Performance evaluation of spatially multiplexed MIMO systems with subset antenna transmission in interference limited environments

Transmit antenna selection in spatially multiplexed multiple-input multiple-output (MIMO) systems is a low complexity low-rate feedback technique, which involves transmission of a reduced number of streams from the maximum possible to improve the error rate performance of linear receivers. It has been shown to be effective in enhancing the performance of single-user interference-free point-to-point MIMO systems. However, performance of transmit antenna selection techniques in interference-limited environments and over frequency selective channels is less well understood. In this paper, we investigate the performance of transmit antenna selection in spatially multiplexed MIMO systems in the presence of co-channel interference. We propose a transmission technique for the downlink of a cellular MIMO system that employs transmit antenna selection to minimize the effect of co-channel interference from surrounding cells. Several transmit antenna selection algorithms are proposed and their performance is evaluated in both frequency flat and frequency selective channels. Various antenna selection algorithms proposed in the literature for single user MIMO links are extended to a cellular scenario, where each user experiences co-channel interference from the other cells (intercell interference) in the system. For frequency selective channels, we consider orthogonal frequency division multiplexing (OFDM) with MIMO. We propose a selection algorithm that maximizes the average output SINR over all subcarriers. A method to quantify selection gain in frequency selective channel is discussed. The effect of delay spread on the selection gain is studied by simulating practical fading environments with different delay spreads. The effect of the variable signal constellation sizes and the number of transmitted streams on the bit error rate (BER) performance of the proposed system is also investigated in conjunction with the transmit antenna selection. Simulation results show that for low to moderate interference power, significant improvement in the system performance is achievable with the use of transmit antenna selection algorithms. Even though the gain due to selection in frequency selective channels is reduced compared to that in flat fading channels due to the inherent frequency diversity, the performance improvement is significant when the system is interference limited. The performance improvement due to reduced number of transmit streams at larger signal constellation sizes is found to be more significant in spatially correlated scenarios, and the gain due to selection is found to be reduced with the increased delay spread. It is found that employing transmit antenna selection algorithms in conjunction with adaptation of the number of transmitted streams and the signal constellation sizes can significantly improve the performance of MIMO systems with co-channel interference.     

Joint pre-processing co-channel interference cancellation for single user MIMO

In general, multiplexing and diversity gains of single user MIMO systems are restricted by min(M,N) where M, N denote the number of antenna elements at a transmitter and receiver, respectively. In order to increase the multiplexing/diversity gains and improve the performance of single user MIMO systems, a joint pre-processing co-channel interference cancellation (JPCIC) method is proposed. The JPCIC is analyzed in both the perfect and the imperfect channel state information. The dependence of channel capacity on the number of antenna elements in every subset, the number of subsets, transmit powers and channel estimation errors is discussed. As theoretical calculation result, the channel capacity increases when the multiplexing/diversity gains and/or the transmit power increase in a certain channel model whether the channel estimation error is absent or present. Compared to the conventional zero-forcing method, the channel capacity of JPCIC is considerably higher because of higher multiplexing/diversity gains, however, it is less robust and decreased more rapidly due to incomplete cancellation of interference terms when the channel estimation error increases. There is a trade-off between the channel capacity and the complexity of system, however, according to quick development in circuit techniques and miniaturization of devices, the JPCIC is expected to be an attractive technology for MIMO system.     

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.     

The Downlink Capacity of Single-User SA-MIMO System

In this paper, a novel multiple antenna system framework, which combines smart antennas (SA) with multiple-input-multiple-output (MIMO) at the transmitter, is proposed. The downlink capacity of the single-user SA-MIMO wireless systems is investigated. The joint optimization problem corresponding to the capacity is deduced. After that, upper bounds of the capacity are given in general case and in the case of equal power allocation, respectively. Furthermore, in the case of equal power allocation and the same direction of departure from one transmit smart antenna to all antenna arrays at the receiver the closed-form expression of the capacity is obtained. Some numerical results are given to show that smart antennas can bring significant capacity gain for the MIMO systems due to the smart antennas gain, without additional spatial degrees of freedom, especially at high SNR with strong correlation among the MIMO channel links or at low SNR.     

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.     

