无线通信系统的MIMO信道测量与建模

在多径信道中,使用多天线的M IMO(多输入多输出)无线系统能够比单天线系统提供更高的信道容量,而信道测量与建模是决定通信性能的一个重要因素。文中对目前国际范围内现有的M IMO信道测量和建模进行了研究,并进行了归纳和分类,同时分析了M IMO信道测量和建模的方法,指出了目前信道测量和建模中存在的问题,并给出了一些针对M IMO信道测量系统设计的建议。     

Dynamics of spatial correlation and implications on MIMO systems

The use of multiple antennas has found various applications in the area of wireless communications. One such application has recently become very popular and is referred to as the multiple-input multiple-output (MIMO) antenna system. The main idea behind MIMO is to establish independent parallel channels between multiple transmit and receive antennas. Each channel uses the same frequency, and the transmissions occur simultaneously. In such a configuration, the amount of data transmitted increases linearly with the number of parallel channels, which is what makes MIMO so popular in the wireless world. The enormous capacity offered by MIMO systems is not realizable when the parallel channels are highly correlated. The goal of this article is to highlight the correlation concept and its impact on MIMO systems. Although correlation can be defined in many dimensions, here we focus on spatial correlation, and specifically consider antenna correlations in mobile units. We provide an overview of spatial correlation and present its underlying parameters in detail. Special attention is given to mutual coupling since it has signal decorrelation and antenna gain reduction effects. We then present how correlation in a MIMO system affects the amount of data that can be transmitted (MIMO capacity) and briefly review how power should be distributed with the knowledge of correlation. Analyses indicate that in real propagation environments, the high capacity gain of MIMO systems can be realized with improved antenna selection algorithms and power allocation strategies.     

B3G空中接口技术分析--MIMO信道测量

在多径信道中,使用多天线的MIMO无线系统能够比单天线系统提供更高的信道容量,而信道测量是决定通信性能的一个重要因素。对目前国际范围内现有的MIMO信道测量进行了研究,并做了归纳和分类。此外,对MIMO信道测量方法进行了分析,并给出了一些针对MIMO信道测量系统设计的建议,为B3G空中接口技术研究提供了技术支持。     

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.     

Spatial precoder design for space–time coded MIMO systems: based on fixed parameters of MIMO channels

In realistic channel environments the performance of space–time coded multiple-input multiple output (MIMO) systems is significantly reduced due to non-ideal antenna placement and non-isotropic scattering. In this paper, by exploiting the spatial dimension of a MIMO channel we introduce the novel idea of linear spatial precoding (or power-loading) based on fixed and known parameters of MIMO channels to ameliorate the effects of non-ideal antenna placement on the performance of coherent (channel is known at the receiver) and non-coherent (channel is un-known at the receiver) space–time codes. Antenna spacing and antenna placement (geometry) are considered as fixed parameters of MIMO channels, which are readily known at the transmitter. With this design, the precoder is fixed for fixed antenna placement and the transmitter does not require any feedback of channel state information (partial or full) from the receiver. We also derive precoding schemes to exploit non-isotropic scattering distribution parameters of the scattering channel to improve the performance of space–time codes applied on MIMO systems. However, these schemes require the receiver to estimate the non-isotropic parameters and feed them back to the transmitter. Closed form solutions for precoding schemes are presented for systems with up to three receive antennas. A generalized method is proposed for more than three receive antennas.     

