applications

Journal of Computational Electronics - A tree-shaped graphene-based microstrip multiple-input and multiple-output (MIMO) antenna for terahertz applications is proposed. The proposed MIMO antenna is...     

Adaptive control design for MIMO switched nonlinear systems with full state constraints

This paper presents an adaptive fuzzy control approach of multiple‐input–multiple‐output (MIMO) switched uncertain systems, which involve time‐varying full state constraints (TFSCs) and unknown disturbances. In the design procedure, the fuzzy logic systems are adopted to approximate the unknown functions in the systems. The adaptive fuzzy controller is set up by backstepping technique. According to the tangent barrier Lyapunov function (BLF‐Tan), a novel adaptive MIMO switched nonlinear control algorithm is designed. Under the rule of arbitrary switchings and the proposed control laws, it is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of zero with TFSCs. Furthermore, the simulation example validates the effectiveness of presented control strategy.     

大规模MIMO系统下的低复杂度迫零预编码技术

针对大规模天线技术导致传统迫零(zero-forcing,ZF)预编码复杂度上升的问题,提出了一种低复杂度预编码技术.首先利用对称超松弛迭代(semi-iteration symmetric successive overrelaxation method,SSOR)技术优化信道矩阵求逆复杂度的问题;然后利用切比雪夫半...     

Multi-user MIMO systems: the future in the making

Very few technologies have had as much impact on the trajectory of evolution of wireless communication systems as multiple input multiple output (MIMO) systems. MIMO systems have already been employed in the existing 802.11n and 802.16e standards resulting in a huge leap in their achievable rates. A relatively recent idea of extending the benefits of MIMO systems to multi-user scenarios seems promising in the context of achieving high data rates envisioned for future cellular standards after 3G. Although substantial research has been done on the theoretical front, recent focus is on making multi-user MIMO (MU-MIMO) practically realizable. It offers an enormous scope for further research in the coming years. As in the case of any evolving technology in communication systems, the literature concerning MU-MIMO systems involves complex mathematical analysis, making it difficult for an ordinary reader to comprehend. This article aims at giving an insight into MU-MIMO systems---its concept, fundamentals, and trends including an overview of important research results. It is intended at giving a good start to amateurs interested in being part of the community that shapes the future of wireless systems.     

Analysis of maximal-ratio of transmitting/receiving antenna selection with perfect and partial channel information

To improve system performance and reduce the complexity and cost of receiver hardware, we investigated a new multiple-input multiple-output (MIMO) scheme combining maximal-ratio transmitting and receiver antenna selection (MRT/RAS). In this scheme, a single receiving antenna, which maximizes the signalto-noise ratio (SNR) at the receiver, is selected for demodulation. The closed-form outage probability and the bit error rate (BER) of the MRT/RAS system are both presented. The simulation demonstrates that the MRT/RAS scheme can achieve a full diversity order as if all the receiving antennas were used. It is shown that the MRT/RAS scheme outperforms some more complex space-time codes of the same spectral efficiency. The analytical results are verified by simulation. In the end, we also analyze the MRT/RAS system based on partial channel information.     

U-model based learning feedforward control of MIMO nonlinear systems

In this paper, a learning feedforward controller (LFFC) using the U-model is proposed for a better tracking control of multivariable nonlinear systems over a finite time interval. The multivariable system is modelled using the U-model and the LFFC is established using Newton–Raphson method. U-model significantly simplifies the online synthesis of the feedforward control law. The proposed technique is verified on 2-link robot manipulator in real-time. The performance of the proposed U-model based LFFC is compared with a number of schemes under varying load conditions.     

