结合凸优化的宽带MIMO系统接收天线选择

研究宽带多输入多输出(MIMO)系统中的接收天线选择技术。基于添加循环前缀辅助的宽带MIMO系统数学模型,利用邻近子载波间的相关性,设计次优的天线选择准则,并对结合凸优化方法的接收天线选择算法进行改进。仿真结果表明,次优准则可以获得与最优准则几乎相同的性能,改进的接收天线选择算法以增加较少计算量为代价,提高了系统的容量性能。     

Development of decoupling scheme for high order MIMO process based on PSO technique

Multiple-input multiple-output (MIMO) with N Input/ N Output processes are characterized by significant interactions between their inputs and outputs. The control of MIMO processes is usually implemented using sets of single-input single-output (SISO) loop controllers, which requires proper input–output pairing and development of decoupling compensator unit. In this paper, a generalized decoupling technique is proposed. The proposed technique uses relative gain array (RGA) to select proper pairing and particle swarm optimization (PSO) technique to estimate the optimal elements’ values of steady state decoupling compensation matrix constituting the decoupling compensator unit. The proposed technique is applied on 4 Input/ 4 Output two coupled distillation columns process, it proves remarkable success in minimizing the interaction between every input and all outputs except that output has been proper paired with.     

Performance analysis of ordered CFAR detectors for MIMO radars

Ordered statistics is one of the proposed solutions to improve the detection in a multiple target environment. Some variants of this technique have been proposed for the SISO (Single Input Single Output) radars such as the OS-CFAR (Ordered Statistics CFAR), the GOSCA-CFAR (Generalized Ordered Statistics, Cell Averaging CFAR), the OSGO-CFAR (Ordered Statistics Greatest Of CFAR) and the OSSO-CFAR (Ordered Statistics Smallest Of CFAR) to deal with multiple target situations. In this paper, we generalize these CFAR detectors for the MIMO (Multi Input Multi Output) radars with three different schemes. We derive closed-form expressions of the probability of false alarm (Pfa) and the probability of detection (Pd) in a homogeneous environment for two schemes. The performance of these detectors for a non-homogeneous clutter environment (presence of interfering targets and clutter edge) has been assessed and compared. The results obtained showed that the best performance is obtained by the OSSO-CFAR.     

Development of a fractional order based MIMO controller for high dynamic engine testbeds

Testbed are used to tune and assess automotive engines. As more High Dynamic (HD) scenarios need to be simulated, the testbeds require Multi Input Multi Output (MIMO) and robust control systems. A cooperation involving a major testbed manufacturer and two university laboratories was therefore set up. This paper presents the Control-System Design (CSD) methodology developed from system identification to the design and assessment of the MIMO robust controller for a HD testbed coupled with a spark-ignition engine. It is specially highlighted how the entire process has been automated and simplified and how the fractional order based MIMO CRONE CSD has been parameterized to obtain the best performance. Experimental results show that the proposed fractional order based MIMO control system is able to improve robustness and decoupling.     

提高MIMO信道BER性能的干扰对齐方案

为提高多输入多输出(MIMO)X信道的比特误码率(BER)性能,提出一种干扰对齐方案。在发送端将数据按照Alamouti编码方案重复发送,在接收端通过重新配置天线工作模式改变信道系数,构成具有正交结构的等效信道矩阵,通过矩阵运算消除干扰,并采用低复杂度的PIC群译码算法进行译码。仿真结果验证了该方案的有效性。     

Fradkov Theorem-Based Control of MIMO Nonlinear Lurie Systems

Consideration was given to the problem of adaptive output control of the class of MIMO (Multiple Input Multiple Output) systems that are functionally and parametrically uncertain. An approach to the design of the control law ensuring stabilization of the MIMO nonlinear Lurie system, that is, a system consisting of the linear part (strictly minimum-phase unit) and nonlinear static feedback unit, was proposed on the basis of the Fradkov theorem on feedback passification of linear systems.     