Sum Capacity of Multiuser MIMO Broadcast Channels with Block Diagonalization

The sum capacity of a Gaussian broadcast MIMO channel can be achieved with dirty paper coding (DPC). However, algorithms that approach the DPC sum capacity do not appear viable in the forseeable future, which motivates lower complexity interference suppression techniques. Block diagonalization (BD) is a linear preceding technique for downlink multiuser MIMO systems. With perfect channel knowledge at the transmitter, BD can eliminate other users' interference at each receiver. In this paper, we study the sum capacity of BD with and without receive antenna selection. We analytically compare BD without receive antenna selection to DPC for a set of given channels. It is shown that (1) if the user channels are orthogonal to each other, then BD achieves the same sum capacity as DPC; (2) if the user channels lie in the same subspace, then the gain of DPC over BD can be upper bounded by the minimum of the number of transmit and receive antennas. These observations also hold for BD with receive antenna selection. Further, we study the ergodic sum capacity of BD with and without receive antenna selection in a Rayleigh fading channel. Simulations show that BD can achieve a significant part of the total throughput of DPC. An upper bound on the ergodic sum capacity gain of DPC over BD is proposed for easy estimation of the gap between the sum capacity of DPC and BD without receive antenna selection.     

3×3多天线系统衰落相关与信道容量研究

为分析天线间距和散射角等信道物理参数对多输入多输出系统信道容量的影响,提出了一种相关衰落环境中信道容量的分析方法。该方法基于接收均匀圆阵构建了蕴含信道物理参数的衰落相关矩阵。并由此详细推导了3×3多天线系统信道容量的闭式表达。结果表明,相关矩阵特征值的个数和大小决定了系统信道容量的大小。该方法回避了已有算法需求取相关衰落信道特征值概率密度函数的问题,降低了运算量,可以被推广到任意收发天线数的多输入多输出和多输入多输出-频分复用系统。仿真结果表明,天线间距增大,信道容量随之增大。但是当天线间距增大到衰落相关的第一个过零点时,信道容量达到最大值,再增大天线间距对信道容量影响很小。散射角越大,信道容量收敛到最大值速率越快。     

一种应用于无线通信系统的MIMO天线

MIMO系统是通过不同的分集技术,以实现在相同带宽和发射功率的条件下大幅改善系统容量和可靠性,减小信道失真。作为系统关键模块之一的天线,则要求有着好的分集特性,并接收较多的这波。这里提出的MIMO天线工作在2．4GHz,天线单元是等边三角形贴片天线。三角形天线的宽波瓣可以使MIMO天线接收更丰富的多径这波,与天线单元的高增益相结合能较好改善MIMO系统的SNR和抗干扰能力。通过对天线端口间的互耦和相关性分析,该系统能实现好的极化和方向图分集,获得高的分集增益。     

Antenna Array Structures Effect on Water-Filling Capacity of Indoor NLOS MIMO Channel

1 Introduction Digital communication using MI MO has recently e-merged as one of the most significant technical break-throughs in modern wireless communications .Foschini ,Telatar and others saythat the capacity can beincreasedlinearly with the mini mum antenna numbers of thetransmitter and receiver if the scattering environment isrich and there is no correlation between the antennapairs at the transmitter and the receiver[1 ~2]. Toachieve these capacities coding techniques such asBLAST an…     

三维MIMO信道物理模型的统计特征

提出以散射矩阵来概括并简化电波传播过程中散射体对电磁波的影响,并对传统的距离分集和极化分集多入多出（MIMO）信道模型进行扩展,建立了一种可以应用于各种分集情况的三维通用MIMO物理信道模型。再以此模型为基础,对三维环境中的MIMO信道统计特征进行了研究,推导出任意情况下交叉极化鉴别度（XPD）和子信道间相关性的计算方法,并进行了仿真验证。仿真结果表明从文中所提出信道模型提取得到的统计特征与理论分析的结果是相符的。     

