互耦作用对MIMO系统信道容量的影响

简单概括了无线多输入多输出（MIMO）系统及其信道容量,应用矩量法分析了因互耦作用引起的天线阵各阵元辐射图的变化,进而应用已提出的射线追踪模型分析了一个4.4MIMO系统接收端阵元间距不同时互耦作用对信道容量的影响。仿真结果说明在接收端使用多天线,阵元间距不可能太大的情况下,考虑互耦作用后,在小阵元间距（d=0.4λ）时就可得到较大的信道容量。得出结论在接收端阵元间距较小的情况下,互耦是一个有利的因素,在系统分析和设计时可以有效地加以利用。     

室内MIMO无线信道模型和信道容量研究

本文从工程的实际出发,首先提出一种修正的室内MIMO无线信道模型,该模型有效地修正先前室内MIMO无线信道模型的不足,具有明显吻合室内实际通信环境的特点,然后分析天线方向性以及天线单元间的互耦对室内MIMO无线信道容量的影响.数值模拟验证了这种影响,并得到在一定条件下互耦导致的天线方向图畸变产生角度分集,提高信道容量,互耦对空域相关性无影响的条件以及室内丰富的多径使天线方向性对信道容量的影响不明显等结论.最后,实验也证实理论分析.     

Multiuser MIMO receivers for space frequency block coded SC‐FDMA systems

Single carrier‐frequency division multiple access (SC‐FDMA) has been adopted as the uplink transmission standard in fourth generation cellular network to enable the power efficiency transmission in mobile station. Because multiuser MIMO (MU‐MIMO) is a promising technology to fully exploit the channel capacity in mobile radio network, this paper investigates the uplink transmission of SC‐FDMA systems with orthogonal space frequency block codes (SFBC). Two linear MU‐MIMO receivers, orthogonal SFBC (OSFBC) and minimum mean square error (MMSE), are derived for the scenarios with limited number of users or adequate receive antennas at base station. In order to effectively eliminate the multiple access interference (MAI) and fully exploit the capacity of MU‐MIMO channel, we propose a turbo MU‐MIMO receiver, which iteratively utilizes the soft information from maximum a posteriori decoder to cancel the MAI. By the simulation results in several typical MIMO channels, we find that the proposed MMSE MU‐MIMO receiver outperforms the OSFBC receiver over 1 dB at the cost of higher complexity. However, the proposed turbo MU‐MIMO receivers can effectively cancel the MAI under overloaded channel conditions and really achieve the capacity of MU‐MIMO channel. Copyright © 2014 John Wiley & Sons, Ltd.     

Ergodic channel capacity of the spatial correlated rayleigh MIMO channel

The theoretical capacity of the spatial correlated Rayleigh multiple input multiple output (MIMO) channel is an important issue in MIMO technology. In this article, an ergodic channel capacity formula of the spatial correlated rayleigh MIMO channel is provided, which is deduced when two antennas exist at either the transmitter or the receiver. The multi-dimensional least-squares fit algorithm is employed to narrow the difference between the theoretical formula capacity and the practical capacity. Simulation results show that the theoretical capacity approaches the practical one closely.     

Degradation of the MIMO channel capacity due to additional noises of amplifiers

It is theoretically well known that a multiple input multiple output (MIMO) system can offer higher channel capacity than a conventional wireless system. The MIMO capacity is increased as a function of signal‐to‐noise ratio (SNR) and a number of antenna elements at both the transmitter and receiver. To realize MIMO capability in practical use, the implementation of all electronic devices is necessary to be considered. Amplifiers become the most common devices assembled at the transmitter and receiver with the purpose of overcoming the power loss in the wireless channel. High power amplifier (HPA) and low noise amplifier (LNA) are the special types of amplifiers that are compulsory for the transmitter and receiver, respectively. Both devices have the same function to provide the reliable power gains while adding as little noise as possible. For a MIMO system, the channel capacity sensitively grows as a function of SNR. Therefore, the changes in SNR due to HPA and LNA definitely degrade the system capacity. In this paper, the degradation due to both devices is investigated by taking the gain and noise figure of these amplifiers into account. The new formula of MIMO channel capacity including amplifier characteristics is originally proposed. The results indicate the remarkable consideration on using amplifiers as they may degrade the capacity up to 26%. This can be the guideline for MIMO researchers to spare the capacity margin caused by the additional noises of amplifiers. Copyright © 2008 John Wiley & Sons, Ltd.     