关于MIMO系统的天线子集选择性能的研究

讨论了有关 MIMO 无线系统中的天线子集选择性能的问题。首先建立了 MIMO 信道模型,对信道模型进行了分析,接着对信道矩阵为非满秩的情况进行了研究,分别采用几种组合对发射、接收天线进行选择,得出不同组合对信道容量的影响。仿真结果表明,选择发射天线可以增加信道容量,选择接收天线虽然无助于增加信道容量,但在不会严重降低信道容量的前提下,可以降低系统的成本。     

Spatial multiplexing with transmit antenna and constellation selection for correlated MIMO fading channels

We consider spatial multiplexing systems in correlated multiple-input multiple-output (MIMO) fading channels with equal power allocated to each transmit antenna. Under this constraint, the number and subset of transmit antennas together with the transmit symbol constellations are determined assuming knowledge of the channel correlation matrices. We first consider a fixed data rate system and vary the number of transmit antennas and constellation such that the minimum margin in the signal-to-noise ratio (SNR) is maximized for linear and Vertical Bell Laboratories Layered Space-Time (V-BLAST) receivers. We also derive transmit antenna and constellation selection criteria for a successive interference cancellation receiver (SCR) with a fixed detection order and a variable number of bits transmitted on each substream. Compared with a system using all available antennas, performance results show significant gains using a subset of transmit antennas, even for independent fading channels. Finally, we select a subset of transmit antennas to maximize data rate given a minimum SNR margin. A lower bound on the maximum outage data rate is derived. The maximum outage data rate of the SCR receiver is seen to be close to the outage channel capacity.     

Adaptive transmit antenna selection with pragmatic space-time trellis codes

We consider the problem of selecting a subset of transmit antennas in MIMO systems to minimize error probability when only partial channel information is available at the transmitter. An upper bound for error probability of space-time coded transmit antenna selection scheme conditioned on the channel state information is presented. Based on the performance analysis, a criterion of selecting a subset of available transmit antennas to minimize the upper bound on the PEP is proposed. In contrast to other transmit antenna selection schemes for uncoded transmission or with a fixed number of antennas within the selection subset in the literature, the proposed scheme can adaptively select both a variable number of transmit antennas and their corresponding space-time codes for transmission. Furthermore, we present pragmatic space-time trellis coding schemes for slow Rayleigh fading channels. The principal advantage of the schemes is that a single encoder and decoder can be used for systems with a variable number of transmit antennas. The performance of the pragmatic space-time codes with adaptive antenna selection and the effect of the imperfect channel estimation on performance are evaluated by simulations. It is shown that the adaptive selection offers considerable antenna selection gain relative to the antenna selection system with a fixed number of antennas within the selection subset     

一种移动终端多天线方向图重构快速选择算法与基于滑动时间窗的加速实现

 多输入多输出(MIMO)系统中,天线选择技术可以在降低复杂度的同时,有效地提高系统的性能.但对于天线安装空间受限的小型终端,天线的数目将受到很大限制,本文结合方向图可重构技术,考虑基于线性接收机的空间复用系统,通过在已选择的发射天线上采用等功率分配等增益传输以减少反馈信息量.在此条件下,推导出空间相关衰落信道下自适应发射天线选择的统计容量公式下限,然后,在此基础上提出基于方向图重构的发射天线快速选择方法以最大化该容量值.此外,在实现中提出了一种基于滑动时间窗的梯度更新估计模型,缩短了算法所需时间.     

基于分布式天线选择的TD—SCDMA动态小区覆盖技术

分布式M IMO天线结构可以降低发射功率,减少小区干扰,而天线选择技术在保持了M IMO系统优点的同时降低成本。TD-SCDMA有独特的时隙结构,可将不同时隙用于不同的天线组来覆盖不同的小区。基于此,提出了一种分布式天线选择的动态小区覆盖技术,采用两级天线选择,第一级可根据用户的具体位置选择天线组并确定覆盖范围,有效减少小区干扰,同时采用了预分配天线组方法,避免了通用天线选择算法的复杂性;第二级在选定的天线组内确定具体的天线,仿真结果说明该方法具有与一般天线选择相同的性能但更简单。     

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.     

MIMO Precoder Designs for Frequency-Selective Fading Channels Using Spatial and Path Correlation

Multiple-input–multiple-output (MIMO) precoder design for frequency-selective fading channels using partial channel information based on the spatial and path correlation matrices is presented. By representing a frequency-selective fading channel as a multipath model with $L$ effective paths, a general precoding structure is proposed and used to derive optimum precoding designs that maximize Jensen's upper bound on the channel ergodic capacity under the transmitted power constraint for two cases, i.e., uncorrelated and correlated channel paths. Analytical results show that, in the uncorrelated case, the precoder structure consists of a number of parallel precoders for frequency-flat fading channels. The power assignment to each precoder and the power allocation over the eigenmodes of each precoder are calculated based on the power of channel paths and the eigenvalues of the transmit correlation matrix. In the correlated case, the precoder structure is an eigenbeamformer with the beams referred to a function of eigenvectors of the Kronecker product of path and transmit correlation matrices. Furthermore, the power allocated to each eigenmode can be obtained from a statistical water-pouring policy that is specified by the product of eigenvalues of the transmit antenna and path correlation matrices. Simulation results for different scenarios indicate that the proposed precoder can increase the ergodic capacity of MIMO systems in a frequency-selective fading environment with spatial and path correlations, and its offered capacity gain is increased with the level of correlation and numbers of antennas and channel paths.      