Generalized decorrelating discrete-time rake receiver

In this paper, we introduce the generalized decorrelating discrete-time RAKE receiver (GD-DTR) for single antenna systems and extend it to multi-antenna (e.g. MIMO) systems. The GD-DTR benefits from the correlated nature of multiple access interference while being robust against channel estimation errors. It is a combination of two other advanced RAKE reception methods namely, the discrete-time version of the generalized RAKE (G-RAKE) receiver and the decorrelating discrete-time RAKE receiver (D-DTR). The G-RAKE was proposed for correlated interference mitigation. The D-DTR improves performance in the presence of channel estimation errors in diffuse channels. Our results show that the performance of the discrete-time G-RAKE (G-DTR) could be worse than a conventional discrete-time RAKE receiver (C-DTR) when there are channel estimation errors in the system. Unlike G-DTR, our proposed GD-DTR provides gains up to 0.7 dB at a raw bit error rate of 10^-2 in the presence of channel estimation errors compared to C-DTR. For the MIMO case, the gain of the MIMO GD-DTR compared to MIMO C-DTR are 1 dB and 1.1 dB at a raw bit error rate of 10^-2 in 2 transmit 2 receive antenna (2times2) and 3times3 systems respectively, if there is no correlation between the antennas. For a highly correlated receive antenna case, the gain increases to 4 dB.     

A review of antennas and propagation for MIMO wireless communications

Multiple-input-multiple-output (MIMO) wireless systems use multiple antenna elements at transmit and receive to offer improved capacity over single antenna topologies in multipath channels. In such systems, the antenna properties as well as the multipath channel characteristics play a key role in determining communication performance. This paper reviews recent research findings concerning antennas and propagation in MIMO systems. Issues considered include channel capacity computation, channel measurement and modeling approaches, and the impact of antenna element properties and array configuration on system performance. Throughout the discussion, outstanding research questions in these areas are highlighted.     

Channel modeling and analysis for multipolarized massive MIMO systems

In this paper, we use the multipolarized antennas in massive multiple‐input multiple‐output (MIMO) systems to decline the channel orthogonality and enhance the system performance. We propose 3 multipolarized massive MIMO system schemes according to antenna structures of 3 widely used massive MIMO systems and establish 3‐D geometrical channel models. Simulation results show that the multipolarized massive MIMO systems outperform the unipolarized massive MIMO systems in many situations. The multipolarized antennas would be the best choice for massive MIMO systems if the space efficiency and the miniaturization of equipments are of primary concern.     

Outdoor MIMO wireless channels: models and performance prediction

We present a new model for multiple-input-multiple-output (MIMO) outdoor wireless fading channels and their capacity performance. The proposed model is more general and realistic than the usual independent and identically distributed (i.i.d.) model, and allows us to investigate the behavior of channel capacity as a function of the scattering radii at transmitter and receiver, distance between the transmit and receive arrays, and antenna beamwidths and spacing. We show how the MIMO capacity is governed by spatial fading correlation and the condition number of the channel matrix through specific sets of propagation parameters. The proposed model explains the existence of "pinhole" channels which exhibit low spatial fading correlation at both ends of the link but still have poor rank properties, and hence, low ergodic capacity. In fact, the model suggests the existence of a more general family of channels spanning continuously from full rank i.i.d. to low-rank pinhole cases. We suggest guidelines for predicting high rank (and hence, high ergodic capacity) in MIMO channels, and show that even at long ranges, high channel rank can easily be sustained under mild scattering conditions. Finally, we validate our results by simulations using ray tracing techniques. Connections with basic antenna theory are made.     

Optimal antenna selection based on capacity maximization for MIMO systems in correlated channels

Recent work has shown that multiple-input multiple-output (MIMO) systems with multiple antennas at both the transmitter and receiver are able to achieve great capacity improvement. In such systems, it is desirable to select a subset of the available antennas so as to reduce the number of radio frequency (RF) chains. This paper addresses the problem of antenna selection in correlated channels. We consider a narrowband communication system with M transmit and N receive antennas. We present the criterion for selecting the optimal L/sub t/ out of M transmit and L/sub r/ out of N receive antennas in terms of capacity maximization, assuming that only the long-term channel statistics, instead of the instantaneous channel-state information, are known. Simulations will be used to validate our theoretical analysis and demonstrate that the number of required RF chains can be significantly decreased using our proposed selection strategy, while achieving even better performance than the conventional MIMO system without antenna selection.     