Pre-Coding for MIMO Systems in Frequency-Selective Fading Channels

Multiple input multiple output (MIMO) systems showed good utilization of channel characteristics. In MIMO systems multiple signals are transmitted using multiple antenna system. This provides each receiver the combined signals and hence, array processing techniques helps in reducing the effects of interference among them. In this paper we devise the use of pre-coded MIMO system to reduce the effects of frequency selectivity and hence, enhance the systems capacity and/or reduce the bit error rate. In this technique we introduce a temporal pre-coder on each antenna signal; this creates a deterministic multi-path signals similar to signals received when the channel is multi-path fading channel. The same antenna signal will arrive at each receiver forming orthogonal sub-space and the receiver will be simple add and delay of the received signals. Ant colony optimization is used in this paper to select the best pre-code. Results showed that we can diagonalize the channel matrix and practically eliminate the interference for frequency selective fading channel. Simulation of two transmitting two receiving antennas pre-coded MIMO system showed that the capacity can be doubled.     

TD-SCDMA HSPA+中的单双流MIMO技术的研究

多输入多输出(MIMO)技术是近年来移动通信的热门研究领域,它的特征在于无线发射机和接收机都引入了多根天线.MIMO技术除了通过空间分集方式获得容量的提升外,还可以通过空间复用方式,利用不同天线信道的独立性建立多个空间子信道来提高容量.但是,无论是基于空间分集的单流模式还是基于空间复用的双流模式,单独在TD-SCDMA...     

Spatially and temporally correlated MIMO channels: modeling and capacity analysis

Wireless communication systems employing multiple antennas at both the transmitter and receiver have been shown to offer significant gains over single-antenna systems. Recent studies on the capacity of multiple-input-multiple-output (MIMO) channels have focused on the effect of spatial correlation. The joint effect of spatial and temporal correlation has not been well studied. In this paper, a geometric MIMO channel model is presented, which considers motion of the receiver and nonisotropic scattering at both ends of the radio link. A joint space-time cross-correlation function is derived from this model and variates with this joint correlation are generated by using the vector autoregressive stochastic model. The outage capacity of this channel is considered where the effects of antenna spacing, antenna array angle, degree of nonisotropic scattering, and receiver motion are investigated. When n transmit and n receive antennas are employed, it is shown that the outage capacity still increases linearly with respect to n, despite the presence of spatial and temporal correlation. Furthermore, analytical expressions are derived for the ergodic capacity of a MIMO channel for the cases of spatial correlation at one end and at both ends of the radio link. The latter case does not lend itself to numerical evaluation, but the former case is shown to be accurate by comparison with simulation results. The proposed analysis is very general, as it is based on the transmit and receive antenna correlations matrices.     

二进制猫群算法在大规模MIMO天线选择中的应用

在多输入多输出(MIMO)系统中,天线选择技术平衡了系统的性能和硬件开销,但大规模MI-MO系统收发端天线选择复杂度问题一直没有得到很好的解决.基于信道容量最大化的准则,采用两个二进制编码字符串分别表示发射端和接收端天线被选择的状态,提出将二进制猫群算法(BCSO)应用于多天线选择中,以MIMO系统信道容量公式作为猫群的适应度函数,将收发端天线选择问题转化为猫群的位置寻优过程.建立了基于BCSO的天线选择模型,给出了算法的实现步骤.仿真结果表明所提算法较之于基于矩阵简化的方法、粒子优化算法具有更好的收敛性和较低的计算复杂度,选择后的系统信道容量接近于最优算法,非常适用于联合收发端天线选择的大规模MIMO系统中.     