Investigation on dual‐port printed MIMO antenna with reduced RCS for C‐band radar application

In this communication, two port printed Multi Input Multi Output (MIMO) antenna with reduced radar cross section and low mutual coupling is designed and analyzed. Reduced mutual coupling (less than ?20 dB) is achieved by placing the electromagnetic band gap structure in between the two identical ports. Frequency selective surface has been used to reduce the radar cross section (more than 30 dB reduction) of the proposed antenna design, which makes it suitable for military applications. The proposed radiating design is fabricated and measured for the purpose of validation. It resonates at 6.8 GHz supporting an impedance bandwidth of 1.03 GHz from 6.12 to 7.15 GHz. It promises a gain of 4.75 dB in the working frequency range. This radiator is suitable for military radars works in C‐band.     

EVOLUTIONARY SEARCH FOR LIMIT CYCLE AND CONTROLLER DESIGN IN MULTIVARIABLE NONLINEAR SYSTEMS

A feature of many practical control systems is a Multi‐Input Multi‐Output (MIMO) interactive structure with one or more gross nonlinearities. A primary controller design task in such circumstances is to predict and ensure the avoidance of limit cycling conditions followed by achieving other design objectives. This paper outlines how such a system may be investigated using the Sinusoidal Input Describing Function (SIDF) philosophy quantifying magnitude, frequency and phase of any possible limit cycle operation. While Sinusoidal Input Describing function is a suitable linearization technique in the frequency domain for assessment of stability and limit cycle operation, it can not be employed in time domain. In order to be able to incorporate the time domain requirements in an overall controller design technique, the appropriate linearization technique suggested here is the Exponential Input Describing Function (EIDF). First, an evolutionary search based on a multi‐objective formulation is employed for the direct solution of the harmonic balance system matrix equation. The search is based on Multi‐Objective Genetic Algorithms (MOGA) and is capable of predicting specified modes of theoretically possible limit cycle operation. Second, the design requirements in time as well as frequency domain are formulated by a set of constraint inequalities. A numerical synthesis procedure also based on Multi‐Objective Genetic Algorithm is employed to adjust the initial compensator parameters to meet the imposed constraints. Robust stability and robust performance are investigated with respect to linearization uncertainty within the context of multiobjective formulation. In order to make the Genetic Algorithm (GA) search more amenable to design trade‐off between different and often contradictory specifications, a weighted sum of the functions is introduced. This criterion is subsequently optimized subject to the nonlinear system dynamics and a set of design requirements. Examples of use are given to illustrate the effectiveness of the proposed approach.     

Formulation of Closed-Loop Min–Max MPC as a Quadratically Constrained Quadratic Program

In this note, we show that min-max model predictive control (MPC) for linearly constrained polytopic systems with quadratic cost can be cast as a quadratically constrained quadratic program (QCQP). We use the rigorous closed loop formulation of min-max MPC, and show that any such min-max MPC problem with convex costs and constraints can be cast as a finite dimensional convex optimization problem, with the QCQP arising from quadratic costs as a special case. At the base of the proof is a lemma showing the convexity of the dynamic programming cost-to-go, which implies that the worst case on an infinite polytopic set is assumed on one of its finitely many vertices. As the approach is based on a scenario tree formulation, the number of variables in this problem grows exponentially with the horizon length. Fortunately, the QCQP is tree structured, and can thus be efficiently solved by specially tailored interior-point methods whose computational costs are linear in the number of variables. The new formulation as a tree sparse QCQP promises to facilitate online solution of the rigorous min-max MPC problem with quadratic costs     

分布式MIMO系统容量最优的预编码设计

针对分布式多入多出(MIMO)系统各天线功率无法共享的问题,基于分布式MIMO系统各天线功率受限的假设,提出容量准则下的最优预编码矩阵设计方案。采用Lagrange对偶优化的方法,将原优化问题转化为其对偶问题,给出求解预编码矩阵的迭代算法流程,以及在不同天线配置和容量准则下的信号发射策略。仿真结果表明,在发射天线数目多于接收天线数目时或信道矩阵缺秩时,该迭代算法求得的预编码矩阵的容量性能优于已有次优解析解。     