Adaptive neural dynamic surface control of MIMO stochastic nonlinear systems with unknown control directions

In this paper, an adaptive neural output‐feedback control approach is considered for a class of uncertain multi‐input and multi‐output (MIMO) stochastic nonlinear systems with unknown control directions. Neural networks (NNs) are applied to approximate unknown nonlinearities, and K‐filter observer is designed to estimate unavailable system's states. Due to utilization of Nussbaum gain function technique in the proposed approach, the singularity problem and requirement to prior knowledge about signs of high‐frequency gains are removed, simultaneously. Razumikhin functional method is employed to deal with unknown state time‐varying delays, so that the offered control approach is free of common assumptions on derivative of time‐varying delays. Also, an adaptive neural dynamic surface control is developed; hence, explosion of complexity in conventional backstepping method is eliminated, effectively. The boundedness of all the resulting closed‐loop signals is guaranteed in probability; meanwhile, convergence of the tracking errors to adjustable compact set in the sense of mean quartic value is also proved. Finally, simulation results are shown to verify and clarify efficiency of the offered approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Improved Tomlinson-Harashima precoding for the downlink of multi-user MIMO systems

By pre-equalizing the interlayer interference at the transmitter, the Tomlinson-Harashima precoding (THP) algorithm provides a solution for the downlink of multi-user multiple-input multiple-output (MIMO) systems, in which, because of the absence of cooperation among mobiles, receiver-based layer-separation algorithms cannot be implemented. In this paper, a new THP algorithm using the minimum mean-square error (MMSE) criterion is developed for the downlink of multi-user MIMO systems. This algorithm, called the MMSE THP algorithm, provides significant performance improvement compared to the zero-forcing (ZF) THP algorithm discussed in the literature. Moreover, ordering of the rows of the channel matrix is found to be important to the THP system performance, and the way in which this ordering affects the system structure is presented. An ordering lemma that generalizes the conditions, under which the ?best-first? ordering is optimal, is introduced.With this lemma it is proved that the ?best-first? ordering method achieves the optimal order in the minimax noise-variance sense for the ZF THP and the optimal order in the minimax error-variance sense for the MMSE THP. Simulation results show the performance advantage attained by the MMSE THP and the optimal ordering.     

Rejection of unknown periodic disturbances for continuous‐time MIMO systems with dynamic uncertainties

Rejection of unknown periodic disturbances in multi‐channel systems has several industrial applications that include aerospace, consumer electronics, and many other industries. This paper presents a design and analysis of an output‐feedback robust adaptive controller for multi‐input multi‐output continuous‐time systems in the presence of modeling errors and broadband output noise. The trade‐off between robust stability and performance improvement as well as practical design considerations for performance improvements are presented. It is demonstrated that proper shaping of the open‐loop plant singular values as well as over‐parameterizing the controller parametric model can significantly improve performance. Numerical simulations are performed to demonstrate the effectiveness of the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive inverse control of unmodeled stable SISO and MIMO linear systems

Adaptive‐signal‐processing techniques have been employed with great success in such applications as: system identification, channel equalization, statistical prediction and noise/echo cancellation. From a mathematical point of view, there is little difference between these applications and the types of operations required by control systems to control a dynamical system. This paper presents an approach to control systems called adaptive inverse control in which adaptive‐signal‐processing techniques are used throughout. Adaptive inverse control comprises three simultaneous processes. The plant is automatically modeled using adaptive system identification techniques. The dynamic response of the system is adaptively controlled using the resulting model and methods related to channel equalization. Adaptive disturbance canceling is performed using methods similar to noise canceling. The method applies directly to stable single‐input single‐output (SISO) and multi‐input multi‐output (MIMO) plants, and does not require an a priori model of the system. If the plant is unstable, it must first be stabilized using conventional feedback. This implies that at least a rudimentary model need be made if the plant is unstable. Once the plant is stabilized, adaptive inverse control may be applied to the stabilized system. Copyright © 2002 John Wiley & Sons, Ltd.     