A stochastic MIMO channel model with joint correlation of both link ends

Abstract-This paper presents a novel stochastic channel model for multiple-input multiple-output (MIMO) wireless radio channels. In contrast to state-of-the-art stochastic MIMO channel models, the spatial correlation properties of the channel are not divided into separate contributions from transmitter and receiver. Instead, the joint correlation properties are modeled by describing the average coupling between the eigenmodes of the two link ends. The necessary and sufficient condition for the proposed model to hold is that the eigenbasis at the receiver is independent of the transmit weights, and vice versa. The authors discuss the mathematical elements of the model, which can be easily extracted from measurements, from a radio propagation point of view and explain the underlying assumption of the model in physical terms. The validation of the proposed model by means of measured data obtained from two completely different measurement campaigns reveals its ability to better predict capacity and spatial channel structure than other popular stochastic channel models.     

互耦效应对超大规模MIMO天线系统信道容量的影响

超大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)天线系统是6G的关键技术,由于天线单元间距很小,多个天线单元的互耦效应是影响其性能的因素之一。建立了基于石墨烯基贴片天线阵列-子阵列架构的超大规模MIMO天线系统,推导出了互耦效应影响下的信道容量表达式。通过电磁场数值计算仿真了超大规模MIMO天线系统的信道容量,结果表明,在不考虑互耦效应时,超大规模MIMO天线系统的信道容量与子阵列天线单元数、子阵列数以及发射机功率正相关;在互耦效应的影响下,系统的信道容量降低,互耦效应的强弱与子阵列天线单元的间距有关,天线单元间间距越小,相邻天线间的互耦效应越明显,系统的信道容量越小。该仿真结果可以为6G中超大规模MIMO天线系统的设计提供参考。     

MIMO信道在巷道中的GBDB模型分析

多输入多输出(MIMO)技术可以有效减弱无线传输多径衰落现象。建立矿井巷道环境下MIMO信道的三维GBDB模型,推导了该模型的空时相关函数,并对矿井下MIMO信道容量进行了数值仿真。结果表明,矿井巷道中的空间相关性对MIMO系统容量的影响很大,增加接收端天线数量、增大天线间距可以大幅度提高系统的信道容量。     

MIMO channel capacity and modeling issues on a measured indoor radio channel at 5.8 GHz

Multiple transmitters and receivers can be used to provide high link capacity in future wireless systems. Herein, an analysis of indoor environment multiple-input-multiple-output (MIMO) measurements in the industrial, scientific, and medical (ISM) band at 5.8 GHz is performed and the possible increase in capacity, utilizing multiple transmitters and receivers is examined. The investigation shows that in the measured indoor environment, the scattering is sufficiently rich to provide substantial link capacity increases. Furthermore, the effect of intra-element spacing on the channel capacity is studied. Our investigation also shows that the envelope of the channel coefficients for this obstructed-line-of-sight (OLOS) indoor scenario is approximately Rayleigh distributed and the MIMO channel covariance matrix can be well approximated by a Kronecker product of the covariance matrices describing the correlation at the transmitter side and the receiver side, respectively. A statistical narrowband model for the OLOS indoor MIMO channel based on this covariance structure is presented.     

基于电磁矢量传感器的MIMO天线阵列系统研究

将电磁矢量传感器(EVS,electromagnetic vetor sensor)信号处理法与传统MIMO信号处理有机地结合,建立了基于EVS的多天线三维信道模型。采用多重信号分类(MUSIC,multiple signal classification)算法对MIMO的达波信号方向(DOA,direction of arrival)进行空间谱估计,导出基于EVS的三维空间信道解析式,阐明了EVS信号处理与MIMO多径信道相关性的关系。与传统标量传感器阵列(SSA,scalar sensor array)MIMO天线阵列比较,EVS阵列能获取达波信号的多维极化信息,同时具有空间域和极化信号处理能力。因此可缓解空间多径信道相关性,使空间极化分量的相关性趋于零值,而且使MIMO系统性能受空间结构的影响较小。理论分析和仿真结果表明在提高MIMO天线系统性能上,基于EVS阵列的系统比SSA系统具有更高的优越性。     