MIMO技术在无线通信领域的应用研究

在第4代移动通信技术（4G）飞速发展的今天,MIMO（MultipleInputMultipleOutput,多输入多输出）技术由于其在通信领域的先天技术优势,被广泛的应用于无线通信技术中。文章从MIMO从无线通信技术的发展引出MIMO的概念,详细介绍了MIMO的系统原理、关键技术应用研究、发展前景等。     

Robust capacity maximization transceiver design for MIMO OFDM systems多天线正交频分复用系统中鲁棒性容量最大化的收发机设计

In this paper, we investigated capacity maximization problem for Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing systems with imperfect channel state information (CSI). To the best of our knowledge, the considered problem is still an open problem. However, the transceiver designs for MIMO OFDM systems have been extensively studied. It seems nobody gives closed-form solutions for resource allocation for MIMO OFDM systems with statistical channel estimation errors up to date. In our work, based on practical channel estimation algorithm, the channel estimation errors are first derived and then the robust resource allocation problem has been formulated. The structure of the optimal robust precoder is first derived, based on which the optimization problem will be simplified significantly. Furthermore, based on the Lagrangian dual method, a robust power allocation algorithm is proposed. The proposed power allocation can be considered as a variant of water-filling solution named cluster water-filling solution. Finally, simulation results show that our proposed robust design outperforms the non-robust design in terms of channel capacity.     

Improved dynamic output feedback RMPC for linear uncertain systems with input constraints

In this work, we propose a dynamic output feedback robust model predictive control (RMPC) design method for linear uncertain systems with input constraints. In order to handle the input constraints, the control signals are permitted to saturate, which can fully utilize the capability of actuators and thus can reduce the conservatism. For the unavailable states, an ellipsoidal set is used to obtain an estimation, and it is updated at every time instant. A modified RMPC design requirement is used to ensure the recursive feasibility of the optimization problem. Then, the design method is formulated in terms of a convex optimization problem with linear matrix inequality constraints. The proposed output feedback RMPC design method is expected to further reduce the conservativeness. The improvements of the proposed algorithm over the other existing techniques is demonstrated by an example. Copyright © 2015 John Wiley & Sons, Ltd.     

基于双码本的多用户MIMO有限反馈预编码方法

针对多用户多输入多输出(MIMO)下行链路由有限反馈导致的性能缺失,提出一种基于双码本的有限反馈预编码方法。该方法首先在接收端根据期望用户最大信干比准则从预置码本中选取预编码码字及扰动码字反馈给发送端,然后利用矩阵线性变换特性对预编码码字进行线性变换扰动以达到容量最优,从而补偿由于有限反馈导致的容量性能缺失。仿真结果表明,所提出的方法在保证反馈链路开销与系统误码性能的情况下,有效地改善了系统吞吐量。     

IEEE802.16接收机检测模块的FPGA实现

提出了一种采用现场可编程门阵列器件FPGA实现802.16接收端MIMO(多输入多输出)2×2检测的方案。在C语言平台对基于并行干扰消除的最小均方误差的算法进行研究和仿真后,使用Verilog硬件描述语言对MIMO检测各模块分别设计;均通过了综合和验证;这样本文提出了对系统起重要作用的接收端的MIMO检测芯片的实现方法。     

IEEE802.16接收机的MIMO检测模块的FPGA设计与实现

提出了一种采用现场可编程门阵列器件FPGA实现802.16接收端MIMO(多输入多输出)2×2检测的方案。在C语言平台对基于并行干扰消除的最小均方误差的算法进行研究和仿真后,使用Verilog硬件描述语言对MIMO检测各模块分别设计;均通过了综合和验证;这样本文提出了对系统起重要作用的接收端的MIMO检测芯片的实现方法。     