Capacity Analysis for Transmit Antenna Selection Using Orthogonal Space-Time Block Codes

Antenna selection for multiple-input multiple-output (MIMO) where only a subset of antennas at the transmitter and/or receiver are activated for signal transmission is a practical technique for the realization of full diversity. Despite extensive research, closed-form capacity expressions for MIMO systems employing transmit antenna selection (TAS) and orthogonal space-time block codes (OSTBCs) are not available. We thus derive the exact closed-form capacity expressions when an OSTBC is employed and N transmit antennas out of total L_t antennas are selected for transmission. The expressions are valid for a frequency-flat Rayleigh fading MIMO channel and avoid numerical integration methods     

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。     

Adaptively Grouped Multilevel Space-Time Trellis Codes

Grouped multilevel space-time trellis codes (GMLSTTCs) utilize multilevel coding (MLC), antenna grouping and space time trellis codes (STTCs) for simultaneously providing coding gain, diversity improvement and increased spectral efficiency. The performance of GMLSTTCs is limited due to predefining of the antenna groups. It has been shown that when perfect or partial channel state information is available at the transmitter, the performance and capacity of space-time coded system can be further improved. In this paper, we present a new code designed by combining MLC, STTCs, antenna grouping and channel state information at transmitter, henceforth referred to as adaptively grouped multilevel space time trellis codes (AGMLSTTCs). AGMLSTTCs use a single full-diversity STTC at initial some levels and multiple STTCs at some later levels. The single full diversity STTC at each initial level spans all transmit antennas and the STTC at each later level spans a group of transmit antennas. The channel state information at the transmitter is used to adaptively group the transmit antennas for the later levels. Instantaneous channel power gain is calculated between each transmit antenna and all the receive antennas. A subset of transmit antennas having maximum channel power gain is selected to form a group. The simulation results show that AGMLSTTCs enable to transmit more than one data symbol per time slot with improved error performance over GMLSTTCs with predefined transmit antenna grouping.     

MIMO空间复用系统的最小BER比特分配

该文基于最小误比特率(BER)准则,提出了多输入多输出(MIMO)空间复用系统的贪婪比特分配算法和基于二分法的比特分配算法。在总比特速率和每个发射天线分配相等功率的约束条件下,通过比特分配优化每个发射天线的调制方式,改善了系统的BER性能。仿真结果表明,与传统的MIMO系统相比,比特分配的MIMO系统可获得显著的信噪比(SNR)增益;与功率分配相比,比特分配在性能损失很小的情况下减少了每个发射天线的功率放大器的动态范围。     

基于最大比合并的MIMO分集系统递增天线选择算法

MIMO分集系统天线选择技术可以在不增加系统射频链路的情况下,达到与全天线几乎相同的分集增益.针对发送端采用最大比发送,接收端采用最大比合并的MIMO分集系统,提出了一种递增天线选择方法,每次增加一根天线,并使得它与已选出的天线结合起来具有最大的信噪比增益.相对于对所有可用天线集进行遍历的最优算法,它减小了需要搜索的范围和每次搜索的计算量,降低了复杂度;相对于功控天线选择算法,它考虑了新增天线与已选出天线集之间的相关性,改善了性能.仿真结果表明,在误比特率、信道容量和信噪比增益方面,此算法和最优算法性能相近,且不随可用天线数和选出天线数的改变而改变.     

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。     

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。     

线性离散码系统中基于近似容量分析的发送天线选择算法

为了降低应用线性离散码(LDC)的多输入多输出系统中发送天线选择算法的复杂度,该文利用LDC的线性变换矩阵的酉矩阵参数化性质,推导出了一种考虑LDC矩阵平均影响的近似容量表达式。近似容量表达式不涉及时间扩展的高阶等效信道矩阵的运算,从而基于近似容量的发送天线选择算法可以有效地降低运算复杂度。该文从近似容量出发,给出了最大化近似容量的发送天线选择算法和基于矩阵消元的天线选择算法。近似容量表达式为基于垂直空时分层码(V-BLAST)提出的低复杂度天线选择算法在LDC系统中的直接应用提供了理论支持。仿真结果表明,所提方案具有与最优天线选择算法相近的性能,但具有更低的计算复杂度。基于矩阵消元的天线选择算法与在V-BLAST系统中提出的基于范数和相关性的天线选择算法相比,可以获得更好的分集增益,因而具有更好的误码率性能。