Experimental verification of massive antenna systems employing parallelogram planar arrays

This paper experimentally verifies how the parallelogram planar array (PPA) can improve the space division multiplexing (SDM) performance of multiuser massive multiple‐input multiple‐output (MIMO) in line‐of‐sight (LOS) channels. PPA can reduce the spatial channel correlation (inter‐user correlation) without any increase in processing load. Channel state information (CSI) of up to 94 antenna elements is measured with simplified test equipment in an outdoor propagation environment. Assessment of the measured CSI confirms the effectiveness of PPA in terms of reduced spatial channel correlation and its higher order SDM ability with simplified user scheduling.     

Observer‐based adaptive neural control of uncertain MIMO nonlinear systems with unknown control direction

This paper investigates adaptive neural network output feedback control for a class of uncertain multi‐input multi‐output (MIMO) nonlinear systems with an unknown sign of control gain matrix. Because the system states are not required to be available for measurement, an observer is designed to estimate the system states. In order to deal with the unknown sign of control gain matrix, the Nussbaum‐type function is utilized. By using neural network, we approximated the unknown nonlinear functions and perfectly avoided the controller singularity problem. The stability of the closed‐loop system is analyzed by using Lyapunov method. Theoretical results are illustrated through a simulation example. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive regulation of MIMO linear systems against unknown sinusoidal exogenous inputs

This paper deals with the adaptive regulation problem in linear multi‐input multi‐output systems subject to unknown sinusoidal exogenous inputs, where the frequencies, amplitudes, and phases of the sinusoids are unknown and where the number of sinusoids is assumed to be known. The design of an adaptive regulator for the system under consideration is performed within a set of Q‐parameterized stabilizing controllers. To facilitate the design of the adaptive regulator, triangular decoupling is introduced in part of the closed‐loop system dynamics. This is achieved through the proper selection of the controller state feedback gain and the structure of the Q parameter. Regulation conditions are then presented for the case where the sinusoidal exogenous input properties are known. For the case where the sinusoidal exogenous input properties are unknown, an adaptation algorithm is proposed to tune the Q parameter in the expression of the parameterized controller. The online tuning of the Q parameter allows the controller to converge to the desired regulator. Convergence results of the adaptation algorithm are presented. A simulation example involving a retinal imaging adaptive optics system is used to illustrate the performance of the proposed adaptive system. Copyright © 2008 John Wiley & Sons, Ltd.     

Optimal conductor selection for radial distribution systems

In this paper, an algorithm is proposed for selecting the optimum size of conductors of feeder sigments of radial distribution networks. The optimal size of conductor determined by load flow method is applied to the optimal distance radial distribution network. The conductor, which is determined by the proposed method, will maximize the total saving in cost of conducting material and cost of energy losses and maintain acceptable voltage levels in radial distribution systems. An attempt has been made to reduce the losses in the existing radial distribution networks by optimizing the size of the branch conductor. The effectiveness of the proposed method is illustrated with suitable examples.     

基于快速输出采样的MIMO离散系统变结构控制

针对一类含有界扰动的多输入多输出离散时间线性系统,采用快速输出采样反馈技术（FOS）,设计了离散变结构控制器,并给出了确定控制器参数的方法,且未知扰动的界已知但不要求满足匹配条件。理论分析表明,所设计的控制器能保证闭环系统是有界稳定的,无需利用系统的状态作为反馈而仅利用输出采样来设计控制器,因而具有较强的实用性且易于实现。通过仿真验证了结论的有效性。     

Game theory‐based MIMO cognitive radio systems: Accuracy examination

The Letter proposes a precise mathematical expression for game theory‐based multiple‐input multiple‐output (MIMO) cognitive radio systems. The sum of information rates and the network utility are maximized, providing an accurate examination. Constraining the interference signals caused by the secondary transmitters on the primary receivers in the underlay scenario also needs to be addressed. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

小电流接地选线技术的分析

结合国内小电流选线装置动作准确率低的实际情况,给出了目前小电流接地选线原理的分类和选线装置的使用现状,阐述了单相接地后系统中零序电流的流向特征,小电流接地选线中存在地问题和今后的研究方向.