Ultra‐compact 4‐port DR antenna for multi‐input multi‐output standards

Here, an ultra‐compact Multi‐Input‐Multi‐Output (MIMO) antenna system is presented for Wireless Local Area Network (WLAN) applications. The proposed antenna compactness approach is based on using Cylindrical‐Dielectric‐Resonator‐Antenna (CDRA) symmetry with the help of image theory to achieve the best size reduction of the resonators and maintain the resonance frequency of the original CDRA. The electric/magnetic walls approach is utilized to miniaturize the size by exploring the symmetry and antisymmetry of the resonant mode. First, a CDRA for MIMO system is designed and tested in terms of return loss and radiation efficiency. Then, two configurations of MIMO‐Antennas (two and four ports) are examined by using the same substrate size. The 2‐port‐MIMO antenna is built from two half‐CDRs (HCDRs) facing each other. Similarly, four‐quarter‐CDRs (QCDRs) are created to form a 4‐port MIMO antenna system. As a result, a 75% size reduction is achieved (size of 30 × 30 × 7.62 mm³). The measured impedance bandwidth for the 4‐port MIMO antenna is 5.4% (5.4‐5.7 GHz), with more than 15 dB isolation levels. Proper levels of Envelope Correlation Coefficients (ECCs) are also achieved (1 × 10^?2‐4 × 10^?2), with a channel capacity loss (CCL) of 0.04 bits/S/Hz. The proposed MIMO antennas are suitable for compact wireless communication systems.     

Evolutionary approach on connectivity-based sensor network localization

The sensor network localization based on connectivity can be modeled as a non-convex optimization problem. It can be argued that the actual problem should be represented as an optimization problem with both convex and non-convex constraints. A two-objective evolutionary algorithm is proposed which utilizes the result of all convex constraints to provide a starting point on the location of the unknown nodes and then searches for a solution to satisfy all the convex and non-convex constraints of the problem. The final solution can reach the most suitable configuration of the unknown nodes because all the information on the constraints (convex and non-convex) related to connectivity have been used. Compared with current models that only consider the nodes that have connections, this method considers not only the connection constraints, but also the disconnection constraints. As a MOEA (Multi-Objective Evolution Algorithm), PAES (Pareto Archived Evolution Strategy) is used to solve the problem. Simulation results have shown that better solution can be obtained through the use of this method when compared with those produced by other methods.     

Solving nesting problems with non-convex polygons by constraint logic programming

In this paper an application of constraint logic programming (CLP) to the resolution of nesting problems is presented. Nesting problems are a special case of the cutting and packing problems, in which the pieces generally have non‐convex shapes. Because of their combinatorial optimization nature, nesting problems have traditionally been tackled by heuristics and in the recent past by meta‐heuristics. When trying to formulate nesting problems as linear programming models, to achieve global optimal solutions, the difficulty of dealing with the disjunction of constraints arises. On the contrary, CLP deals easily with this type of relationships among constraints. A CLP implementation for the nesting problem is described for convex and non‐convex shapes. The concept of nofit polygon is used to deal with the geometric constraints inherent to all cutting and packing problems. Computational results are presented.     

基于Stackelberg博弈的多输入多输出雷达信号与目标干扰优化

针对实际杂波环境中多输入多输出(MIMO)雷达与目标间检测与隐身的博弈问题,提出一种新的两步注水算法。首先建立时空编码模型;然后基于互信息量准则,用注水法分配目标干扰功率,用通用注水法分配雷达信号功率;最终得到强弱杂波环境Stackelberg博弈中目标占优和雷达占优的优化方案。仿真结果表明,雷达信号功率分配和通用注水水位变化规律均受杂波影响,两优化方案的互信息量在强杂波环境降低约50%,干扰影响系数分别降低0.2和0.25,互信息量受干扰影响程度降低,证明了所提算法的有效性。