信道估计误差对MIMO系统信道容量的影响研究

为了分析信道估计误差对信道容量的影响,结合MIMO系统接收端信道估计误差的特点,重新构建了MIMO信道的统计模型。利用Wishart分布的性质,推导了当MIMO信道矩阵满秩时,仅接收端已知信道CSI情况下系统信道容量的下限。仿真结果表明,MIMO系统信道容量对信道估计误差比较敏感。     

Statistical Eigenmode Transmission Over Jointly Correlated MIMO Channels

We investigate multiple-input multiple-output (MIMO) eigenmode transmission using statistical channel state information at the transmitter. We consider a general jointly correlated MIMO channel model, which does not require separable spatial correlations at the transmitter and receiver. For this model, we first derive a closed-form tight upper bound for the ergodic capacity, which reveals a simple and interesting relationship in terms of the matrix permanent of the eigenmode channel coupling matrix and embraces many existing results in the literature as special cases. Based on this closed-form and tractable upper bound expression, we then employ convex optimization techniques to develop low-complexity power allocation solutions involving only the channel statistics. Necessary and sufficient optimality conditions are derived, from which we develop an iterative water-filling algorithm with guaranteed convergence. Simulations demonstrate the tightness of the capacity upper bound and the near-optimal performance of the proposed low-complexity transmitter optimization approach.     

STBC MIMO CDMA系统CMVDR接收机研究

提出了STBC MIMO CDMA系统中一种新的基于多用户ML估计的带制约的最小方差无失真响应(CMVDR)接收机，能有效抑制多址干扰(MAD和符号间干扰(ISI)。给出了多用户、多径的STBC MIMO CDMA系统信道模型及ML参数估计，并给出了分部加权和整体加权两种CMVDR接收机，本接收机也适用于SIMO CDMA系统。进行了系统模拟，并对分部加权和整体加权两种CMVDR接收机的性能以及自适应CMMSE接收机的性能进行了比较分析。     

基于稀疏贝叶斯学习的MIMO-OFDM电力线通信系统接收机设计

丰富的脉冲噪声干扰对基于MIMO-OFDM技术的电力线通信系统接收机设计带来了巨大挑战。针对这个问题,提出了一种联合估计电力线信道和脉冲噪声的接收机设计方案。该方案主要利用电力信道多径模型参数在频域上的稀疏性和脉冲噪声在时域上的稀疏性特征,将待估计信道模型参数和脉冲噪声联合视作一个稀疏向量,同时利用MIMO系统的空间相关性,构建了一个基于多测量向量的压缩感知模型,并引入多测量向量稀疏贝叶斯学习理论,设计了一种联合估计MIMO信道模型参数和脉冲噪声的方法。仿真结果表明,与传统的MIMO信道估计与脉冲噪声抑制相互分离的接收机方案相比,新方法在估计性能和误比特率性能上有明显提升。     

MIMO系统中天线选择的关键技术及其应用

多天线MIMO系统利用多个收、发天线有效地改善无线通信系统性能,提高系统容量,增强系统可靠性.然而使用多个射频的MIMO系统增加了天线的体积、功率和硬件,从而增加了成本.天线选择是一种低成本、低复杂度的有效方法,可以利用多天线系统的多数优点.使用天线选择技术可以降低系统成本和复杂度,同时保留MIMO系统的优越性能.文中考虑了天线选择系统的一些实际应用问题,RF预处理,训练序列等的实际应用.最后,给出了一些天线选择的结论.     

Multiple antenna systems: their role and impact in future wireless access

Multiple antennas play an important role in improving radio communications. In view of this role, the area of multiple antenna communication systems is in the forefront of wireless research. This article reviews two key related aspects of multiple antenna communication systems: multiple access interference mitigation at the receiver via multi-user beamforming; and space-time modulation and coding for MIMO systems. It is shown that both multi-user and MIMO receivers share similar signal processing and complexity tradeoffs.. Following that, a general unified framework for assessing different types of space-time modulation for MIMO systems is introduced. These space-time modulation methods are then compared in terms of Shannon capacity over multipath channels. Key MIMO system performance and implementation issues are also highlighted.