天线间隔对室内非视距MIMO信道容量的影响

采用2维射线跟踪法分析了天线间隔对非视距室内环境中MIMO系统容量ccdfs的影响。结果表明，天线间隔对MIMO系统容量影响非常显著，而且天线数目不同，天线间隔对MIMO系统容量影响不同。天线间隔越大，系统容量越接近Telatar所预测的MIMO系统容量；但随着天线间隔的减小，系统容量则会显著降低。对于相同天线间隔的多天线系统，随着天线数目的增加，系统所能实现的独立同分布瑞利信道容量的百分比越低。     

天线阵结构对非视距室内MIMO信道容量的影响

采用2维射线跟踪法分析了非视距室内环境中天线间隔、天线阵形对MIMO系统容量和互补累积分布函数(CCDF)的影响。结果表明随着天线间隔减小,MIMO系统容量降低。10%中断容量表明,天线间隔相同时,有独立同分布瑞利信道容量大于线性阵容量大于方阵容量或者圆形阵容量的关系。当天线间隔大于等于3 时,不同天线阵列阵形对容量影响非常小,此时i.i.d.瑞利信道理论容量几乎全部实现。当天线间隔小于等于1 时,天线阵列阵形对容量影响较大,矩形阵和圆形阵MIMO系统容量相差较小,但都显著小于线性阵列系统容量。在非视距的室内环境中,要实现最大的MIMO容量增益,设计天线阵列时应该对天线间隔和阵列阵形综合考虑。     

MIMO CDMA antenna system for SINR enhancement

We present a system to enhance signal-to-interference plus noise ratio (SINR) for multiple-input-multiple-output (MIMO) direct-sequence code-division multiple-access (DS/CDMA) communications in the downlink for frequency-selective fading environments. The proposed system utilizes a transmit antenna array at the base station and a receive antenna array at the mobile station with finite-impulse response filters at both the transmitter and receiver. We arrive at our system by attempting to find the optimal solution to a general MIMO antenna system. A single user joint optimum scenario and a multiuser SINR enhancement scenario are derived. In addition, a simplified one-finger receiver structure is introduced. Numerical results reveal that significant system performance and capacity improvement over conventional approaches are possible. We also investigate the sensitivity of the proposed system to channel estimation errors.     

Receive antenna selection for closely-spaced antennas with mutual coupling

We investigate the achievable rate of receive antenna selection MIMO systems in the presence of mutual coupling and spatial correlation. For that, we assume the antenna array to consist of dipole antennas placed side-by-side in a linear pattern and in a very limited physical space. In a first step, we will assume perfect channel state information at the receiver side only and a negligible training overhead compared with the payload. We will demonstrate that in contrast to what might be expected based on results for cases without mutual coupling, MIMO receive antenna selection can achieve higher data rates than the system using all antennas provided that the total number of receive antennas is larger than a critical value that we will further discuss. We then propose an optimal antenna selection processing that ensures rate maximization regardless of the number of antennas used. In a later step, we will address the impact of training overhead on the system achievable rate when the training overhead is considerable. We will show that such a rate is reduced dramatically due to the large amount of training overhead arising from the presence of mutual coupling. To overcome this problem, we will thus propose a novel channel estimation method, which reduces the training overhead greatly and improves the system achievable rate performance.     

MIMO无线传输技术综述

MIMO无线传输技术是通信领域的一项重要技术突破,它能在不增加带宽与功率的情况下成倍地提高无线通信系统的容量和频谱效率,堪称新一代无线通信系统中的关键技术之一,近年来引起了人们的广泛关注与研究兴趣。回顾无线移动通信的发展历程,概述天线分集技术与智能天线技术,剖析MIMO无线传输技术的原理与国内外研究现状:传统单天线系统向多天线系统演进、智能天线向多天线系统演进、MIMO无线传输技术的原理、MIMO系统中的分集与复用、MIMO无线信道建模、MIMO系统中的多天线设计等,为深入认识与进一步研究MIMO无线传输技术奠定基础。